Description
Agricultural Applications of Earth Observation details the revolutionary impact of satellite and remote sensing technologies in enhancing agricultural practices. It bridges the knowledge gap by making advanced satellite and sensor data understandable and applicable, enabling readers to select the best tools for specific agricultural needs. Real-world case studies and practical examples demonstrate the successful implementation of Earth Observation technologies in agriculture, inspiring readers with tangible results and encouraging innovative thinking. Agricultural Applications of Earth Observation enables readers to apply Earth Observation technologies to enhance agronomical sustainability and contribute to more environmentally friendly practices. With detailed methodologies and a range of additional supplementary elements, the book equips readers with the knowledge and tools to drive the future of agriculture into a more sustainable era.- Extensive coverage of various remote sensing technologies equips readers with the knowledge to select the best tools for specific agricultural needs, maximizing their effectiveness- Real-world case studies and practical examples demonstrate the successful implementation of Earth Observation technologies in agriculture, inspiring readers with tangible results and encouraging innovative thinking- Emphasis on sustainable practices, aided by Earth Observation, empowers readers to adopt environmentally friendly strategies in areas such as cover cropping, minimal tillage, and efficient water management
Table of Contents
1. Introduction to Earth Observation in Agriculture2. Retrieval of key agricultural variables using radiative transfer modeling3. Retrievals of parameters characterising land surface interactions from the synergy of EO data with simulation process models4. Monitoring evapotranspiration in agricultural fields5. Monitoring crop phenology with remote sensing6. Mapping cropland extent with Landsat image using machine learning7. Satellite imagery-based mapping of crop yield8. Learning feature representations with recurrent neural networks for the Earth Sciences9. Drought Monitoring based on Remote Sensing and Multiple Data Fusion10. Carbon sequestration potential in abandoned cropland11. Remote sensing of soil moisture in agroecosystems
