A Review: Detection types and systems in remote sensing
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Abstract
Remote sensing (RS) is the process of capturing, measuring, and digitally storing the reflection, radiation, and scattering values emitted by an object in one or more different band ranges of the broad electromagnetic spectrum and using this data to identify tools. RS is a method used by many professional disciplines and is frequently preferred today. Therefore, it has been the subject of this study. This study aims to conduct in-depth literature research on RS and present the results of related studies. For this goal, studies in the literature were reviewed. In addition, studies connected to RS or types were scanned in the Vosviewer application, and maps were constructed based on the locations, years, and keywords of the studies done.
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References
Adjovu, G. E., Stephen, H., James, D., & Ahmad, S. (2023). Overview of the application of remote sensing in effective monitoring of water quality parameters. Remote Sensing, 15(7), 1938. https://doi.org/10.3390/rs15071938
Anand, A., & Deb, C. (2023). The potential of remote sensing and GIS in urban building energy modelling. Energy and Built Environment, 957-969. https://doi.org/10.1016/j.enbenv.2023.07.008
Çelik, M. Ö., & Yakar, M. (2023). Monitoring Land Use and Land Cover Change Using Remote Sensing and GIS: A Case Study in Mersin, Türkiye. Turkish Journal of Geographic Information Systems, 5(1), 43-51. https://doi.org/10.56130/tucbis.1300704
Çelik, M. Ö., Fidan, D., Ali, U. L. V. İ., & Yakar, M. (2024a). Evaluation of forest fires using remote sensing and geographic information systems: a case study of Mersin province, Silifke district. Anatolian Journal of Forest Research, 9(2), 116-125. https://doi.org/10.53516/ajfr.1302553
Çelik, M. Ö., Kuşak, L., & Yakar, M. (2024b). Assessment of groundwater potential zones utilizing geographic information system-based analytical hierarchy process, vlse kriterijumska optimizacija kompromisno resenje, and technique for order preference by similarity to ideal solution methods: A Case Study in Mersin, Türkiye. Sustainability, 16(5), 2202. https://doi.org/10.3390/su16052202
Cuca, B., Zaina, F., & Tapete, D. (2023). Monitoring of Damages to Cultural Heritage across Europe Using Remote Sensing and Earth Observation: Assessment of Scientific and Grey Literature. Remote Sensing, 15(15), 3748. https://doi.org/10.3390/rs15153748
Hu, D., & Minner, J. (2023). UAVs and 3D city modeling to aid urban planning and historic preservation: A systematic review. Remote Sensing, 15(23), 5507. https://doi.org/10.3390/rs15235507
Janga, B., Asamani, G. P., Sun, Z., & Cristea, N. (2023). A Review of practical ai for remote sensing in earth sciences. Remote Sensing, 15(16), 4112. https://doi.org/10.3390/rs15164112
Jia, J., & Ye, W. (2023). Deep Learning for Earthquake Disaster Assessment: Objects, data, models, stages, challenges, and opportunities. Remote Sensing, 15(16), 4098. https://doi.org/10.3390/rs15164098
Karthikeyan, L., Chawla, I., & Mishra, A. K. (2020). A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses. Journal of Hydrology, 586, 124905. https://doi.org/10.1016/j.jhydrol.2020.124905
Kavak, K. Ş. (1998). Uzaktan algılamanın temel kavramları ve jeolojideki uygulama alanları (in Turkish). Journal of Geological Engineering, 21(1), 63-74.
Kurbanov, E., Vorobev, O., Lezhnin, S., Sha, J., Wang, J., Li, X., Cole, J., Dergunov, D., & Wang, Y. (2022). Remote sensing of forest burnt area, burn severity, and post-fire recovery: A review. Remote Sensing, 14(19), 4714. https://doi.org/10.3390/rs14194714
Lan, H., Liu, X., Li, L., Li, Q., Tian, N., & Peng, J. (2022). Remote sensing precursors analysis for giant landslides. Remote Sensing, 14(17), 4399. https://doi.org/10.3390/rs14174399
Lillesand, T. M. & Kiefer, R. W. (2004). Remote sensing and image interpretation, John Wiley & Sons.
Louw, A. S., Fu, J., Raut, A., Zulhilmi, A., Yao, S., McAlinn, M., Fujikawa, A., Siddique, M. T., Wang, X., Yu, X., Mandvikar, K., & Avtar, R. (2022). The role of remote sensing during a global disaster: COVID-19 pandemic as case study. Remote Sensing Applications: Society and Environment, 27, 100789. https://doi.org/10.1016/j.rsase.2022.100789
Ma, J., Ma, R., Pan, Q., Liang, X., Wang, J., & Ni, X. (2023). A global review of progress in remote sensing and monitoring of marine pollution. Water, 15(19), 3491. https://doi.org/10.3390/w15193491
Neyns, R., & Canters, F. (2022). Mapping of urban vegetation with high-resolution remote sensing: A review. Remote sensing, 14(4), 1031. https://doi.org/10.3390/rs14041031
Olgun, A. (2012). Monitoring of coastline changes of the Goksu Delta by means of remote sensing and geographic information systems (Publication No. 315311) [Doctoral Thesis, İstanbul Technical University]. YÖK National Thesis Center.
Shafiq, M., Mahmood, S. (2022). Spatial assessment of forest cover change in Azad Kashmir, Pakistan. Advanced GIS, 2(2), 62-69.
Sutherland, N., Marsh, S., Priestnall, G., Bryan, P., & Mills, J. (2023). Infrared thermography and 3D-data fusion for architectural heritage: a scoping review. Remote Sensing, 15(9), 2422. https://doi.org/10.3390/rs15092422
Tanniru, S., & Ramsankaran, R. (2023). Passive microwave remote sensing of snow depth: Techniques, challenges and future directions. Remote Sensing, 15(4), 1052. https://doi.org/10.3390/rs15041052
Wang, Z., Shi, Y., & Zhang, Y. (2023). Review of desert mobility assessment and desertification monitoring based on remote sensing. Remote Sensing, 15(18), 4412. https://doi.org/10.3390/rs15184412
Xu, Q., Zhao, B., Dai, K., Dong, X., Li, W., Zhu, X., Yang, Y., Xiao, X., Wang, S., Huiyan,
J., Deng, B., & Ge, D. (2023). Remote sensing for landslide investigations: A progress report from China. Engineering Geology, https://doi.org/10.1016/j.enggeo.2023.107156
Yu, D., & Fang, C. (2023). Urban remote sensing with spatial big data: A review and renewed perspective of urban studies in recent decades. Remote Sensing, 15(5), 1307. https://doi.org/10.3390/rs15051307
Zheng, Q., Seto, K. C., Zhou, Y., You, S., & Weng, Q. (2023). Nighttime light remote sensing for urban applications: Progress, challenges, and prospects. ISPRS Journal of Photogrammetry and Remote Sensing, 202, 125-141. https://doi.org/10.1016/j.isprsjprs.2023.05.028
Zhou, X., Wang, J., Zheng, F., Wang, H., & Yang, H. (2023). An Overview of Coastline Extraction from Remote Sensing Data. Remote Sensing, 15(19), 4865. https://doi.org/10.3390/rs15194865