Front Cover ; Land Surface Remote Sensing in Agriculture and Forest ; Copyright ; Contents; Foreword; Acronyms; Introduction; Chapter 1. Mapping of Primary Soil Properties Using Optical Visible and Near Infrared (Vis-NIR) Remote Sensing; 1.1. Introduction; 1.2. Spectral signatures of soils; 1.3. Estimation of soil properties from their spectral signatures; 1.4. Direct uses of estimation models; 1.5. Use of the Vis-NIR remote sensing products for digital soil mapping; 1.6. Perspectives; 1.7. Key points; 1.8. Bibliography.

Chapter 2. Estimation of Biophysical Variables from Satellite Observations2.1. Introduction; 2.2. Definition of the canopy biophysical variables accessible from remote sensing observations ; 2.3. Inversion methods of radiative transfer models; 2.4. Theoretical performances in estimating the different variables of interest ; 2.5. How to manage the under-determined and ill-posed nature of the inverse problem? ; 2.6. Combination of methods and sensors to improve estimates; 2.7. Conclusion; 2.8. Key points; 2.9. Bibliography; Chapter 3. Land Cover Mapping from Optical Images; 3.1. Introduction.

3.2. The input data3.3. Land cover map production approaches; 3.4. Use examples; 3.5. Key points; 3.6. Bibliography; Chapter 4. Contribution of Remote Sensing for Crop and Water Monitoring; 4.1. Introduction; 4.2. Indicators for crop monitoring; 4.3. Indicators of agricultural practices at the territory level; 4.4. Estimating water status and the water needs of crops using models; 4.5. Agricultural production quantification; 4.6. Some cases studies of environmental impacts of agriculture: spatial modeling of water, nitrogen and CO2 fluxes ; 4.7. Precision agriculture.

4.8. Results and prospects4.9. Key points; 4.10. Bibliography; Chapter 5. Contribution of Remote Sensing to Crop Monitoring in Tropical Zones; 5.1. Introduction: the case of tropical crops; 5.2. Crop mapping; 5.3. Yield prediction; 5.4. Harvest monitoring; 5.5. Conclusion and outlook; 5.6. Key points; 5.7. Bibliography; Chapter 6. Monitoring of Agricultural Landscapes Using Remote Sensing Data; 6.1. Introduction; 6.2. Identifying winter land cover within the framework of intensive agriculture ; 6.3. Phenology monitoring and crop characterization from a series of radar images; 6.4. Prospects.

6.5. Key points6.6. Bibliography; Chapter 7. Applications of Multispectral Optical Satellite Imaging in Forestry; 7.1. Introduction; 7.2. Specific key points of the forest cover; 7.3. Examples of application; 7.4. Prospects; 7.5. Key points; 7.6. Bibliography; Chapter 8. Characterization of Forests with LiDAR Technology; 8.1. Introduction; 8.2. The LiDAR technology; 8.3. LiDAR technology in forestry: platforms and applications; 8.4. Future of LiDAR technology in forestry?; 8.5. Key points; 8.6. Bibliography; Chapter 9. Forest Biomass From Radar Remote Sensing.

9.1. Forest biomass at the global scale.

Includes index.

Print version record.