Remote Sensing Of Vegetation

Author: Hamlyn G Jones
Publisher: Oxford University Press
ISBN: 9780199207794
Size: 16.17 MB
Format: PDF
View: 50

An accessible yet rigorous introduction to remote sensing and its application to the study of vegetation for advanced undergraduate and graduate students. The underlying physical and mathematical principles of the techniques disucussed are explained in a way readily understood by those without a strong mathematical background.

Hyperspectral Remote Sensing Of Vegetation

Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 9781439845387
Size: 17.52 MB
Format: PDF, ePub, Mobi
View: 64

Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research. Hyperspectral Remote Sensing of Vegetation integrates this knowledge, guiding readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Taking a practical approach to a complex subject, the book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment. This comprehensive book brings together the best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, vegetation classification, biophysical and biochemical modeling, crop productivity and water productivity mapping, and modeling. It provides the pertinent facts, synthesizing findings so that readers can get the correct picture on issues such as the best wavebands for their practical applications, methods of analysis using whole spectra, hyperspectral vegetation indices targeted to study specific biophysical and biochemical quantities, and methods for detecting parameters such as crop moisture variability, chlorophyll content, and stress levels. A collective "knowledge bank," it guides professionals to adopt the best practices for their own work.

Advances In Environmental Remote Sensing

Author: Qihao Weng
Publisher: CRC Press
ISBN: 1420091816
Size: 17.80 MB
Format: PDF, Docs
View: 79

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.