Agricultural Applications of Earth Observation

Peng Fu

• Publisher: Elsevier
• Year: 2026
• Topic: Technology & Engineering
• eBook ISBN:
  9780443383465
• Subtopic: Agriculture
• Index: Technology & Engineering

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

• Title of Book
• Chapter 1 Earth Observation in agriculture: an introduction
• Chapter 2 Quantifying agricultural biophysical variables from remote sensing: methods, models, and applications
• Chapter 3 Exploring the potential of Sim2DSphere model in predicting the spatiotemporal variability of shortwave incoming radiation flux and air temperature across varied ecosystem conditions
• Chapter 4 Monitoring evapotranspiration in agricultural fields with LST-based models
• Chapter 5 Monitoring crop phenology with remote sensing
• Chapter 6 Agricultural land mapping with satellite imagery using machine learning
• Chapter 7 Satellite-based mapping of crop yield
• Chapter 8 Learning feature representations with recurrent neural networks for the Earth Sciences
• Chapter 9 Drought monitoring based on remote sensing and multiple data fusion
• Chapter 10 Carbon sequestration potential in abandoned croplands
• Chapter 11 Remote sensing of soil moisture in agroecosystems
• Index