Intercontinental Geoinformation Days

A geostatistical analysis of soil salinity and its impact on wheat yield in Gujranwala District

Asma Javed — 2023-12-19

This study applies geostatistical analysis to examine how soil salinity affects wheat yield in the Gujranwala area in the context of changing rainfall patterns and climate change. The goal of the research is to determine the geographical and temporal patterns of soil salinity and how they affect agricultural productivity, with a particular emphasis on wheat cultivation. Despite the use of comprehensive geostatistical techniques and statistical analysis, the study finds a strong negative relationship between wheat production and soil salinity as determined by electrical conductivity (EC). As geostatistical techniques such as Linear Regression Rate (LLR) assess the influence of soil salinity on wheat yield, Inverse Distance Weighting (IDW) examines the distribution of salt in the soil. Finding hotspots for extremely salinized soil emphasizes the need for precise controls and thoughtful land management. Increasing soil salinity monitoring, encouraging targeted irrigation, looking into crops that can withstand salt, enhancing drainage, and teaching farmers how to manage soil salinity are some of the recommendations. This geostatistical analysis concludes that there is a notable negative link between Gujranwala wheat yield and soil salinity, which offers important information to land managers, policymakers, and agricultural experts. Understanding soil salinity dynamics enables proactive measures to enhance agricultural output.

Seismicity analysis of the Eastern Hindu Kush Region using geospatial techniques

Mahnoor Qadir — 2023-12-19

This study presents a geo-statistical approach to analyze the seismicity of the Eastern Hindu Kush region using earthquake records from the past 200 years obtained from the USGS open-source geo-database. The study also utilized SRTM, Digital elevation model to visualize the spatial range, magnitude, and depth of earthquakes in the region. The IDW and Weighted Overlay Analysis approaches were employed to interpolate seismic data in a GIS environment. For seismic assessment in the Eastern Hindu Kush region, a Seismic Hazard Zonation Map (SHZM) based on fault density, seismic depth, and magnitude was developed. The map highlights that the north-eastern side of region is located in a zone with a high level of seismic activity. Western Chitral, the western part of Upper Dir, and Lower Dir fall under a moderate seismicity zone, while Swat, south-eastern Chitral, and the northern section of Upper Dir lie in a zone with strong seismic activity. The study findings revealed that the Hindu Kush Region is vulnerable to moderate and high-magnitude earthquakes, posing a risk to the region's residents, particularly given their socioeconomic status and the highly susceptible nature of their houses. As a result, the findings of this study can give significant insights to disaster management authorities in decision-making and policy planning to improve community resilience and minimize the potential negative effects of future earthquakes.

Analysis and forecasting of coastline morphology in Pakistan using digital shoreline analysis

Mazhar Shakoor — 2023-12-19

A sustainable protective strategy's design and informed coastal management depend on the assessment of coastal erosion and accretion. This study analyses Pakistani coastal dynamics from 1990 to 2020 using the Digital Shoreline Analysis System (DSAS) version 5.1 linked with ArcGIS software. The study, which focuses on erosion and accretion, uses metrics like Liner Regression Rate (LRR), End Point Rate (EPR), and Shoreline Change Envelope (SCE) to divide the area into four segments (a, b, c, and d) within the western zone. The findings show that the rates of erosion and accretion along Pakistan's coastline vary significantly. Maximum erosion rates are found on Transect Id 49, which reaches -42.28 m/yr; maximum accretion rates are found on Transect Id 105, which reaches 2.27 m/y to 2.77 m/y. Significantly, regions bordering Iran—segment d, in particular—accrete more than the original section between 1990 and 2020. The predominant process is erosion, which affects a large amount of Pakistan's coastline, especially in areas with a high concentration of industry and areas recently devastated by disasters. These results highlight the necessity of customized coastal management plans that take into account the intricate interactions between anthropogenic and natural elements in the area.

Analysis of snow avalanche causes and damages in District Chitral, Pakistan

Ramsha Sohail — 2023-12-19

Avalanches are a major problem in the Central Asian area, which includes the Karakorum, Hindu Kush, and Pamir ranges. Avalanches are frequently caused by the glaciers of Chiantar, Tirchmir, and Atrak near Chitral district. This study investigated the causes of avalanches in Chitral using data from the Digital Elevation Model (DEM) acquired from USGS. High-resolution Shuttle Radar Topography Mission (SRTM) DEM (30 m) from USGS was used to examine the causative factors such as elevation, slope, aspect, and hill shade. The objectives of the study were to determine the causes of natural avalanches, evaluate the amount of damage caused between 2010 and 2020, and provide a distribution map that shows the danger zones. Using GIS technology, it was discovered that the length and steepness of the slope, together with the lack of summit trees, were the main causes of large avalanches in Chitral. Avalanche hotspots throughout the last ten years were identified on the distribution map that resulted. Forecasters can identify danger areas and describe scenarios with the use of this information. The avalanche inventory map helps policymakers create preventative measures for risky locations in Chitral, which helps with risk management.

Mapping of frequently flood affected villages in Eastern Hindukush Region, Pakistan

Ramsha Sohail — 2023-12-19

In order to locate and map the villages in the Eastern Hindu Kush region that are frequently affected by flooding, this research offers a rigorous analysis that combines point level geocoding techniques with an extensive literature assessment. In Eastern Hindu Kush region, flooding is a frequent and destructive natural calamity that affects infrastructure and populations. This study uses information from the literature and geospatial data to identify the communities that are most vulnerable in order to solve this problem. In order to precisely pinpoint these communities on digital maps, this research uses advanced geocoding techniques, which offers insightful information for activities aimed at mitigating and preparing for disasters. This study provides an integrated picture of the flood-prone regions in Eastern Hindu Kush region by merging historical flood data with academic research findings. This allows for targeted interventions and resource allocation for disaster management and community resilience.

Optical remote sensing application of Kızılcaören-Sivrihisar (Eskişehir) REE-Thorium Deposit

Cihan Yalçın — 2023-12-19

The Kızılcaören-Sivrihisar rare earth element (REE)-Thorium deposit is situated within the Eskişehir Province of Türkiye. The deposit in question represents the sole commercially viable rare earth element-thorium (REE-Th) source within Türkiye, thus rendering it a significant supplier of these crucial minerals. The Kızılcaören-Sivrihisar REE-Thorium deposit exhibits a captivating mineral assemblage that possesses the potential to unlock valuable resources. Within the geological composition, a complex interplay of minerals takes place, involving fluorite, bastnäsite, and barite. The Kızılcaören-Sivrihisar deposit can be effectively mapped using optical remote sensing techniques. This phenomenon can be attributed to the fact that the deposit exhibits several discernible characteristics that can be identified through the utilization of optical remote sensing techniques. This study demonstrates the presence of fluorite-bearing zones, which are characterized by the fluorite index. The present investigation provides evidence for the concurrent presence of divalent iron alongside fluorite. Quartz is also present within this ore-bearing zone. Magnesite and calcite are also found within the serpentinitic-mafic zone in the study area. In conclusion, the study area successfully identified the ore-bearing fluoritic zone through the application of remote sensing processing using ASTER L1T data. The aforementioned studies have demonstrated that optical remote sensing possesses significant potential as a valuable instrument for the examination and assessment of the Kızılcaören-Sivrihisar REE-Th deposit. The utilization of optical remote sensing enables the mapping of deposits, the identification of their extent, and the evaluation of their economic development potential.

An application of remote sensing and GIS in geothermal alteration and potential in Ziga/Aksaray (Türkiye)

Hacer Bilgilioğlu — 2023-12-19

Where energy production is essential today, geothermal energy, one of the renewable energy sources, is of great importance. Ziga geothermal field, chosen as the study area, has an essential geothermal potential. Ziga Geothermal Area benefits from numerous sources, wells, thermal tourism, residential heating, greenhouse cultivation, and balneological practices. Hydrothermal alteration zones are one of the critical indicators for the exploration of geothermal fields. It contributes significantly to the exploration studies by narrowing the target areas in the feasibility studies of geothermal exploration studies. With remote sensing (UA) techniques in detecting hydrothermal alteration minerals spread over large areas, it is ensured that large areas can be evaluated holistically, and effective results can be obtained by saving time and economy. In the study, it was evaluated in a GIS environment by using ASTER satellite data to determine the hydrothermal alteration zones. The differences in the determined parameters of all alteration types in the study area were mapped with ASTER data. As a result of the data obtained by remote sensing and GIS methods, guiding data for the discovery of new potential areas in the rocks of Ziga and its surroundings are explained in detail in the study.

Comparing land motion in Chiang Mai and Bangkok, Thailand, using Sentinel-1 InSAR time series

Kunlacha Inpai — 2023-12-19

Bangkok, Thailand's capital, and Chiang Mai in northern Thailand are both susceptible to land motion due to natural and human influences. They differ significantly in geological settings: Bangkok is characterized by Neogene clay deposits prone to compaction-induced land subsidence, while Chiang Mai's motion is driven by factors like geological structure and morphology, leading to slope instability and subsidence. Sustainable development in these cities necessitates precise monitoring of geological hazard-prone areas. Radar interferometry, particularly the persistent scatterer interferometry (PS-InSAR) technique, offers a high-resolution, cost-effective solution. This study utilizes Sentinel-1 data to monitor land deformation in both cities, combining geological, morphological, and ground measurements to create deformation maps. Analysis of 61 images for Bangkok and 62 images for Chiang Mai from January 2020 to May 2023 reveals Bangkok's subsidence driven by the early Miocene geological evolution of the Thon Buri Basin, exacerbated by construction and groundwater extraction. Chiang Mai experiences vertical and horizontal motion influenced by factors like depositional environment, morphology, and lithology. Both cities face land subsidence challenges due to rapid urbanization, leading to structural damage and heightened flood risk. This research highlights the potential of PS-InSAR techniques for geological hazard and land deformation monitoring, addressing city-specific challenges and advantages.

