Remote Sensing in Precision Agriculture

Transforming Scientific Advancement into Innovation

• Author(s): Salim Lamine, Prashant K. Srivastava, Ahmed Kayad, Francisco Munoz Arriola, Prem Chandra Pandey,
• Publisher: Elsevier
• Pages: 514
• ISBN_10: 0323914640
  ISBN_13: 9780323914642
  
• Language: en
• Categories: Technology & Engineering / Agriculture / Agronomy / Crop Science , Technology & Engineering / Agriculture / General , Business & Economics / Industries / Agribusiness , Technology & Engineering / Agriculture / Agronomy / General , Technology & Engineering / Agriculture / Agronomy / Soil Science , Computers / Business & Productivity Software / Business Intelligence , Technology & Engineering / Agriculture / Irrigation , Technology & Engineering / General , Science / Environmental Science , Technology & Engineering / Agriculture / Sustainable Agriculture , Computers / Information Technology , Technology & Engineering / Machinery , Computers / Business & Productivity Software / General , Computers / General ,

Description:... Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones’ geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information.

• Presents a well-integrated collection of chapters, with quality, consistency and continuity
• Provides the latest RS techniques in Precision Agriculture that are addressed by leading experts
• Includes detailed, yet geographically global case studies that can be easily understood, reproduced or implemented
• Covers geospatial data, with codes available through shared links