Application of Remote Sensing Data in Crop Monitoring and Crop Yield Prediction

Dear Colleagues,

Remote sensing data are increasingly being introduced into the practice of agricultural production. Research in this field of knowledge is aimed at developing new methods and technologies for rapid, low-cost, and accurate monitoring of crop condition and crop yield forecasting. However, the proposed approaches are mostly local in nature. Attempts to transfer them to other areas do not lead to success. For further advancement in this scientific direction, new ideas and algorithms aimed at achieving a full understanding of the mechanisms of crop and plant imaging on remote sensing data of various types are needed.

We invite original and review articles on the latest progress in elaborating new methods and algorithms for crop monitoring and crop yield prediction using satellite and UAV data, in understanding mechanisms of the forming of crop spectral reflection properties. This would help researchers to devise strategies for the application of satellite and UAV data for operative crop monitoring. It would have further importance for receiving precise and operative information from decision makers on crop status, and crop yield contributing to future food security.

Topics appropriate for this Special Issue include but are not limited to the following:

• Application of satellite data for annual and perennial crop monitoring;
• Application of UAV data for annual and perennial crop monitoring;
• Spectral reflectance of crop canopy and plants;
• Crop yield prediction, and forecasting using remote sensing data;
• Crop recognition based on remote sensing data;
• Crop acreage assessment using remote sensing data;
• Crop stress detection based on remote sensing data;
• Risk of crop loss due to unfavorable conditions (drought, frost, insects’ invasions, and so on) modeling using remote sensing data;
• Crop weedness detection based on remote sensing data.

Prof. Dr. Igor Savin
Guest Editor

Manuscript Submission Information

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• crop monitoring
• remote sensing
• crop yield prediction
• crop phenology
• crop acreage assessment
• vegetation indexes
• spectral reflectance of crop canopy