Assessment of urbanization and different land use and land cover types on urban heat islands in growing cities, a case study: Tabriz, Iran

Khalil Valizadeh Kamran — 2023-12-19

In this study, Landsat ETM⁺ and OLI images from 1984 to 2013 were selected to examine the relationship between land surface temperature and land use pattern in Tabriz, and to investigate the impact of land use changes on the urban heat islands. First, the mono-window algorithm was utilized to retrieve land surface temperature from thermal band of Landsat images. The zonal statistic was then carried out to evaluate the area proportion of land use classes in each LST category. Finally, the urban thermal characteristic was analyzed by investigating the relationships between the land surface temperature and land use types. The results suggest that the process of urbanization in Tabriz has significant effects on the surface temperature.

Performance evaluation of spectral indices and classification algorithms for built-up area extraction using PRISMA hyperspectral images

Seyed hedayat Sheikhghaderi — 2023-12-19

This article aims to evaluate and compare NDBI, NBI, PB1BI and HIBI spectral indices and SVM, ANN and MLC classification algorithms in order to identify and extract urban constructions using Prisma hyperspectral images. took The findings of this research indicate that the classification algorithms in both Tehran and Urmia have higher accuracy than the spectral indices; So, in Tehran city, PB1BI and HIBI indices have higher accuracy than NDBI and NBI indices with overall accuracy of 85% and 86% and kappa coefficient of 70% and 72% respectively from left to right. On the other hand, in Urmia city, NBI indices with 88% overall accuracy and 77% kappa coefficient and NDBI with 87% overall accuracy and 75% kappa coefficient showed better performance than PB1BI and HIBI indices. Also, in Urmia city, the overall accuracy and Kappa coefficient of SVM and ANN classification algorithms were more accurate than MLC with over 90%. Also, in the city of Tehran, SVM and ANN algorithms with overall accuracy and high Kappa coefficient of 90% and 83% performed better than the MLC algorithm. In general, according to the effectiveness of various factors including the scope of the study, the spectral range used, the type of roof of the buildings, the types of uses, etc., the combined and comparative use of indices and spectral algorithms improves the results.

Emerging trends in geographic information systems

Samir Ganili — 2023-12-19

Geographic Information Systems (GIS) have undergone significant transformations in recent years, shaping the way we analyze and interpret spatial data. This paper explores the latest trends in GIS technology and their profound implications for various industries and society as a whole. We delve into five key trends: 1) the rise of location-based services, 2) the integration of GIS with Internet of Things (IoT), 3) advances in 3D GIS technology, 4) the increasing importance of GIS in disaster management, and 5) the ethical considerations in GIS data handling.

GIS-based soil loss estimation using revised universal soil loss equation

Ekundayo Adesina — 2023-12-19

Soil loss estimation plays a vital role in the management and conservation of land and water resources, offering vital insights for watershed-level development in various regions. This study focuses on the development of a soil loss model for Bosso Local Government Area in Minna, Nigeria, utilizing the Revised Universal Soil Loss Equation (RUSLE). Integration of Landsat images, Digital Elevation Models (DEM), rainfall and precipitation records, and soil erodibility factors was employed to estimate the average annual soil erosion within the study area. The individual parameters of the RUSLE model were integrated into the ArcGIS environment using the raster calculator in the Arc toolbox. The results reveal that an alarming 6672.83 tonnes per hectare per year of soil are lost annually in the study area. This rate of soil erosion raises concerns about the sustainability of agricultural practices in the study area. The findings underscore a critical absence of conservation practices or plans to combat and mitigate soil erosion in the region. In light of these findings, it is imperative that local government authorities, in collaboration with various ministries, take immediate action to promote and enforce conservation measures aimed at combating soil erosion within the area.

Land use and land cover classes affected by possible sea level rise in Mersin city center

Onur Güven — 2023-12-19

In this study, a sea level rise (SLR) investigation was carried out in an area representing the Mersin city center located in the south of Turkey. The study area covers an area of ca. 385 km². Future projections provided by the IPCC were used for the SLR assessment. These projections are for the years 2100, 2200, 2300, 2400, and 2500 and the SLR for these periods are 0.83 m, 2.03 m, 3.59 m, 5.17 m, and 6.63 m, respectively. It is aimed to determine the areas affected by the SLR that will occur according to these projections. In this context, land use and land cover (LULC) data were obtained from the CORINE 2018 dataset. The data obtained were adapted within the boundaries of the study area and processesed using various GIS analyses. The results have shown that all LULC classes are greatly affected by the SLR, but in varying degrees. Land losses as a result of SLR are as follows: 0.4% at 0.83 m SLR, 9.8% at 2.03 m SLR, 16.7% at 3.59 m SLR, 21.6% at 5.17 m SLR, and 25% at 6.63 m SLR.

LULC change and CO2 emissions in Shangai 2000-2020

Jianwen Zheng — 2023-12-19

The absorption and release of carbon dioxide by different types of land cover, with activities like deforestation or urbanization releasing CO², while afforestation or natural ecosystems act as carbon sinks, affecting the overall carbon balance in the atmosphere. This paper analyzes the spatial and temporal characteristics of land use and carbon emissions in Shanghai from 2000 to 2020 using the land use transfer matrix, the carbon emission estimation model, and the standardized error ellipse method. The results indicate that the total carbon emissions from land use in Shanghai have exhibited an upward trend from 2000 to 2020, with an average annual growth rate of 3.055%. The expansion of construction land has been identified as the main source of carbon emissions, while forests serve as the primary carbon sink. Spatial analysis reveals that areas with high-intensity carbon emissions are mainly concentrated in Pudong New Area, while regions with moderate carbon emissions are in Jiading and Minhang districts, gradually expanding towards the northeast. Based on these findings, it is recommended that carbon emission policies consider the characteristics of regional differences, control land use intensity appropriately, and guide low-carbon and efficient land utilization as the primary direction to achieve Shanghai's energy low-carbon transformation.

Trend analysis of precipitation and temperature in the Western Black Sea region of Türkiye

Muhammed Zakir Keskin — 2023-12-19

Climate change indicates alterations in climate parameters, involving both increases and decreases. Trend analysis enables the identification and direction of these changes. This study aims to conduct trend analysis in the Western Black Sea region of Türkiye. Non-parametric tests like Mann-Kendall and Theil-Sen Slope were employed to define temperature and precipitation changes in the region. In the analysis annual mean temperature (°C) and total annual precipitation (mm) data were used, collected from 15 different stations across the region. Mapping has been applied to visualize the results for better understanding of the findings. The results indicate an insignificant trend in precipitation across most of the region, while the temperature clearly demonstrates an upward trend.

Spatio-temporal land use/ cover changes analysis using remote sensing and landscape spatial metrics: A case study of Basin Liqvan

Khalil Valizadeh Kamran — 2023-12-19

Over time, patterns of land cover and land use change and subsequent changes are fundamental and human factor plays a most important role in this process. Ever, scientists have attempted to identify factors that cause land use changes and their impact on the environment. Therefore, in previous decades, researchers have different views collected from the field, as well as aerial photographs to detect land use changes resulting from the imposition of natural and human processes have been analyzed. Today, however, based on technological advances made in the field of remote sensing, satellite imagery can be used to more accurately evaluate the environmental changes during the process and the final results of the illustrated model. The main purpose of the ongoing monitoring of land use changes in river basins Liqvan is 1985-2006-2013. Accordingly, to explore the changes occurring in the study area, Landsat TM and ETM + Landsat images of the years 1985-2006-2013 were analyzed. Accordingly, after applying atmospheric and geometric correction, image enhancement operations performed using the maximum likelihood method of supervised classification algorithms similar actions and thematic maps of land use of the basin has been designed to Liqvan. Finally, moorland in the first place and then irrigated gardens and residential areas in the study area are eventually.

Exploring the difference between Standard Precipitation Evapotranspiration Index (SPEI) from in-situ meteorological stations and SPEIbase

Ahmad Abu Arra — 2023-12-19

Drought has destructive impacts on all sectors, such as environmental and agricultural sectors, as well as water resources management. The first step in drought evaluation and monitoring is determining the drought index. Because of its vital role, this research aims to investigate the difference between Standardized Precipitation Evapotranspiration Index (SPEI) at different timescales, 3, 6, 9, and 12-month, based on in-situ meteorological stations and SPEIbase, which is a satellite global product. They were compared in two ways: 1) using drought categorization and 2) drought index (SPEI values). The results showed a significant difference between the results obtained from each dataset. Based on the drought categorization, only 61% of the months were within the same categories. The dominant months were within the normal category (N) because of a wide range ranging between -1 and 1. Furthermore, SPEI values calculated using SPEIbase gave more extreme drought events (ED). However, SPEI using in-situ meteorological stations gave more severe drought events (SD) for all time scales. Also, a significant fluctuation can be noticed based on the difference between SPEI from the two datasets. These results can be attributed to many reasons, such as using different time periods, calculating potential evapotranspiration, and the reliability of the precipitation and potential evapotranspiration.

Monitoring changes in air pollution using Sentinel-5 data

Behnaz Ghaderi — 2023-12-19

Today, air pollution is one of the most important issues in the field of environment and human health. In the last few years, remote sensing has helped a lot in the field of monitoring, measuring the concentration of pollutants. In this article, the monitoring of air pollution changes with Sentinel 5 satellite images in the southwest of Iran was discussed. Sentinel 5 images were received using the Google Earth Engine system in January 2022 to January 2023. After the detection of NO2, CO, UV-Aerosol and SO2, a map of atmospheric pollutants with color layers was obtained and then the one-year time changes of No2, Co, UV-Aerosol and SO2 were determined with a graph. The results of the graph of monthly changes showed that the concentration of NO2 and CO in spring and summer have the highest concentration, UV-Aerosol has the highest concentration in spring, and September and October have the highest concentration for SO2 in the center and southwest of Khuzestan province.

Evaluation of the application of the multi-temporal method in Sentinel 2 satellite images for the separation of agricultural products

Samira Asadnezhand Khormazard — 2023-12-19

One of the ways to obtain information about the condition of the land is to produce land use maps. In this research, using different time series from Sentinel 2 satellite images, with the aim of choosing the appropriate classification method for the separation of land products in Ravansar city, Kermanshah province. Took based on the growing season, it was first prepared by referring to the agricultural calendar of different products of the region. By determining the time of planting, the peak of greenness, harvesting and plowing of different crops, information was collected and stored in the database for the necessary analysis to determine the time of the images based on the major crops of the study area, including (wheat, corn, barley, road, other-vegetation, other-plough-barren, water, peas, tomato) should be taken from Sentinel 2 images on two dates. By making the necessary corrections on the images, in the next step, the mentioned dates were done with the PCA method and then the classification was done with the maximum likelihood and minimum distance method. The results showed that the maximum likelihood classification was more accurate than the minimum distance method in multiple times with an overall accuracy of 94% and a kappa coefficient of 92%.

