Remote Sensing in Precision Agriculture Transforming Scientific Advancement into Innovation Earth Observation Series
Coordonnateurs : Lamine Salim, Srivastava Prashant K., Kayad Ahmed, Munoz Arriola Francisco, Pandey Prem Chandra
Section 2. PA Practices for soil management
Section 3. PA practices for irrigation water management
Section 4. PA practices for crop management
Section 5. Advanced modelling practices in PA
Section 6. Future Aspects and Challenges in RS for PA
Prashant K. Srivastava is working at IESD, Banaras Hindu University, as a faculty and was affiliated with Hydrological Sciences, NASA Goddard Space Flight Center, as
- 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
Date de parution : 10-2023
Ouvrage de 554 p.
19x23.4 cm
Thèmes de Remote Sensing in Precision Agriculture :
Mots-clés :
?; Active and passive remote sensing; Agriculture; Automated methods for soil mapping and monitoring; Biomass retrieval; Biotic factors; Carbon farming information; Chlorophyll; Climate; Climate change; Colombia; Common Agricultural Policy; Crop condition; Crop damage assessment; Crop management; Crop monitoring; Crop productivity; Crop yields; Decision-making; Digital soil mapping; Disease infestation; Drones; European Commission; FAO; Flavescence doree; Food and fiber; Food security; GEOCARBON; GIS; Geoinformation; Geospatial technology; Geostatistics; Grapevine yellows; Green Revolution; Greenhouse gas; Hyperspectral sensors; In situ data; Internet of things; IoT; IoT data; Irrigation; Kriging; Land suitability; Landsat 8; LiDAR imaging; Machine learning; Microwave SAR; Multispectral imaging; Nonparametric regression; Normalized difference vegetation index; Nutrient management; Optical sensors; Palm oil; Pests; Photosynthetic pigments; Phytosanitary; Plant health; Precision agriculture; Regionalized variable; Remote sensing; Resource use efficiency; Rice; Route planning; Salt-affected soils; Satellite imaging; Seed quality; Semivariogram; Sensor; Sensors; Sentinel-2; Sequestration; Site-specific management zones; Smart farming; Soil condition; Soil management; Soil organic carbon; Soil parameters; Spatial variability; Spectral imaging; Spectral reflectance; Spectroscopy; Sustainability; Thermal imaging; UAV; UAVs; Unmixing; Variability-rate applications; Water quality; WorldView-2; Yield; Yield estimation