Land Surface Remote Sensing in Agriculture and Forest
Autor Nicolas Baghdadi, Mehrez Zribien Limba Engleză Hardback – 19 sep 2016
- Provides clear and concise descriptions of modern remote sensing methods
- Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications
- Provides chapters on physical principles, measurement, and data processing for each technique described
- Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made
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Specificații
ISBN-13: 9781785481031
ISBN-10: 1785481037
Pagini: 496
Dimensiuni: 152 x 229 x 35 mm
Greutate: 0.89 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 1785481037
Pagini: 496
Dimensiuni: 152 x 229 x 35 mm
Greutate: 0.89 kg
Editura: ELSEVIER SCIENCE
Public țintă
Research laboratories specializing in remote sensing or users of satellite products, Masters or Doctorate level students in the field of engineering, agriculture and geographyCuprins
1: Mapping of Primary Soil Properties Using Optical Visible and Near Infrared (Vis-NIR) Remote Sensing
2: Estimation of Biophysical Variables from Satellite Observations
3: Land Cover Mapping from Optical Images
4: Contribution of Remote Sensing for Crop and Water Monitoring
5: Contribution of Remote Sensing to Crop Monitoring in Tropical Zones
6: Monitoring of Agricultural Landscapes Using Remote Sensing Data
7: Applications of Multispectral Optical Satellite Imaging in Forestry
8: Characterization of Forests with LiDAR Technology
9: Forest Biomass From Radar Remote Sensing
2: Estimation of Biophysical Variables from Satellite Observations
3: Land Cover Mapping from Optical Images
4: Contribution of Remote Sensing for Crop and Water Monitoring
5: Contribution of Remote Sensing to Crop Monitoring in Tropical Zones
6: Monitoring of Agricultural Landscapes Using Remote Sensing Data
7: Applications of Multispectral Optical Satellite Imaging in Forestry
8: Characterization of Forests with LiDAR Technology
9: Forest Biomass From Radar Remote Sensing