Investigating the effects of land cover land use change on surface temperature using Landsat satellite images

Esra Şengün — 2023-12-19

Global and local population growth and the rapid increase in urbanization affect nature negatively by the destruction on forests and natural lands. An additional problem can be considered as the increment of the land surface temperatures due to the heat island phenomenon. Thus, long-term monitoring of rapidly developing cities is important. In this study, Izmir, which ranks 3rd among the big cities of the country, was chosen to monitor the long-term effects of urbanization. For this purpose, a 20-year period from 2020 to the past has been examined with Landsat images. As a first step, historical land cover – land use maps were produced from satellite images using the Random Forest algorithm in the Google Earth Engine platform. Secondly, the urban thermal field variance index (UTFVI) was calculated from thermal bands of Landsat images to examine the effect of urban heat islands and their relation to urbanization progress. Results of these analyses indicated that both cities faced urbanization at the expense of forest and semi-natural area loss in this 20-year period, which is well correlated with an increase in the UTFVI values. Moreover, the increase in UTFVI values on already urbanized regions proposed that the intensity of the urban areas also increased.

Examination of earthquake effects in closed reinforced concrete structures

Muhammed Emin Işık — 2023-12-19

In this study, the collapse situation, which is one of the factors caused by design errors in reinforced concrete buildings that collapsed or were severely damaged under the influence of an earthquake, was investigated. It has been observed that columns, which are vertical load-bearing elements in buildings with closed cantilevers, are exposed to extra moments and shear forces due to various factors. It has been understood that this situation causes loss of bearing capacity and additional loss of rigidity. According to the results of the review, it has been understood that although closed exits have some economic advantages, their negative effects are much greater.

A tool for basic surveying and geodetic calculations

Muaz Ayran — 2023-12-19

With the rapid development of computer and software technologies, many web-based and mobile applications have been developed in recent years. While these programs can occasionally solve extremely basic problems, they can also solve problems that require a great deal of labour and processing power effortlessly. In the field of geomatics engineering, there are some easy problems as well as challenging and work-intensive calculations. Although there are a few web-based and mobile applications in geomatics, these applications are designed to solve only some professional problems. In this study, a web-based tool has been developed to solve almost all problems encountered in surveying and geodetic applications. All coding is written in C# programming language. User-friendly graphical interfaces (GUI) are designed to be easy to use. Sample images have also been added to the modules so that users can better understand the modules. A total of 35 modules were developed, including 20 surveying and 15 geodetic problem solutions. These modules allow surveying and geodetic problems to be easily solved in both student and professional applications. Thus, it saves both labour and time.

Time series analysis of Turkish National Sea Level Monitoring System (TUDES) level data for Amasra Station

Ahsen Çelen — 2023-12-19

The observation and prediction of sea level are crucial for various reasons including the vertical datum determination, crustal movement forecasting, oceanographic modeling, and coastal infrastructure planning. In Turkey, a sea level monitoring system has been established by the General Directorate of Mapping and aims to measure sea level. Through the Turkish National Sea Level Monitoring System (TUDES), sea level is monitored using data collected at 20 tide gauge stations at 15-minute intervals. Time series analysis is considered a highly suitable modeling and forecasting method for data that is periodically measured. In this study, time series analysis models including ARIMA, SARIMA, and Holt-Winter's methods were applied using data from the Amasra tide gauge station within the TUDES for the year 2019. Additionally, a prediction for January 2020 at the same station was performed. The results were compared with the measured tide gauge data to assess the performance of the models. Evaluation criteria included the Mean Absolute Percentage Error (MAPE) for the Holt-Winter's method and the corrected Akaike Information Criteria (AICc) for the ARIMA and SARIMA models. The SARIMA (3,0,0) (0,2,2) model with an AICc value of -1307.83, indicating a seasonality of 12, was observed to be the best-performing model.

Examining PPP accuracy in relation to altitude

Emre Akman — 2023-12-19

Online PPP services are increasing daily due to their user-friendly interfaces, quick turnaround times, the ability to evaluate data from a single GNSS receiver, and their cost-free nature. However, the veracity of the data provided by these services needs to be verified. This study examined the position and height accuracy variation provided by PPP services based on benchmark point altitudes. For this purpose, seven measurement points were established every 200 meters, starting from the sea level. Four-hour static GNSS observations were carried out at each point, and these data were first evaluated with the static post-processing method to obtain the known positions of the points. The static observations were then submitted to the popular online PPP services Trimble-RTX, AUSPOS, and CSRS-PPP, and the received position and height data were compared to the point’s known coordinates. When the results were analyzed, it was found that changes in the position data were in the order of cm, while changes in the height data were in the order of 1-2 dm, depending on the altitude of the measurement point.

Assessment of land use land cover changes through remote sensing data in Multan Tahsil

Sajjad Hussain — 2023-12-19

Land use land cover (LULC) changes are fundamental aspects of our evolving environment, reflecting the dynamic interplay between human activities and natural processes. Current study, executed to estimate LULC changes in seasonal intervals 2000, 2010 and 2020 to generate an accurate database on LULC changes from 2000 to 2020 in Multan tahsil (Pakistan) using RS data. Data were preprocessed in Arc GIS 10.1 and ERDAS IMAGINE software’s for layer stacking, mosaicking, and sub setting. After pre-proceed, the iterative self-organized supervised clustering algorism (ISODATA) of ERDAS IMAGINE software was used to perform the supervised classification. ‘Built-up area’ in 2000 occupied 15.54 % of all the classes. But in 2020, build-up area increased (911.92 %) as compare to 2020. ‘Vegetation area’ in 2000 occupied the class with 72.312 %, but in 2020 vegetation area decreased (5.06 %) as compare to 2020 and similarly ‘bare soil’ decreased (5.77 %). The study shows that building area is increasing from 2000 to 2020. Increase in building area indicates increase in population in this tahsil. Our results about LULC changes are an essential tool for informed decision-making and sustainable land management.

Urban transformation applications

Muhammed Emin Işık — 2023-12-19

In this study, urban transformation practices are discussed within the scope of renewal, arrangement and development activities of existing buildings under natural disasters and accompanying risks. The problems and deficiencies experienced in practice were examined specifically in Osmaniye city center. Urban transformation has important benefits in terms of public interest and public health. It also increases the comfort levels of city dwellers through urban planning and infrastructure improvements. Despite its many positive effects on disaster-resistant city planning and the priority of life and property safety, it is sometimes possible to encounter very bad examples as a result of incorrect or incomplete applications. When the applications carried out in Osmaniye city center were examined, it was seen that island-based large-scale transformations were more accurate in terms of time, cost and environmental order compared to partially smaller and parcel-based on-site transformations.

Comparison of machine learning regression methods for mass real estate valuation

Batuhan Kamil Sağlam — 2023-12-19

Efficient management of real estate requires an objective assessment of their values by using scientific approaches. Valuation is key for value-related applications such as purchase and sale, taxation, expropriation, and urban regeneration. Mass valuation reduces time and costs by evaluating multiple properties simultaneously. Leveraging statistical analysis and predictive capabilities of machine learning enhances accuracy and speed in real estate valuation. This study focuses on applying many regression models for mass valuation of residential properties in Melbourne, Australia, aiming to improve accuracy and efficiency for stakeholders. Evaluating various algorithms, including Linear Regression, Decision Trees, Random Forest, Bagging, AdaBoost, Gradient Boosting, and XGBoost, on Kaggle's open data, performance metrics are calculated. Notably, ensemble methods like Random Forest and XGBoost consistently outperformed others by capturing nonlinear relationships of determinants and predicting the value accurately. Finally, applying the Inverse Distance Weighting (IDW) interpolation method, a real estate value map is generated for the study area. This study aims to uncover machine learning's role and limitations in real estate valuation by comparing the performance of different ensemble learning methods. The findings highlight the significance of advanced regression models in improving valuation practices, supporting decision-making, and enhancing market efficiency.

Spatial clustering of villages: a solution for agricultural area management: Case study of Aghmiyun agricultural area, East Azerbaijan Province, Iran

Javad Ghasemi — 2023-12-19

All of the world's basic needs are provided by the agricultural sector, and it also provides the raw materials required for industrial processes. Thus, the appropriate administration and development of agriculture are crucial. Like a number of other countries, Iran faces numerous social, economic, environmental, institutional, and human challenges in the development and administration of its agricultural sector. For managing the agricultural sector, Iran has established many different kinds of organizational structures. The Agricultural jihad centers work at the lowest level of the Iranian agriculture sector's governmental administration hierarchy. Each agricultural jihad center covers one or more rural district and a number of villages. The villages covered by each center are divided among the experts who work in the center. How to divide up villages among experts is a major problem facing agricultural jihad centers. Typically, the number of villages under expert administration is not homogeneous, and the allocation of villages among experts is not done appropriately. In this study, village classification has been investigated utilizing four different spatial clustering techniques: KMeans, KMedians, KMedoids, and Spectral Cluster. The findings indicate that while all of these techniques are capable of spatial clustering of villages, KMeans and KMedians are the most effective and useful techniques for clustering.

The investigation of house value criteria in Atakum-Mimarsinan District Pre- and PostPandemic by multiple regression analysis

Simge Anaklı — 2023-12-19

Real estate valuation is the impartial appraisal and determination of the value of a real estate property by evaluating its characteristics such as utility, quality and environment. In recent years, the whole world has faced the Covid19 pandemic. Although the pandemic has actually ended, its impact on human life still continues. It has been observed that living habits have changed in every field due to the pandemic. This study has been prepared by wondering the impact of this change on the importance of the criteria that affect the house valuation. Different methods can be used in real estate valuation. These approaches are categorized under 2 main headings: traditional methods, modern methods and statistical methods. The aim of this study is to analyse the data before and after the pandemic in Atakum-Mimarsinan district of Samsun province using a multiple regression model in the Minitab program and to compare the change in the coefficients of the criteria affecting the house value. As a result of the study, when the coefficients of the criteria affecting the house valuation pre-and post-pandemic are compared, it is concluded that the coefficient of the floor area has decreased, while the number of rooms has become more important.

