Advanced Remote Sensing

Advanced Remote Sensing

Terrestrial Information Extraction and Applications

1st Edition - August 17, 2012

Write a review

  • Editors: Shunlin Liang, Xiaowen Li, Jindi Wang
  • Hardcover ISBN: 9780123859549
  • eBook ISBN: 9780123859556

Purchase options

Purchase options
Available
DRM-free (EPub, PDF, Mobi)
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book’s content intuitive, clearly presented, and practical in its implementation.

Key Features

  • Comprehensive overview of various practical methods and algorithms
  • Detailed description of the principles and procedures of the state-of-the-art algorithms
  • Real-world case studies open several chapters
  • More than 500 full-color figures and tables
  • Edited by top remote sensing experts with contributions from authors across the geosciences

Readership

Geographers, geologists, oceanographers, atmospheric scientists, environmental scientists, and ecologists

Table of Contents

  • Foreword

    Preface

    Acknowledgments

    List of Contributors

    Chapter 1. A Systematic View of Remote Sensing

    1.1 Introduction

    1.2 Platform and Sensor System

    1.3 Data Transmission and Ground Receiving System

    1.4 Data Processing System

    1.5 Mapping Category Variables

    1.6 Estimating Quantitative Variables

    1.7 Production, Archiving, and Distribution of High-level Products

    1.8 Product Validation

    1.9 Remote Sensing Applications

    1.10 Concluding Remarks

    References

    Chapter 2. Geometric Processing and Positioning Techniques

    2.1 Overview

    2.2 Geometric Calibration of Satellite Remote-Sensing Imagery

    2.3 Geometric Rectification of a Single Remote-Sensing Image

    2.4 Geometric Registration of Satellite Remote-Sensing Imagery

    2.5 Construction of a Digital Terrain Model

    2.6 Orthoimage Production

    2.7 Summary

    References

    Chapter 3. Compositing, Smoothing, and Gap-Filling Techniques

    3.1 Multitemporal Compositing Techniques

    3.2 Time-series Data Smoothing and Gap-filling

    3.3 Summary

    References

    Chapter 4. Data Fusion

    4.1 An Overview of Remote-Sensing Data Fusion

    4.2 Methods for Pixel-level Remote-Sensing Data Fusion

    4.3 Generalized Model for Pixel-level Remote-Sensing Data Fusion

    4.4 Heterogeneous Data Source Fusion Technique

    4.5 Summary

    References

    Chapter 5. Atmospheric Correction of Optical Imagery

    5.1 Atmospheric Effects

    5.2 Correcting the Aerosol Impact

    5.3 Correcting the Impact of Water Vapor

    5.4 Correcting the Impacts of Other Constituents

    5.5 Commonly Used Models and Software

    5.6 Conclusions

    References

    Chapter 6. Solar Radiation

    6.1 Basic Concepts

    6.2 Observation Network of Land-Surface Radiation

    6.3 Surface Radiation Estimation Based on Satellite Remote Sensing and Global Circulation Model (GCM)

    6.4 Summary and Discussions

    Nomenclature

    References

    Chapter 7. Broadband Albedo

    7.1 Land-Surface Bi-Directional Reflectance Modeling

    7.2 The Albedo Estimation Method Based on Bi-directional Reflectance Model Inversion

    7.3 The Direct Estimation of Surface Albedo

    7.4 Joint Optimization of Surface-Atmospheric Parameters

    7.5 Global Land-Surface Albedo Products

    7.6 Temporal and Spatial Analysis of the Global Land Surface Albedo

    7.7 Problems and Prospects

    References

    Chapter 8. Land-Surface Temperature and Thermal Infrared Emissivity

    8.1 The Definitions of LST and LSE

    8.2 The Estimation of Average LST

    8.3 LSE Estimation Methods

    8.4 LSE and LST Products

    8.5 Summary

    Acronyms

    References

    Chapter 9. Surface Longwave Radiation Budget

    9.1 Surface Downward Longwave Radiation

    9.2 Surface Upwelling Longwave Radiation

    9.3 Surface Net Longwave Radiation

    9.4 Ground Validation Networks and Existing Satellite-Derived Surface Longwave Radiation Budget Products

    9.5 Summary

    References

    Chapter 10. Canopy Biochemical Characteristics

    10.1 Overview of Principles and Methods

    10.2 Empirical and Semi-empirical Methods

    10.3 Extraction Using Physical Models

    10.4 Conclusions and Discussions

    References

    Chapter 11. Leaf Area Index

    11.1 Definitions

    11.2 Statistical Methods

    11.3 Canopy Model Inversion Methods

    11.4 Data Assimilation Methods

    11.5 Global and Regional LAI Products

    11.6 LAI Climatology

    11.7 Summary

    References

    Chapter 12. Fraction of Absorbed Photosynthetically Active Radiation by Green Vegetation

