Hyperspectral remote sensing of vegetation. Volume IV, Advanced applications in remote sensing of agricultural crops and natural vegetation Second Edition Huete
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Product details:
- ISBN-10 : 1138364762
- ISBN-13 : 9781138364769
- Author :
Table of contents:
Section I: Detecting Crop Management Practices, Plant Stress, and Disease
Chapter 1: Using Hyperspectral Data in Precision Farming Applications
Chapter 2: Hyperspectral Narrowbands and Their Indices in Study of Nitrogen Content of Cotton Crops
Chapter 3: Analysis of the Effects of Heavy Metals on Vegetation Hyperspectral Reflectance Properties
Section II: Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology)
Chapter 4: Mapping the Distribution and Abundance of Flowering Plants Using Hyperspectral Sensing
Chapter 5: Crop Water Productivity Estimation with Hyperspectral Remote Sensing
Chapter 6: Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems
Chapter 7: Hyperspectral Applications to Landscape Phenology
Section III: Land Cover, Forests, and Wetland and Urban Applications Using Hyperspectral Data
Chapter 8: The Use of Hyperspectral Earth Observation Data for Land Use/Cover Classification: Present Status, Challenges, and Future Outlook
Chapter 9: Hyperspectral Remote Sensing for Forest Management
Chapter 10: Characterization of Pastures Using Field and Imaging Spectrometers
Chapter 11: Hyperspectral Remote Sensing of Wetland Vegetation
Section IV: Thermal, SWIR, and Visible Remote Sensing
Chapter 12: Hyperspectral Remote Sensing of Fire: A Review
Section V: Hyperspectral Data in Global Change Studies
Chapter 13: Hyperspectral Data in Long-Term, Cross-Sensor Continuity Studies
Section VI: Hyperspectral Remote Sensing of Other Planets
Chapter 14: Hyperspectral Analysis of Rocky Surfaces on Earth and Other Planetary Bodies
Section VII: Conclusions
Chapter 15: Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume IV: Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation
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