Detection of collapsed buildings from post-earthquake imagery using mask region-based convolutional neural network

Esra Yildirim — 2023-12-19

After large-scale natural disasters such as earthquakes, tsunamis, and floods, the rapid identification of collapsed buildings from high-resolution imagery plays a crucial role in post-disaster damage assessment, reconstruction, and emergency rescue operations. Deep learning (DL) architectures, widely applied across various scientific domains, have also been used for extracting damaged buildings from aerial and satellite images. This study is focused on identifying collapsed buildings using a DL algorithm applied to remotely sensed data collected after the February 6, 2023, Kahramanmaraş earthquake in Türkiye. To achieve this, post-earthquake WorldView-3 image with a spatial resolution of 0.3 m were obtained to establish a building dataset, from which the boundaries of collapsed and intact buildings were manually outlined. The Mask R-CNN model was then trained and validated using various hyperparameter combinations to optimize its performance. Experimental results revealed that the Mask R-CNN model with a ResNet-50 backbone yielded the most accurate results, successfully distinguishing between intact and collapsed buildings with an Average Precision (AP) of approximately 81% and 69%, respectively. The findings of the study illustrate the promising potential of using Mask R-CNN with high-resolution imagery for the detection and mapping of collapsed buildings following earthquake events. This application is particularly significant for post-disaster operations and mitigation studies.

Waterbody change detection using Sentinel-3 thermal imagery: A case study of Mighan Wetland, Iran

Maryam Sadat Aghamiri — 2023-12-19

The wetland ecosystem is an important indicator of climate change and valuable ecosystems for environment and human being that offer substantial services. This study detects the changes land surface temperature in Mighan wetland in 2018 and 2023 by using Sentinel-3 SLSTR data. Two essential factors were used for detection. LST and DTR factors detect changes in water bodies accurately and correctly. The study finds that in the eastern and southern regions of the wetland, there is a decrease in daily LST, indicating a decrease in water temperature. In the central and western regions, there is a decrease in land temperature. The nightly LST trend shows variations between different regions of the wetland, with the eastern region experiencing lesser changes compared to the central and western regions. Additionally, the article analyzes DTR trends and finds that differences between day and night temperatures decreased over time in the eastern and southern parts of the wetland. These findings contribute to understanding temperature dynamics in wetland ecosystems and their potential implications for climate change impacts.

Impact of climate change on the assessment of the content of the indicator organic suspended matter and sea surface temperature of the Caspian Sea

Ismayil Zeynalov — 2023-12-19

The location of Azerbaijan in relatively low latitudes determines an intense influx of solar radiation and an increased value of the radiation balance (RB) of the underlying surface. The surface of the Caspian Sea causes significant changes in the temperature of the lower atmosphere, thereby affecting the climate of the surrounding areas. Oil pollution of coastal waters and the spread of oil films over large areas have a significant impact on the temperature of the surface layer of air. Consequently, the human factor can influence climate formation and lead to further deterioration of the condition of coastal ecosystems. Limited ground-based observation networks and unreliable calculation methods prevent us from correctly identifying these changes. The application of statistical methods of analysis to study climate on a global scale is unrepresentative due to the limited capabilities of the ground-based observation network. The advantage of space means in studying the climatic characteristics of the territory of Azerbaijan allows, based on the transformation of satellite observation data and interpretation of the resulting time series, to solve these problems, with further presentation of the final information at the nodes of a one-degree regular grid. This allows you to observe changes not at one point in space, as was done, in the traditional vertical column of the atmosphere, but in the zonal profile (horizontal aspect).

The impact of climate change on the temperature regime of the Kelbajar and Lachin regions of the Republic of Azerbaijan

Said Safarov — 2023-12-19

In an article based on reanalysis data MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) for the period 1980-2022 the general trends in the temperature regime of the Kalbajar and Lachin regions, which are part of the modern East Zangezur economic region, were studied. It has been determined that during the period under review there is a tendency to increase average annual and seasonal temperatures. Temperature trends for all seasons and annual periods were statistically significant at the 5% confidence level. Calculations showed that the average annual air temperature in the period 2001-2022. increased by 0.9 °C compared to the period 1980-2000, which is consistent with the results obtained in other regions of the republic. The largest increase in average monthly temperature was recorded in February (1.7 °C), March (1.8 °C) and October (1.3 °C). The largest increase in the maximum average temperature was observed in March (2.7 °C) and December (1.9 °C), and the minimum average temperature in October (3.5 °C). A decrease of 0.6°C in the minimum average temperature in January was recorded.

Applicability of satellite data in estimating actual evapotranspiration by SEBS algorithm (Mughan plain, Ardabil, Iran)

Mahmoud Sourghali — 2023-12-19

Land surface evapotranspiration (ET) is of importance for environmental applications including optimization of irrigation water use, irrigation system performance, crop dehydration, drought mitigation strategies. In this regard, the SEBS algorithm is one of the most widely used algorithms in the field of calculating real evaporation and transpiration. This algorithm uses satellite equipment observations and meteorological information to estimate the energy flux and includes a tool to determine the land surface (such as albedo, surface emissivity, surface temperature, vegetation index, etc.) from satellite images. In this research, using the spectral data and thermal band of Landsat 8, the actual evapotranspiration rate of Iran's Mughan plain in Ardabil province has been estimated. Also, in order to validate the results of the model, the results were compared with the results of the Penman month. Comparing the results of the SEBS algorithm with FAO-Penman-Monteith shows similar values, so it can be concluded that the SEBS algorithm can be a suitable alternative to the traditional methods of calculating Actual evapotranspiration.

The modeling and analysis of empirical systems with complex networks

Leyla Naghipour — 2023-12-19

Network construction is an acceptable approach for better understanding the behavior of complex system which can be used to reveal the pattern of collective dynamics for realizing physical interactions in the dynamical system. In this case, characterizing functional connectivity of complex networks for studying a broad class of natural and artificial systems from the measures of correlation and causality is of utmost importance to correctly unravel physical phenomena of the system. Many network reconstruction approaches are based on heuristically thresholding the correlation matrices resulting from pairwise correlation analysis according to experimental methods. Other approaches compare the observed correlations against null models in the statistical analyses, obtaining results which are statistically more robust. Different methods were used, including cross-correlation (CC), spectral coherence (SpeCoh), mutual information (MI), transfer entropy (TE), Spearman's rank correlation (SC) and convergent cross-mapping (CCM). The methods were applied to linear and nonlinear collective dynamics by autoregressive moving average (ARMA) and Logistic map (LOG) models, respectively. The dynamics of interconnected units was simulated from different complex topologies widely observed in empirical systems with well-known network models. The methods of MI and CCM were chosen after examining on the artificial cases consisting of desirable features of the real-world systems.

Assessing algae accumulation in an artificial pond using UAV-based orthophoto

Seyma Akca — 2023-12-19

Artificial ponds serve as critical resources for various human activities, including agriculture, aquaculture, and water management. However, unchecked algae growth in these man-made water bodies can lead to eutrophication, oxygen depletion, and ecological degradation. Monitoring and managing algae accumulation in artificial ponds are essential for environmental sustainability. Traditional assessment methods have limitations in terms of spatial and temporal resolution, making them unsuitable for real-time monitoring. Recent advancements in Unmanned Aerial Vehicles (UAVs) and remote sensing technology have opened new possibilities for environmental monitoring. This study explores the application of UAV-based orthophotos and band ratios for assessing algae accumulation in artificial ponds. Structure from Motion (SfM) photogrammetry is used to create high-resolution orthophotos, providing detailed spatial information. Band ratios, derived from spectral information in RGB images, are employed to detect algae presence. Results show that UAV-based photogrammetry generates detailed orthophotos with a ground sampling distance of 1 cm, allowing for the identification of fine-scale features in the pond. The red/green band ratio proves effective in consistently detecting algae presence. The study demonstrates the potential of UAV-based RGB band ratios for accurate algae assessment, enabling informed decision-making and timely interventions to preserve the ecological integrity of artificial ponds. This innovative approach provides a valuable tool for safeguarding water quality and contributing to the sustainability of essential aquatic ecosystems.

Classifying unmanned aerial vehicle images for urban vegetation mapping utilizing SVM

Zahra Azizi — 2023-12-19

This study focuses on the potential of sUAVs for mapping urban vegetation. The researchers compared the effectiveness of maximum likelihood and SVM algorithms for classification purposes. Additionally, they tested different window sizes to determine the optimal size for calculating textural indices. An ortho-mosaic image was used to analyze the vegetation. A total of 748 images were collected from a height of 100 meters using a low-cost UAV, resulting in a resolution of 2.56 cm per pixel. To ensure accurate results, a high overlap of 90% forward and 80% side overlap was maintained to minimize vegetation masking by tall buildings. Ground control points were collected using GPS RTK technology, and all images were processed using Agisoft PhotoScan v1.27 software with a root mean square error of 0.2 pixels. Eight textural indices, including mean, standard deviation, homogeneity, contrast, dissimilarity, entropy, correlation, and angular second moment were extracted using gray-level co-occurrence matrix (GLCM). These texture indices were calculated using six different window sizes ranging from 3×3 to 45×45. The findings of this study will contribute to the understanding of sUAV-based remote sensing for mapping urban vegetation and provide insights into the most effective classification algorithms and window sizes for calculating textural indices.

Crack detection for bridge inspection utilizing UAV photogrammetry technique

Abdurahman Yasin Yiğit — 2023-12-19

With the expansion of transportation networks, road networks are also growing, resulting in an increased usage of bridges. Consequently, there will also be an increase in bridge deformations due to increased crossings. Inspecting bridges incurs significant maintenance costs. As a promising strategy to safeguard bridges, a bridge inspection method using UAVs with vision sensors is proposed. Crack identification methods on historic concrete bridges are investigated in this paper using a high-resolution vision sensor attached to a commercial UAV. In the preflight, a photorealistic 3D model based on point cloud is created before detecting cracks on the structural surface and calculating their thicknesses and lengths. A field experiment was performed to authenticate the suggested method, and the scientific findings demonstrated the efficacy of bridge inspection using UAVs in detecting and quantifying cracks in infrastructure.

