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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