    12.1 Definitions

    12.2 FAPAR Field Measurements

    12.3 Monte Carlo (MC) simulation

    12.4 Empirical Retrieval Methods

    12.5 Popular Remote-Sensing FAPAR Products

    12.6 FAPAR Retrieval Method Based on the Hybrid Vegetation Spectral Model

    12.7 Case Study

    12.8 Summary

    References

    Chapter 13. Fractional Vegetation Cover

    13.1 Introduction

    13.2 Field Measurements of FVC

    13.3 The Remote-Sensing Retrieval

    13.4 Current Remote-Sensing Products

    13.5 Challenges and Prospects for FVC Estimation

    References

    Chapter 14. Vegetation Height and Vertical Structure

    14.1 Field Measurement of Vegetation Height and Vertical Structure

    14.2 Small-Footprint Lidar Data

    14.3 Large-Footprint Lidar Data

    14.4 Vegetation Canopy Height and Vertical Structure from SAR Data

    14.5 Future Perspectives

    References

    Chapter 15. Above-ground Biomass

    15.1 Introduction

    15.2 Allocation Methods

    15.3 Optical Remote-sensing Methods

    15.4 Active Remote-Sensing Methods

    15.5 Methods for Biomass Estimation from Multisource Data

    15.6 Future Perspective

    References

    Chapter 16. Vegetation Production in Terrestrial Ecosystems

    16.1 Concept of Vegetation Production

    16.2 Ground Observation of Vegetation Production

    16.3 Statistical Models Based on the Vegetation Index

    16.4 Light-Use Efficiency Model Based on Remote-Sensing data

    16.5 Dynamic Global Vegetation Models (DGVMs)

    16.6 Temporal and Spatial Distribution Pattern of Global Vegetation Productivity

    16.7 Summary

    References

    Chapter 17. Precipitation

    17.1 Surface Measurement Techniques

    17.2 Estimation from Satellite Data

    17.3 Global and Regional Datasets

    17.4 Global Precipitation Climatology

    17.5 Future Perspectives

    References

    Chapter 18. Terrestrial Evapotranspiration

    18.1 Introduction

    18.2 Basic Theories of λE

    18.3 Satellite λE Algorithms

    18.4 Observations for Algorithm Calibration and Validation

    18.5 Conclusions and Discussion

    Acknowledgements

    References

    Chapter 19. Soil Moisture Content

    19.1 Introduction

    19.2 Conventional SMC Measurement Techniques

    19.3 Microwave Remote-Sensing Methods

    19.4 Optical and Thermal-IR Remote-Sensing Methods

    19.5 Estimation of Soil Moisture Profile

    19.6 Comparison of Different Remote-Sensing Techniques

    19.7 Available Datasets and Spatial and Temporal Variations

    19.8 Conclusions

    References

    Chapter 20. Snow Water Equivalence

    20.1 Passive Microwave Remote-Sensing Techniques

    20.2 Active Microwave Remote-Sensing Techniques

    20.3 Visible Band Remote-Sensing Techniques

    20.4 Summary

    References

    Chapter 21. Water Storage

    21.1 Water-Balance-Based Estimation

    21.2 Surface-Parameter-based Estimation

    21.3 GRACE-based Estimation

    21.4 Discussion and Future Prospects

    References

    Chapter 22. High-level Land Product Integration Methods

    22.1 Introduction

    22.2 Geostatistical Methods

    22.3 Multiresolution Tree

    22.4 Empirical Orthogonal Function (EOF)-based Methods

    22.5 Summary

    References

    Chapter 23. Production and Data Management Systems

    23.1 Overview of the Production and Database Management

    23.2 System Hardware

    23.3 Production System

    23.4 Data Management System

    23.5 Summary

    References

    Chapter 24. Land Cover and Land use Changes

    24.1 Introduction

    24.2 Urbanization

    24.3 Intensive Agriculture

    24.4 Forest Cover Changes

    24.5 Conclusions

    References

    Index

Product details

  • No. of pages: 800
  • Language: English
  • Copyright: © Academic Press 2012
  • Published: August 17, 2012
  • Imprint: Academic Press
  • Hardcover ISBN: 9780123859549
  • eBook ISBN: 9780123859556

About the Editors

Shunlin Liang

Dr. Liang received his Ph.D. degree in 1993 from Boston University, USA. He is a Professor with the Department of Geographical Sciences, University of Maryland, College Park, USA. He has published over 420 SCI indexed peer-reviewed journal papers, 42 book chapters, and nine special issues of different journals. He authored/edited seven books and four of which were translated in Chinese, such as “Quantitative Remote Sensing of Land Surfaces” (Wiley, 2004), “Advances in Land Remote Sensing: System, Modeling, Inversion and Application” (Springer, 2008), “Advanced Remote Sensing: Terrestrial Information Extraction and Applications” (Academic Press, 2012, 2019), “Global LAnd Surface Satellite (GLASS) Products: Algorithms, Validation and Analysis”(Springer, 2013), “Land Surface Observation, Modeling, Data Assimilation” (World Scientific, 2013), and “Earth’s Energy Budget” (Elsevier, 2017). He is an IEEE Fellow and an Editor-in-Chief of Science of Remote Sensing.

Affiliations and Expertise

Department of Geography, University of Maryland, College Park, MD, USA

Xiaowen Li

Affiliations and Expertise

College of Geography, Beijing Normal University, Beijing, China

Jindi Wang

Prof. Wang graduated from Beijing University of Postal and Telecommunications, and received the B.S degree in Electronic Engineering in 1982. She is currently professor of the Research Center for Remote Sensing and GIS of Beijing Normal University. Prof. Wang hosted a number of research projects on remote sensing modeling and validation, land surface parameters retrieval, typical land object’s spectrum database establishment, dynamic feature analysis and modeling of remote sensing information, supported by the National Basic Research Program of China, the National High Technology Research and Development Program of China, the National Natural Science Foundation of China.

Affiliations and Expertise

Professor, College of Geography, Beijing Normal University, Beijing, China

Ratings and Reviews

Write a review

There are currently no reviews for "Advanced Remote Sensing"