Monitoring shoreline and areal change with UAV data

Adem Kabadayı — 2023-12-19

It is important to determine the spatiotemporal changes of wetlands for their sustainable management and effective use. In this study, the shoreline of Topçu Pond used for agricultural irrigation in Yozgat, Turkey in 2022 and 2023 was determined with the help of contour lines. In addition, the maximum capacity elevation of the pond was determined, and its maximum area was calculated. As a result of the study, the water level and pond area for the year 2022 were calculated as 1191.56 m and 99165.58 m², respectively, and the water level and pond area for the year 2023 were calculated as 1195.05 m and 142487.95 m², respectively. The maximum elevation and area of the pond were determined as 1200.65 m and 279019.94 m² respectively.

Assessing the contribution of RGB VIs in improving building extraction from RGB-UAV images

Richmond Akwasi Nsiah — 2023-12-19

Buildings are a fundamental component of the built environment, and accurate information regarding their size, location, and distribution is vital for various purposes. The ever-increasing capabilities of unmanned aerial vehicles (UAVs) have sparked an interest in exploring various techniques to delineate buildings from the very high-resolution images obtained from UAVs. However, UAV images have limited spectral information, and VIs have been adopted to increase the spectral strength of UAVs for building classification. This study aims to assess the contribution of four VIs, the green leaf index (GLI), red-green-blue vegetation index (RGBVI), visual atmospherically resistant index (VARI), and triangular greenness index (TGI), in improving building classification using geographic object-based image analysis (GeoBIA) approach and random forest classifier. For this purpose, five datasets were created and comprised of the RGB-UAV image and the RGB VIs. The experimental result indicated that the RGB + VARI dataset had the best improvement in the building classification based on four evaluation metrics: overall accuracy (0. 9799), precision (0. 9806), recall (0. 9806), and F1-score (0. 9806). The combination of all the VIs with the RGB image, on the other hand, attained results lower than the standalone RGB image: accuracy (0. 9507), precision (0. 9570), recall (0. 9368), and F1-score (0. 9468).

The effect of the number and distribution of ground control points (GCP) on map production

Volkan İzci — 2023-12-19

Thanks to recent advances in data collection technologies from Unmanned Aerial Vehicles (UAVs), very large data sets covering important surfaces with centimeter-scale resolution can be rapidly collected, resulting in the opportunity to analyze areas digitally. With the presence of a regular monitoring program carried out over a wide area, UAVs provide significant advantages in the cost of data collection. Many studies in the literature have focused on finding an effective and sustainable research strategy to limit costs and study times. Unmanned aerial vehicle (UAV) photogrammetry has recently emerged as a popular solution to obtain certain products required in linear projects such as orthoimages or digital surface models. The main reason for this is the ability to provide these topographic products quickly and economically. It is important to know how many ground control points (GCPs) are required to guarantee a certain degree of accuracy and how to distribute them across the work area. The purpose of this study is to determine the number of GCPs for a work area and how to distribute them to provide higher accuracy.

Delineation of groundwater potential zone and mapping using GIS/Remote Sensing techniques and Analytic Hierarchy Process (AHP) for District Bhimber, Pakistan

Muhammad Shahid Usman — 2023-12-19

Groundwater plays a critical role in the sustainability of both ecosystems and human activities. This study presents an integrated methodology that combines the Analytic Hierarchy Process (AHP), Multi-Criteria Decision Analysis (MCDA), Geographic Information Systems (GIS), and Remote Sensing (RS) techniques. The main objective is to precisely delineate groundwater potential zones in the Bhimber district, leading to the creation of a comprehensive guide map for optimized groundwater exploration and utilization. This approach aims to promote sustainable resource management and overall development. The methodology involves data collection from diverse sources, including the Shuttle Radar Topography Mission (SRTM) for digital elevation models and remote sensing satellite images for thematic layers like geology, rainfall, slope, soil, drainage density, land use, and lineament density. Integration is facilitated through multicriteria evaluation. Using weighted overlay analysis and AHP-guided weight assignment, potential groundwater zones are systematically identified and mapped. The resulting groundwater potential map is categorized into four classes: Poor, Fair, Good, and Excellent. The findings reveal distinct patterns of groundwater potential in the district. The eastern region stands out with an excellent groundwater potential covering 26 square kilometres, attributed to substantial rainfall and the presence of water bodies. The mid-eastern and western sectors exhibit good potential (512 sq km), influenced by water bodies and consistent rainfall. Elevated terrains correspond to fair potential (779 sq km), while the upper north-east part indicates a Poor potential (24 sq km). This integrated approach enhances informed decision making, boosts resilience, and spurs socioeconomic development. Furthermore, the study contributes to scientific insights on groundwater dynamics, laying the groundwork for future research. The study underscores the effectiveness of GIS, RS and AHP in addressing complex groundwater management challenges, offering valuable information for global water resource management efforts.

Spatial distribution of public services and facilities in the Sahand new city of Iran

Shiva Sattarzadeh Salehi — 2023-12-19

With the increasing growth of urbanization in the world, the cities that are developing, including Iran, with unequal services and population distribution. In this way, its instability is achieved in the form of spatial and social inequality, and it is based on it due to the deprivation of citizens from urban services and the increase of the gap. Therefore, in this research, the new city of Sahand has been investigated for the distribution of urban services and facilities using four indicators of population, electricity and energy, water, and green space. The information needed for the research has been prepared by document-library and field methods. The fuzzy method was used to describe the indicators, and then the mentioned indicators were analyzed in the ArcGIS software environment with Moran's spatial autocorrelation analysis. The results show that the Moran values of population, water, electricity, and green space are 0.17, 0.15, 0.15, and 0.03, respectively, so that the first three indicators follow a strong cluster pattern, while the green space index is scattered in the surface of the city is distributed.

Geopark Potential of Osmaniye Province

Nuri Erdem — 2023-12-19

Osmaniye province is a city with limited economic opportunities, which was heavily damaged by the earthquakes centered in Kahramanmaraş on February 6, 2023, and where the rural population is predominant. Natural, cultural and geoarchaeological sites with potential for establishing a geopark in the province identifying geosites, protecting them and bringing them into geotourism will make significant economic, social and cultural contributions to the region. The landforms, caves, hot springs, castles and especially the current view of the Lalegölü volcano found in Osmaniye also reflect information about the creation of the world and the change it has undergone. These and similar features increase the potential of a UNESCO-tagged geopark area in the province. Projecting this potential and opening it to geotourism is important for the protection of the geoheritage in the region.

Logging methodology decision-making with the new high-resolution DEM of Türkiye

Arif Oguz Altunel — 2023-12-19

There are many ways one can decide if an engineering related undertaking would be feasible and productive when the topography is thoroughly and precisely investigated before it takes shape. Forestry is just one profession that proper planning is of the essence when it comes to the logging phase of the entire production process. Logging in Türkiye is primarily handled over an ever-growing forest-road network. Although the specialized equipment e.g. yarders, tractor-winches, are also put into the works, their share and production capacity is limited and confined to certain parts of the country. Thus, timber production primarily revolves around direct tractor-skidding throughout the forest floor, taking the felled log from the stump to the nearest road. Here, topography is the real constraint in production method decision-making. Topographic maps have long been used to extract topographic parameters. However, Türkiye recently announced the completion of first national high-resolution digital elevation model, 5 m DEM. High precision, which would be achieved utilizing this DEM, reemphasized the importance of slope and topographic roughness in primary transport planning. In this study, we calculated the amount of slope and topographic roughness acreages in two forest planning units based on elevation differences. Both yielded enough extreme surface acreages, which would question the expansion of road building and justify the adoption of specialized equipment.

Spatial and regression-based missing precipitation data imputation: Western Black Sea region

Seyma Akca — 2023-12-19

The study of natural phenomena in the environment influences the shaping of human geography. Investigating the occurring physical events is achieved by measuring the magnitudes in nature. These measurements are then structured within certain models, and the resulting outputs are used in engineering applications. However, measurements taken from nature or a system may not provide continuous data due to human and sensor-related errors or inadequacies, resulting in gaps or discontinuities in data acquisition. The success of the method in the missing data completion problem is still an important research topic, as it is influenced by various factors such as the characteristics of the data and the type of missing data. Particularly, the lack of precipitation observation data due to climate change poses serious risks in the planning of water structures. In this study, spatial-based inverse weighted distance (IDW), regression, and statistical methods such as mean and median values are used to fill in and complete missing precipitation data obtained from meteorological stations in the Western Black Sea Region. The results of the study conducted at 10 stations showed that the spatial-based method, IDW, produced more successful results.

Monitoring gully erosion from UAV data

Yunus Kaya — 2023-12-19

Gully erosion is recognized as an important process of land degradation. Continuous monitoring of gully erosion is important to determine the damage caused to the land. Terrestrial imaging systems such as handheld cameras are inadequate for monitoring gully erosion damage. Aerial surveys by Unmanned Aerial Vehicles (UAVs) play an important role in monitoring gully erosion. The aim of this paper is to monitor gully erosion with digital photogrammetry technique using UAV data. In this study, Digital Elevation Model (DEM) and orthophoto were produced with UAV data and the directions of gully erosion were determined. This study is also a preliminary study to determine the multi-temporal change of gully erosion.

Evaluating the ground point classification performance of Agisoft Metashape Software

Nizar Polat — 2023-12-19

This paper investigates the complex process of extracting bare land surfaces from point clouds, with a particular focus on filtering out objects such as trees, buildings, and vehicles. It underscores the importance of this task in diverse domains, including cadastral surveying, base mapping, and various geographical sciences, all while excluding specific reference to LiDAR and GIS applications. The research provides an extensive exploration of different algorithms used for point cloud filtering, culminating in a comprehensive evaluation of Agisoft's ground point filtering algorithm in contrast to the well-recognized CSF method. For this comparison, an Unmanned Aerial Vehicle (UAV) flight was performed at Harran University's Osmanbey campus to generate the necessary point cloud. The results of this assessment reveal that a significant portion of the obtained points pertains to ground points, underscoring the efficacy of the filtering process in producing Digital Terrain Models (DTMs). The numerical findings demonstrate that the overall accuracy stands at 0.002, with minimal Type I and Type II errors, reaffirming the robust performance of the filtering algorithms in producing accurate DTMs.

