Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications
CRC Press, Feb 16, 2011 - Technology & Engineering - 610 pages
Generating a satisfactory classification image from remote sensing data is not a straightforward task. Many factors contribute to this difficulty including the characteristics of a study area, availability of suitable remote sensing data, ancillary and ground reference data, proper use of variables and classification algorithms, and the analyst’s experience. An authoritative text, Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications compiles comprehensive review articles to examine the developments in concepts, methods, techniques, and applications as well as focused articles and case studies on the latest on a particular topic.
Divided into four sections, the first deals with various sensors, systems, or sensing operations using different regions of wavelengths. Drawing on the data and lessons learned from the U.S. Landsat remote sensing programs, it reviews key concepts, methods, and practical uses of particular sensors/sensing systems. Section II presents new developments in algorithms and techniques, specifically in image preprocessing, thematic information extraction, and digital change detection. It gives correction algorithms for hyperspectral, thermal, and multispectral sensors, discusses the combined method for performing topographic and atmospheric corrections, and provides examples of correcting non-standard atmospheric conditions, including haze, cirrus, and cloud shadow.
Section III focuses on remote sensing of vegetation and related features of the Earth’s surface. It reviews advancements in the remote sensing of ecosystem structure, process, and function, and notes important trade-offs and compromises in characterizing ecosystems from space related to spatial, spectral, and temporal resolutions of the imaging sensors. It discusses the mismatch between leaf-level and species-level ecological variables and satellite spatial resolutions and the resulting difficulties in validating satellite-derived products.
Finally, Section IV examines developments in the remote sensing of air, water, and other terrestrial features, reviews MODIS algorithms for aerosol retrieval at both global and local scales, and demonstrates the retrieval of aerosol optical thickness (AOT). This section rounds out coverage with a look at remote sensing approaches to measure the urban environment and examines the most important concepts and recent research.
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Chapter 2 Review of Selected ModerateResolution Imaging Spectroradiometer Algorithms Data Products and Applications
Chapter 3 Lidar Remote Sensing
Chapter 4 Impulse Synthetic Aperture Radar
Chapter 5 Hyperspectral Remote Sensing of Vegetation Bioparameters
Theoretical Backgrounds and Case Studies
Section II Algorithms and Techniques
Chapter 7 Atmospheric Correction Methods for Optical Remote Sensing Imagery of Land
Chapter 12 Remote Sensing of Ecosystem Structure and Function
Chapter 13 Remote Sensing of Live Fuel Moisture
Chapter 14 Forest Change Analysis Using TimeSeries Landsat Observations
Chapter 15 SatelliteBased Modeling of Gross Primary Production of Terrestrial Ecosystems
Chapter 16 Global Croplands and Their Water Use from Remote Sensing and Nonremote Sensing Perspectives
Air Water and Land
A Review of Aerosol Retrieval Using the ModerateResolution Imaging Spectroradiometer
Chapter 18 Remote Estimation of Chlorophylla Concentration in Inland Estuarine and Coastal Waters
Chapter 8 ThreeDimensional Geometric Correction of Earth Observation Satellite Data
Chapter 9 Remote Sensing Image Classification
Chapter 10 ObjectBased Image Analysis for Vegetation Mapping and Monitoring
Chapter 11 LandUse and LandCover Change Detection
Section III Environmental ApplicationsVegetation
Chapter 19 Retrievals of Turbulent Heat Fluxes and Surface Soil Water Content by Remote Sensing
Chapter 20 Remote Sensing of Urban Biophysical Environments
Chapter 21 Development of the USGS National LandCover Database over Two Decades