Land Surface Remote Sensing in Agriculture and Forest
- 1st Edition - September 15, 2016
- Imprint: ISTE Press - Elsevier
- Authors: Nicolas Baghdadi, Mehrez Zribi
- Language: English
- Hardback ISBN:9 7 8 - 1 - 7 8 5 4 8 - 1 0 3 - 1
- eBook ISBN:9 7 8 - 0 - 0 8 - 1 0 1 1 8 3 - 6
The environmental and economic importance of monitoring forests and agricultural resources has allowed remote sensing to be increasingly in the development of products and se… Read more
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The environmental and economic importance of monitoring forests and agricultural resources has allowed remote sensing to be increasingly in the development of products and services responding to user needs.
This volume presents the main applications in remote sensing for agriculture and forestry, including the primary soil properties, the estimation of the vegetation’s biophysical variables, methods for mapping land cover, the contribution of remote sensing for crop and water monitoring, and the estimation of the forest cover properties (cover dynamic, height, biomass).
This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD), engineers and scientists, specialists in remote sensing applied to agriculture and forestry.
Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of radar imaging techniques.
- 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
Research laboratories specializing in remote sensing or users of satellite products, Masters or Doctorate level students in the field of engineering, agriculture and geography
- Foreword
- Acronyms
- Introduction
- 1: Mapping of Primary Soil Properties Using Optical Visible and Near Infrared (Vis-NIR) Remote Sensing
- Abstract
- 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
- 2: Estimation of Biophysical Variables from Satellite Observations
- Abstract
- 2.1 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
- 3: Land Cover Mapping from Optical Images
- Abstract
- 3.1 Introduction
- 3.2 The input data
- 3.3 Land cover map production approaches
- 3.4 Use examples
- 3.5 Key points
- 4: Contribution of Remote Sensing for Crop and Water Monitoring
- Abstract
- 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 prospects
- 4.9 Key points
- 5: Contribution of Remote Sensing to Crop Monitoring in Tropical Zones
- Abstract
- 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
- 6: Monitoring of Agricultural Landscapes Using Remote Sensing Data
- Abstract
- 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 points
- 7: Applications of Multispectral Optical Satellite Imaging in Forestry
- Abstract
- 7.1 Introduction
- 7.2 Specific key points of the forest cover
- 7.3 Examples of application
- 7.4 Prospects
- 7.5 Key points
- 8: Characterization of Forests with LiDAR Technology
- Abstract
- 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
- 9: Forest Biomass From Radar Remote Sensing
- Abstract
- 9.1 Forest biomass at the global scale
- 9.2 Quantifying forest biomass with radar remote sensing: physics and measurement techniques
- 9.3 Biomass from SAR L-band
- 9.4 The BIOMASS mission: forest biomass with P-band SAR
- 9.5 Summary and prospects
- 9.6 Key points
- Glossary
- List of Authors
- Index
- Scientific Committee
- Edition: 1
- Published: September 15, 2016
- Imprint: ISTE Press - Elsevier
- Language: English
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Nicolas Baghdadi
Nicolas Baghdadi is Research Director at IRSTEA in France. He is currently the scientific director of the French Land Data Centre (Theia).
Affiliations and expertise
IRSTEA, FranceMZ
Mehrez Zribi
Mehrez Zribi is Director of Research at CNRS/France. He received Ph.D. degree in 1998 from the University of Toulouse, France. Since October 2008, he has been with the Centre d’Etudes Spatiales de la Biosphère, Toulouse. His research interests include land surface characterization for hydrology applications, remote sensing signal processing, and airborne microwave instrumentation. Mehrez Zribi has published 125 papers in peer-reviewed journals and has coordinated publication of 20 books about remote sensing for land surfaces. He serves as an editorial board member for several journals and coordinate several international and french research projects. He is deputy director of CESBIO laboratory.
Affiliations and expertise
Director of Research, National Centre for Scientific Research (CNRS), FranceRead Land Surface Remote Sensing in Agriculture and Forest on ScienceDirect