The effect of segmentation parameters on extracting the crown area of Tehran pine trees (Pinus eldarica)

Ali Hosingholizade — 2023-12-19

Man_made forests have been created with ecological goals such as preserving water and soil resources and economic goals such as wood production. These forests help reduce pressure on natural forests. Therefore, knowledge of the state of quantitative and qualitative features of the forest has always been of interest to the managers of these types of forests and to help them in future planning and achieving primary goals. The purpose of this research is to compare the crown area of Eldarica pine trees in Pardisan Park, North Khorasan province with the change of density parameters in stages 0.1, 0.3, 0.5, 0.7, 0.9, 1 , scale in stages 0.1,0.5,0.7,0.9 and Shape in stages 25, 50, 100 ,150. The results showed that the change in each of the parameters brings different results in the estimation of the tree's crown surface. Also, the results showed that the best result was obtained in (density=0.5, scale=25, shape=0.1) and the worst result in (shape=0.9, compactness=0.1, scale=150).

Digitization and archiving of Turkish motives by photogrammetric methods

Eda Menekşe — 2023-12-19

Individuals bear significant responsibility in carrying out the essential and selfless work that ensures an increased level of knowledge and culture within Turkish society. Additionally, they strive to preserve cultural values that have been harmed or are at risk of disappearing due to various factors. These efforts include documenting and passing along such values to future generations. At this stage, individuals communicated their thoughts through cave art, rock art and woven textiles. Within this context, individuals consider, design, and weave together the events and situations they wish to convey. At this point, motifs play a crucial role and are comparable to the constituent words of a sentence. Understanding the meaning of the motifs allows for grasping and interpretation of the essence of the woven textiles. Carpet and rugs possess artistic characteristics and unravel the socio-cultural context of their era and their makers. Hence, they offer a historical reflection. The patterns on carpets and rugs unveil a spiritual depth and convey meaning by integrating its symbolism with the object on which it is exhibited, through formal connotations, bestowing a unique identity upon it. It could be argued that the symbols and motifs found in traditional carpet and rug weaving are representative of the attitudes and behaviors of their weavers.

3D modeling of a stone sarcophagus at Kanlıdivane Ruins

Aydın Alptekin — 2023-12-19

Türkiye has a wide cultural heritage inventory. Many historical monuments have survived until today without being damaged. However, these historical monuments are destroyed due to natural and human reasons. In order for these works to regain their original state after being worn out, their current condition must be modeled in three dimensions (3D) in a computer environment. In this study, photographs of a sarcophagus, made of stone material, located in Mersin Kanlıdivane Ruins were taken with a mobile phone. Using the photographs obtained, a 3D model of the sarcophagus was created on a computer. The 3D model created can be used both to promote the region in tourism and to restore the sarcophagus when it is damaged in the future.

Use of photogrammetry in criminology

Muhammed Emin Bıyık — 2023-12-19

Criminology is a scientific discipline which explains the commission of crime, studies criminal conduct and its origins, and deals with preventing and combating crime. It is widely considered as a field of observation that can play a vital role in promoting a more peaceful society. By identifying a sustainable strategy for a harmonious societal response to crime, criminology can serve as a catalyst for societal transformation. The primary objective of criminology is to guarantee that the evidence found at crime scenes is gathered and documented without incurring any damage or loss. In the traditional approach, police officers and forensic experts take various measurements and photographs of the crime scene. This method consumes a considerable amount of time to resolve the case, and the reconstruction of crime scene drawings is carried out manually. This approach presents various limitations, including time constraints, imprecision, and the restricted view of findings in just two dimensions (2D). However, these drawbacks can be addressed with the implementation of photogrammetry, a scientific method for observing and quantifying objects in 2D or 3D by analyzing photographic data with specific metrics for documentation and interpretation.

The accuracy evaluation of point cloud data generated with iPhone 15 Pro Next Gen LiDAR sensor

Ramazan Alper Kuçak — 2023-12-19

Low-cost LiDAR sensors have recently become preferred in many fields by architects, geomatics engineers, industrial design, virtual reality applications, and many other disciplines for rapid 3D model generation. Recently, 3D models created with LiDAR sensors of smartphones (iPhone and iPad LiDAR sensors) have become preferred in many areas for 3D model production. This study discusses the accuracy evaluation of point cloud data automatically generated by the iPhone 15 Pro LiDAR sensor. Therefore, a point cloud was created for the same object with the iPhone 15 Pro LiDAR Sensor, and SiteSCAPE and Scaniverse mobile applications were tested. Our results show that the performance of the iPhone 15 Pro LiDAR Sensor is affected by mobile software technical capabilities. In addition, the results generally concluded that the iPhone 15 Pro LiDAR sensor can be used in many geomatics applications for point cloud generation, but it can be used as auxiliary data for survey studies due to its shortcomings.

Terrestrial photogrammetry and handheld laser scanning technique in 3D modeling of small objects

Zekeriya Kaçarlar — 2023-12-19

Cultural heritage works are an important tool in shedding light on a society's past to the future and keeping its social values alive at all times. Cultural heritage; We can examine it in three different ways: concrete, intangible and natural heritage. Nowadays, there are many methods and techniques used in 3D modeling of cultural heritage works. In recent years, laser scanning and photogrammetric techniques have been used in 3D modeling of objects of all sizes. In this study, two objects of different sizes were modeled using photogrammetric and hand-held laser scanning methods and the resulting models were examined. 3D models of the objects were created using two different methods, and the lengths of the same places were compared on the resulting models. While the measurements were obtained, the places to be measured were clearly observed in the measurement values obtained from the photogrammetric method, and values close to the measurement value obtained with the electronic caliper were obtained. Since the point cloud density was not sufficient in the measurements obtained by hand-held laser scanning, the image locations obtained from it could not be selected exactly and approximate measurement values could only be taken. Of the two methods, handheld laser scanning was not affected by ambient lighting and the scanning process was completed faster. Handheld laser scanning is not an applicable technique for small-sized objects because it does not create a sufficiently dense point cloud. It has been concluded that the photogrammetry technique is a suitable technique for 3D modeling of small-sized cultural heritage artifacts and that the resulting models can be used safely in studies.

A comprehensive study on enhanced accuracy analysis of LiDAR data

Berkan Sarıtaş — 2023-12-19

LIDAR technology, a prominent remote sensing technology widely employed today, offers a highly reliable means of swiftly and accurately gathering data. This research project aims to generate a Digital Terrain Model (DTM) from a LIDAR dataset featuring urban attributes. The chosen tool for this endeavor is the CSF Filter algorithm within Cloud Compare, an open-source software, with an emphasis on assessing the model's precision. Within the CSF Filter algorithm, we examined the accuracy of the Surface Approximation Mesh (SAM) when various cover values were employed: 0.1, 0.5, 1, 2, and 5. Our investigation primarily revolved around calculating the volume disparity between a manually created reference model within a computer environment and the models generated through filtering. This analysis allowed us to pinpoint the most suitable parameter value for creating an accurate model. The results indicated that opting for a cover value of 0.5 produced the most accurate model. Notably, when a cover value of 5 was chosen for the input parameter, the largest disparities were observed between the resulting model and the reference model.

Investigating the utilization of iPhone lidar sensor in documenting cultural heritage

Emine Beyza Dörtbudak — 2023-12-19

Historical artifacts and archaeological remains are critical documents that contribute to our understanding of a society's history, culture, and lifestyle. Historical artifacts can be damaged for various reasons. Damages hinder the sustainable preservation of the artwork by complicating the understanding of culture and art. Therefore, documenting the current state of historical artifacts and recording their features helps minimize damage. There are various methods for documenting historical heritage, one of which is photogrammetry, an image-based technique that obtains three-dimensional data by combining two-dimensional images taken from different angles., Another technique that can be employed in the documentation process is Light Detection and Ranging (LIDAR). A Lidar device sends out brief pulses of laser beams to its surroundings. These beams collide with and bounce off objects nearby. Lidar measures distance by detecting these reflected beams. In this study, a 3D point cloud of a relief sculpture in the Kizilkoyun Necropolis was created using photogrammetry and the LIDAR sensor added to smartphones.

Investigation of the usability of handheld laser scanners in reverse engineering applications

Yaren Doğdu — 2023-12-19

Reverse engineering allows for the creation of Computer Aided Design (CAD) models for both new and existing products through surface data capture. CAD is a creative process that utilises computer systems and can be software or hardware based. Typically, CAD data is a software-based tool that is used for design purposes. This process requires computer technology to assist in the creation of technical drawings by incorporating professional concepts. In reverse engineering, prototyping is necessary to quickly fabricate physical parts, assemblies, or models using CAD. Rapid prototyping, a manufacturing technology, enables the creation of physical models directly from 3D CAD drawings. Prototyping enables the design of pre-presentation products before the final product. The aforementioned process involves editing the designed products to create the final product. Therefore, prototyping is a crucial step for ensuring the required quality, accuracy, and precision of the final products in reverse engineering. As such, handheld laser scanners - capable of collecting data at lower densities than their ground-based counterparts - are being evaluated in this field. Although handheld lidar devices are typically preferred for modelling small objects in confined spaces. The study used a handheld lidar device due to its instant and efficient data acquisition, lower cost compared to ground-based lidar, and easy accessibility. Three types of objects were modelled in 3D using handheld laser scanners, which are viewed as an alternative to ground-based laser scanners within the field of reverse engineering. These objects were categorized based on their size, either small, medium, or large scale. For this study, identical models underwent scanning using both a ground-based laser scanner and a handheld laser scanner, followed by a comparative analysis.

