Baghdadi, Nicolas. Zribi, Mehrez. text Electronic books. cau San Diego London Elsevier ISTE, Ltd. 2016 monographic eng

electronic resource

1 online resource (498 pages). 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. edited by Nicolas Baghdadi, Mehrez Zribi. 9.1. Forest biomass at the global scale. Includes index. Forests and forestry Remote sensing Agriculture Remote sensing GARDENING Fruit TECHNOLOGY & ENGINEERING Agriculture General Agriculture Remote sensing Forests and forestry Remote sensing SD387.R4 634.90285 Baghdadi, Nicolas. San Diego : Elsevier Science, �2016 9780081011836 0081011830 http://www.sciencedirect.com/science/book/9781785481031 http://www.sciencedirect.com/science/book/9781785481031 EBLCP 160924 20190328114816.0 ocn959149686 eng