The assessment and management of soil fertility using GIS and remote sensing

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Matanat Asgarova


Geoinformation technologies are deeply rooted in all spheres of human activity, including agriculture. The efficiency rate of agricultural areas can be remarkably increased by utilizing efficient agricultural production technology such as remote sensing and Geographic Information Systems (GIS).  Analyzing soil data through GIS helps in agricultural planning and facilitates quick and appropriate decisions on soil fertility and land use management. GIS technologies make it possible to manage soil fertility and crop quality to the level of farms and even private subsidiary farms.  Soil fertility assessment, field monitoring, yield forecasting, proper farming, soil fertility management include not only soil data collection and analysis, but also spatial information collection. With the help of global positioning systems (GPS), it is possible to accurately determine the location on the ground of each plot, as well as to follow the development of crops from sowing to harvesting, to detect moisture and nutrient deficiencies in time, and to identify plant diseases. A well-known example is the vegetation indices Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) which could be provided by the EOS Crop Monitoring Company to assess much information on soil fertility in agricultural areas. Vegetation indices provide data on crop growth and health and can be used to monitor crop development from sowing to harvesting, timely detection of moisture and nutrient deficiencies, and detection of plant diseases. Within agricultural fields, GIS technologies are effectively used to apply fertilizers to the soil at certain rates according to the condition of the site, as well as for the correct organization of irrigation. The study area is located in the Imishli district of the Central Aran economic region of the Republic of Azerbaijan, which is regarded as an important agriculture site in the region recognizing cotton and grain growing spots. Accordingly, a few well-known indices such as normalized difference vegetation index - NDVI, and normalized difference red edge – NDRE, were step-wisely applied in the assessment of soil fertility in the region by processing EOSDA LandViewer-derived high-resolution imagery inside the ArcGIS functionality. These indices could be used in agricultural planning, particularly soil fertilizers with some standards by the condition of the site, as well as for the proper organization of irrigation.

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Asgarova, M. (2023). The assessment and management of soil fertility using GIS and remote sensing. Advanced Land Management, 3(2), 97–106. Retrieved from


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