Indoor mapping with wearable laser scanner and iPad lidar

Doğukan Sugölü — 2023-12-19

Efficiently surveying complex indoor environments remains a challenge due to the accuracy demands of interior geometric data. Laser scanning technology in indoor and outdoor mapping has significantly advanced the field, surpassing conventional measuring devices. Indoor and outdoor mapping processes have typically depended on acquiring terrestrial laser scanner point clouds, a time-consuming and costly technique. Alternatively, we present a novel indoor mapping strategy utilizing simultaneous localization and mapping (SLAM) based on a wearable mobile laser scanner and a laser sensor incorporated into portable iPad tablets. This approach has already been successfully tested in mapping processes, offering a more efficient and economical alternative to conventional terrestrial laser scanning point clouds. Indoor scanning is conducted in this methodology. Initially, the specified region is scanned with a ground-based laser scanner, and the resultant data serves as a reference. Subsequently, this area is scanned with wearable and iPad laser scanners, and a comparative analysis is executed. Based on the case study area findings, the proposed technique could be an alternative to the portable and wearable laser scanning method. This alternative provides notable benefits regarding accuracy and time efficiency for point cloud laser scanning at a local level.

Evaluation of point cloud software in terms of 3D architectural drawings

Ali Ulvi — 2023-12-19

In 3D reconstruction, the point cloud is crucial for preserving the geometric data of the target object. Following the acquisition of data by 3D laser scanner or image-based techniques, several software options are available for analyzing and processing the point cloud. In this investigation, terrestrial laser scanning was employed for point cloud acquisition, with subsequent analysis being carried out using Sketchub and Pointcab software. Ultimately, a web-based application, Sketchfab, was utilized to create a virtual reality simulation.

Incorrect use of wearable mobile LiDAR: Example of Mersin Soli Beach and Ankara National Library Underpass

Atila Karabacak — 2023-12-19

Scanning was carried out on the Mersin Soli coast with Wearable Mobile LiDAR (GML) to determine the shore edge line without using a Ground Control Point (GCP) and without creating a closed route. As expected, deviations from the sea and errors up to decimeters were observed since the GCP was not used. In a second study, it was used in the 3D modeling of the Ankara National Library subway underpass. In the study, scanning was carried out using GML without using a Ground Control Point (GCP) and by creating a closed route. The study was unsuccessful as a result of not using GCP and having a symmetrical appearance in the field.

Assessing the vulnerability of residential lands against earthquakes and ways to reduce vulnerability using spatial analysis: Case study of Tabriz city

Sana Foroughi — 2023-12-19

Earthquakes are known as one of the most important and dangerous natural hazards in earthquake-affected areas and can lead to severe physical, economic and social damage in cities. Based on the information and data collected about Tabriz city, this article evaluates the vulnerability of urban uses against earthquake risk. The current research was carried out with a descriptive-analytical method and by using the GIS environment as well as the zoning of earthquake-prone areas, an appropriate estimate of the vulnerability of residential uses in Tabriz city was made using spatial and descriptive data. Based on the analysis of spatial data, the residential lands near the faults were examined, and by using appropriate methods, weak points and high-vulnerability uses are identified. Then, solutions to improve and strengthen urban uses are provided and suggestions are provided to reduce vulnerability and increase resistance against earthquakes. The results showed that a significant percentage of Tabriz city is in high and very high vulnerability classes. According to the seismic vulnerability zoning of the city and the distribution of vulnerable classes in Tabriz city, it can be concluded that most of the area is vulnerable to earthquakes.

Evaluation of the quality of climate time series maps extracted from GEE: A case study of Arasbaran Region - Iran

Sajjad Moshiri — 2023-12-19

As one of the 13 biosphere reserves of Iran, the precious forests of Arasbaran are exposed to damage caused by climate change. For its protection, management and continuous monitoring, it is necessary to obtain accurate, correct and timely environmental data and information, including climate data. Due to the insufficient number and inappropriate distribution of meteorological stations in the region, the use of (RS&GIS) data in the GEE platform to extract climatic parameters was put on the agenda. These data were prepared either in the form of existing products or by applying valid formulas on satellite images. Daily minimum, daily maximum and daily average temperatures, along with the temperature of the earth's surface every 16 days (resulting from Landsat 8) as well as daily precipitation, monthly cumulative precipitation and daily maximum wind speed, related to the first six months of the year 1400, are from both sources of information mentioned (GEE and the aforementioned meteorological station) were extracted and compared. Examining the relationship between these climate maps (produced in GEE) with the meteorological data recorded at the Jolfa meteorological station (for example), except for the maximum daily wind speed parameter, other parameters of daily cumulative precipitation, minimum, maximum and daily average temperature, showed a good correlation and the data can be trusted.

Estimation of land subsidence using DInSAR and SBAS techniques

Mojdeh Miraki — 2023-12-19

Land subsidence is one of the few environmental hazards that has received much less attention than other hazards due to low human casualties. However, subsidence over time causes irreparable damage to cities and adjacent areas and facilities, and infrastructure. In the present research, land subsidence in Isfahan province in Iran and specifically in the area of Mobarakeh Steel Company (MSC) using the traditional interferometric method by two images related to the years 2016 and 2021 and time series analysis using the SBAS method by 621 Interferometer and 178 epochs and 159 Sentinel satellite images were used in the ascending direction. The maximum subsidence rate was about -83 mm per year and -28 cm in 5 years for Isfahan City, after processing with time series and traditional interferometric method, respectively. The results of the two methods were close to each other, which can confirm the correctness of the estimated subsidence. Also, the obtained maps were matched with the subsidence maps of the National Cartographic Center of Iran, and it was found that the land subsidence areas are located in the two hotspots of Isfahan and Mahyar plains. Subsidence has expanded in a trend of Isfahan, Shahreza, and Mobarakeh, Iran.

Comprehensive temperature analysis of Türkiye between 2013 and 2023 using Google Earth Engine and ERA5 Dataset

Abdullah Sukkar — 2023-12-19

The climate system involves complicated interactions among diverse atmospheric and environmental elements, and it is essential to comprehend prolonged temperature trends for evaluating the consequences of climate change. In this study, an analysis of temperature changes in Türkiye over the period from 2013 to 2023 was realized. Employing advanced geospatial technology, specifically Google Earth Engine, and utilizing the ERA5 dataset, this study seeks to delve deeply into temperature trends throughout Türkiye. The incorporation of satellite imagery and detailed climate data with high resolution facilitates a detailed exploration of temporal and spatial fluctuations, enhancing a nuanced comprehension of climate dynamics. As climate change continues to exert its influence globally, a focused analysis of Türkiye's temperature trends becomes a necessity for informed decision-making in areas such as agriculture, water resource management, and urban planning. This study aimed to contribute valuable insights into the evolving climate change of Türkiye, considering the relationship between the changing environment and societal considerations. Results indicated a 0.20 Celsius degree increment over Türkiye during this ten-year period, while the Southeastern Anatolia Region faced the highest warming.

PM10 air pollutant prediction using deep learning LSTM Model: A case study of Istanbul, Türkiye

Omar Wisam Alqaysi — 2023-12-19

Accurate forecasting of PM10 concentrations is crucial for air quality management and public health protection. This study proposes a deep learning-based model for predicting PM10 concentrations in Istanbul, Türkiye, utilizing a combination of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models. Historical air pollution data from the Ministry of Environment, Urbanization, and Climate Change of Turkey and meteorological data from NASA for the period of January 2018 to August 2023 were employed for model development. Ümraniye district was selected as the study area due to its comprehensive air quality data availability. An extensive model development process involved identifying the optimal input sliding window, input features, and model architecture through parameter tuning. The LSTM+GRU model resulted in the best metrics, achieving an RMSE of 6.71, R2 of 0.86, and MAPE of 15.9%. The model demonstrated strong generalization capabilities when tested on data from eight different stations in Istanbul. While the proposed model exhibited promising performance, certain limitations warrant further investigation. The effectiveness of the model for air pollutants other than PM10 remains unexplored. Additionally, an evaluation of feature importance ranking for the input parameters is necessary to identify the most influential factors contributing to PM10 concentrations. Future research endeavors will address these limitations and refine the model for broader applicability.

Estimation of chlorophyll concentration on surface water bodies from hyperspectral satellite data

Martina Frezza — 2023-12-19

This research contributes to advancing the measurement and monitoring of crucial biogeophysical parameters, serving as both qualitative and quantitative indicators for the assessment of natural surface conditions. Leveraging hyperspectral satellite sensors, the primary objective is to enhance the management of natural resources. A key focus of this investigation is the concentration of chlorophyll, a pivotal indicator for assessing phytoplankton abundance and algal biomass in aquatic environments. Chlorophyll concentration emerges as a valuable metric for gauging water quality, understanding the biophysical state of water bodies, discerning trophic levels, and evaluating the eutrophication status of water. The imperative to estimate chlorophyll concentration through satellite-derived data stems from inherent limitations in in-situ measurements. Traditional field measurements conducted by pertinent Regional Environmental Protection Agency entities are labor-intensive, allowing for only a sparse sampling frequency, typically limited to a few measurements annually. Furthermore, these in-situ measurements offer data at specific points, potentially overlooking the spatial variability of chlorophyll concentration across water bodies. By leveraging hyperspectral satellite technology, this research aims to overcome these limitations, providing a more comprehensive and spatially distributed understanding of chlorophyll concentration. This holistic approach not only enhances the efficiency of resource management but also contributes to a more nuanced comprehension of the dynamic ecological processes within aquatic ecosystems.

Spatial analysis of the vulnerability of rural housing to earthquakes (case study: rural settlements in the Tehran metropolitan area)

Bahman Tahmasi — 2023-12-19

Natural disasters are one of the main factors in the destruction of human settlements and cause much damage to human societies. An earthquake is one of the most destructive natural disasters that can destroy settlements in just a few seconds. Iran is located in an earthquake-prone region where many earthquakes occur every year. Also, the Tehran metropolitan area is one of the most prone to earthquakes in Iran. This area has a high risk of earthquake due to the high population density, high residential density and the existence of many faults. Rural settlements located in the Tehran metropolitan area have a high potential for vulnerability to earthquakes due to their high population density, low-quality housing, and unique socio-economic conditions. This is the reason this paper analyzes the vulnerability of housing of rural settlements in the Tehran metropolitan area. The statistical population in this research was the rural settlements located in the TMA region. For data analysis, several spatial analysis methods, including IDW interpolation, hotspot analysis, and KMeans spatial clustering, have been used. The results of this study show that the rural settlements located in the central area of TMA have more resistant housing and less vulnerability, and the peripheral areas have more non-resistant housing and more vulnerability.

