Until recently this area of research was an exclusive prerogative of a limited group of remote sensing and geospatial experts. However, the latest computer achievements made the benefits and technology of satellite inquiry manageable by policy- and decision makers.
This project aims to contribute to food security assessment initiatives by investigating application of satellite technologies in agricultural management and monitoring in Eastern Europe. The project run a pilot case study on monitoring cropland condition in Moscow region using satellite data. Several parameters defining crop health and supporting crop monitoring were assessed (overgrown areas detection, wet and chlorophyll content assessment). Analysis of the obtained data allowed identifying crop parcels requiring farmers’ attention and intervention to secure greater crop productivity and greater food security.
A series of maps based on Sentinel-2, Landsat-8 and RapidEye data analysis were produced identifying problematic areas of cropland requiring attention and intervention by farm management to increase crop yields and food security. As another project outcome, a spatial model for automatic satellite data processing were developed. The model could be used for various crops, and correspondingly, food security assessment at other sites within the region and worldwide. The developed algorithm could be easily replicated at any other farming site in other regions at limited or no costs.
During the project several spatial models for data analysis were created. The final spatial model allows to depict crop parcels with the plant growth disturbance identification was developed. That process consists of chlorophyll content in plants’ leaves estimation through MCARI index calculation and thematic classification, water content assessment calculating NDWI index and classification and then combination of two thematic images using intersection operator. As a result the map depicting problematic crop areas were developed.
The results obtained through the spatial model executing can minimize the risk of crop failure and reduce the cost of negative consequences elimination. The identification of problematic areas of cropland requiring attention and intervention of farm management at early stages can increase crop yields and ensure sustainable agriculture. All mentioned examples of remote sensing data analysis showed the high potential of contemporary GIS and satellite techniques to contribute to maintaining sustainable agriculture and ensure food security.
The project laid the foundation for future CEU research activities in food security assessment and using satellite technologies in achieving SDGs for researchers not specializing in remote sensing and geospatial technologies. Developed materials were used for enriching CEU curricula and show feasibility of such research for CEU core expertise areas. Using the obtained results, tutorials on application of geospatial technologies in relevant areas were compiled to stimulate interest within CEU community and to enrich CEU curricula in environmental sciences and public policy.