Agricultural Monitoring and Yield Assessment Through Remote Sensing and GIS

Dear Colleagues,

Agricultural monitoring and yield assessment through remote sensing and GIS provide the basis for digital farming. Modern remote sensing provides information about the condition of crops and soil via analysis of satellite, aerial, drone and ground sensor data. Vegetation indices such as NDVI can be used to estimate crop condition, development stage, and indications of plant stress caused by drought, disease or nutrient deficiencies. Geographic information systems (GIS) enable the integration and analysis of remote sensing data with other spatial information, such as soil, meteorological and agronomical data. Today, Remote sensing and GIS provide essential tools for agricultural decision-making. Thanks to these technologies, we can accurately monitor crop health and condition and forecast yields, increasing farm efficiency.

This Special Issue seeks to spotlight the latest scientific research on the use of remote sensing to monitor agricultural space at various scales—from individual fields to large-scale regions and even at the national level. Therefore, we assume the possibility of using remote sensing with various spatial and temporal resolutions in the presented research. The results should focus on a detailed description of the used/developed models (deterministic, stochastic, or AI) and the possibilities of their broader implementation in the process of monitoring vegetation and estimating yields.

We look forward to receiving a variety of works, such as original research papers and reviews.

Dr. Anna Jedrejek
Dr. Rafał Pudełko
Guest Editors

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