The effect of smart mobility performance in mitigation of climate change, the experiences of European cities

Parinaz Badamchizadeh — 2023-12-19

Smart and sustainable urban improvement is the current priority. Mobility is one of the most difficult topics to face within the urban regions. Great mobility for citizens and businesses incredibly increases the attractiveness and competitiveness of cities. The transport sector is one of the biggest contributors of CO2 emissions and other greenhouse gasses. In order to decreasing the global average temperature by CO2, critical and transformative activities in urban portability are required. As a sub-domain of the smart-city concept, smart-mobility-solutions integration at the municipal level is thought to have environmental, financial and social benefits, e.g., decreasing air pollution in cities, giving modern markets for alternative mobility and ensuring widespread get to to open transportation. Therefore, this article points to analyze the significance of smart mobility in creating a cleaner environment and provide strategic and practical illustrations of smart-mobility services in four European cities: Berlin (Germany), Kaunas (Lithuania), Riga (Latvia) and Tartu (Estonia). The paper presents a systematized writing review approximately the potential of smart-mobility services in reducing the negative natural affect to urban situations in different cities.

Evaluating land use plans in line with climate change adaptation policies in the Semnan Urban Region

Vahid Isazade — 2023-12-19

Climate change in developing countries is more exposed to the risks of climate change due to lack of adaptation capacity, economy dependent on climate-sensitive sectors, gaps in policies caused by central governments, weak institutions and lack of learning adaptation strategies. This article examines the relationship between land use systems as one of the intervention areas of multi-level climate governance and the policy of adapting to different governance methods in this area. This article also introduces the conceptual model of the compatibility of the land management system and the multi-level climate governance framework, from the documentary research method and the systematic review of texts in the form of documents, laws and programs prepared for urban and suburban development in Semnan urban complex in two decades. Examines the latter. The results showed that Regulating the development process of Semnan city based on climate, and environmental considerations, considering natural hazard management and climate change, improving the level of development sustainability through comprehensive ecological management based on a participatory approach, emphasizing desertification control, water conservation, and protection of Soil, air and vegetation, its optimal use, especially in the northern margin of Iran, The climate change fact is intensive among the Middle Eastern countries and especially Iran.

Preventive measures in disaster management can make the difference

Lucrezia Vittoria Natale — 2023-12-19

Coping with the consequences and losses caused by natural disasters is one of the most pressing issues that humanity is often facing. Addressing this challenge involves different strategies, from prevention and reaction plans to adaptation and mitigation projects. Preventive measures can be seen as the most effective way to prevent loss of life and damage to property. These encompass building codes, land use, and environmental conservation efforts, as well as less tangible activities linked to education and awareness. The paper shows some of the possible ways to create effective natural disaster management, with a set of ex-ante measures which are particularly focused on prevention methods. Highlighting their importance does not mean denigrating ex-post activities. Rather, an impactful approach should integrate these two typologies of measures and avoid an excessive reliance on insurance alone. Indeed, by investing in prevention, communities can substantially reduce their vulnerability and exposure. Examples drawn from experience with flooding events are also provided for a more concrete understanding.

Utilizing photogrammetry for forest rehabilitation assessment: Remote sensing techniques applied to Mt Rubavu in Rubavu District, Rwanda

Sabato Nzamwita — 2023-12-19

Forest rehabilitation has gained popularity in an era of unprecedented rapid urban growth for sustainable development. Monitoring forest restoration using geospatial technologies has recently attracted many researchers’ attention. In Rwanda, GIS and remote sensing have been proven to be useful tools in monitoring rehabilitated forest landscapes. The current work assumes to monitor the spatiotemporal change of the rehabilitated artificial forest of Mount Ruvubu near Rubavu city using advanced photogrammetric images and Geographic Information System (GIS) techniques across three distinct time periods: 2005, 2010, and 2015. The results revealed that forest encroachment increased from 23.5 hectares in 2005 to 23.9 in 2010, followed by a significant reversal of this trend in 2015. The NDVI imagery provides a visual representation of these changes, highlighting encroachment in the western and southwest parts of the forest in 2005 and 2010, and successful rehabilitation in the central and western regions in 2015. All in all, the study demonstrates the effectiveness of remote sensing and GIS in monitoring forest cover and rehabilitation efforts. These technologies are essential in sustainable forest management, offering valuable insights into areas that require immediate attention. GIS and remote sensing are crucial for protecting forest benefits for society and the environment.

Groundwater analysis and management plan using integrated community perception and geo-spatial techniques in Wana, South Waziristan

Saddam Hussain — 2023-12-19

Groundwater is one of the most valuable natural resources supporting human health and economic development. Globally, there has been an enormous stress on groundwater. In Pakistan, water shortage and decreasing groundwater level is one of the major issues. The groundwater assessment and management study has been conducted in Wana, South Waziristan using field survey and geospatial techniques. To achieve objectives, both primary and secondary data sources were used. The secondary data were acquired from concerned governmental departments. Primary data were collected through questionnaire survey, personal observations and Global Positioning System (GPS). Landsat ETM+ images were extracted to derive the land use land cover (LULC) of the area with four classes i.e., (Barren land, vegetation, built up and water bodies) through maximum likelihood (ML) technique. Soil map of the study area was digitized in Arc GIS 10.5. Inverse Distance Weighted (IDW) technique was applied to interpolate rainfall. Different parameters include rainfall analysis, land cover, soil group and geology were used to generate NRCS model. NRCS hydrological and watershed modeling were applied to calculate the estimation of surface runoff and stream network order. Forestation, check dams and embankments have been proposed in the management plan. The results show groundwater level in Wana has declined 13 feet in the last five years. There are multiple factors that led to water depletion. The groundwater level drops sharply in the areas where there are high population and where there is large agricultural land. The need of construction of large and small dams to maintain the cultivation of water intensive crops in Wana South Waziristan, which will be helpful in augmenting the groundwater level, stabilizing the climate and will also prevent the land from flooding. The results and findings of this study can assist researchers for future research and decision makers.

Mapping Covid-19 incidence hotspots in Pakistan using spatial-statistical approach

Shakeel Mahmood — 2023-12-19

COVID-19 pandemic is a top-level global emergency which has reduced the coping capacity several developed nations. The infected cases are growing very rapidly. The social interaction and travelling of people have further intensified the situation. Therefore, in this paper an attempt has been made to identify and assess COVID-19 hotspot in Pakistan and public health department to decelerate the exponential growth of patients. Point-level geo-coding technique is applied on patient’s record (25/03/2020 to 20/04/2020) and the relative location was converted into absolute location. A total 468 confirmed cases were geo-coded. Getis-OrdGi* statistical model is applied in ArcGIS10.2 to calculate Z-score and P-values for each location representing the COVID-19 incidence intensity. Then Inverse distance weighted (IDW) technique of spatial interpolation was applied on Z-score and spatial clusters of confirmed cases were geo-visualized in the form hotspot and cold spot. The spatial extent of hotspots and age group of infected persons is alarming. The study provides a suitable methodological framework for identification and analysis infectious disease hotspots. The results can also facilitate public health department and related authorities to win war against COVID-19 lethal outbreak. Similarly, it can help policy makers to restrict travelling and social interaction in hotspots.

Multi-sensorial data-based assessment of artificial surfaces and vegetation index for the response to population expansion: A case study of Musanze Secondary City, Rwanda

Katabarwa Murenzi Gilbert — 2023-12-19

Rapid population growth impacts land use, especially in Musanze, a secondary city. Therefore, our research aims for spatial analyses of the time series change in artificial surfaces and NDVI from 2000 to 2020. A multi-sensorial data-based analysis method assessed the changes and their effects on sustainability. Mathematical expression results reveal that (1) cultivated land increased from 64.6% to 68.9%, signifying a 4.3% rise. Conversely, forested areas decreased from 30.9% to 25.4%, reflecting a notable reduction of -5.5%. Water bodies saw a marginal uptick from 3.4% to 3.5%, a modest increase of 0.1%. Notably, artificial surfaces nearly doubled, soaring from 1.1% to 2.2%, representing an approximate 1.1% expansion in total coverage. (2) In 2000, sampled points demonstrated elevated vegetation indices, signifying that artificial areas were notably smaller than natural ones. Fast forward to 2020, after artificial surfaces had completely covered the sampled area, a significant and notable decrease in the vegetation index was observed, effectively halving the initial value recorded in 2000. In summary, urbanization can foster well-coordinated development; however, it poses a significant threat to natural areas as people migrate to urban centers. Therefore, to ensure a sustainable future for the population, we recommend enforcing zoning plans and building upward, using taller residential buildings instead of spreading out horizontally.

Flood vulnerability assessment using geographical information system: Case study of Mpazi Sub-catchment, Kigali

Patience Manizabayo — 2023-12-19

Floods in the Mpazi sub-catchment pose significant and recurring threats to the community and environment. This study utilized GIS technology to assess flood vulnerability by integrating spatial data on land use, elevation, and rainfall patterns. The results revealed a high susceptibility to flood hazards, particularly during the rainy season. This information is invaluable for stakeholders in formulating effective flood management strategies to mitigate the devastating impact of these recurrent floods on society and essential infrastructure. The study identifies the most vulnerable areas: very high risk 39.74% (353.34 ha), high risk 13.02% (115.73 ha), moderate risk 30.22% (268.62 ha), low risk 5.12% (45.51 ha), very low risk 11.9% (105.77 ha). Infrastructure, such as residential and commercial buildings, is impacted by flooding. This study offers valuable insights for decision-makers and stakeholders, supporting the development of effective flood management plans in the Mpazi sub-catchment.

Land surface temperature and urban heat island analysis using remote sensing and GIS: A case study in Mersin, Türkiye

Mehmet Özgür Çelik — 2023-12-19

Global urbanization is rapidly increasing. This situation shifts land use/land cover (Lu/Lc) quickly. It also puts pressure on the land. Mersin, the study area, is also experiencing an increase in urbanization pressure. It is critical to assess the effects of urbanization on land. The calculation of remote sensing (RS) and geographic information system (GIS)-based Land surface temperature (LST) and urban heat island (UHI) aids in detecting impacts. LST and UHI maps were constructed for this purpose, and the most recent changes in the study area were monitored.