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Remotely Sensed Data Characterization, Classification, and Accuracies

A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the;

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Classification Methods for Remotely Sensed Data

developments, Classification Methods for Remotely Sensed Data, Second Edition provides a comprehensive and up-to-date review of the entire field;

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Landcover Classification and Topography

Landcover mapping is an important tool for natural resource managers. The incorporation of remotely sensed data to produce landcover maps;

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Real-Time Auto Geotagging and Visualization of Remotely Sensed Data

development of a prototype system RTAG. The system is used to remotely sense data, embed the geographical location in the data and visualize the;

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Advanced Environmental Monitoring with Remote Sensing Time Series Data and R

remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from;

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Advanced Environmental Monitoring with Remote Sensing Time Series Data and R

remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from;

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Uncertainty Management in Remote Sensing of Climate Data

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a;

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Quantitative Remote Sensing of Land Surfaces

Processing the vast amounts of data on the Earth's land surface environment generated by NASA's and other international satellite programs;

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Computer Processing of Remotely-Sensed Images 5e

provides students with methods of computer processing of remotely sensed data and introduces them to environmental applications which make use;

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Remote Sensing of Water Resources, Disasters, and Urban Studies

scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data;

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Remote Sensing and GIS Integration

remotely sensed data GIS is predominantly a data-handling technology, while remote sensing is a data retrieval and analysis technology. This;

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Neurocomputation in Remote Sensing Data Analysis

sensed satellite data. Remote sensing has now become a discipline in which ever increasing volumes of data, gathered from space together with;

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Remote Sensing for Ecology and Conservation

of remotely sensed data and analyses have tended to discourage scientists and managers from using this valuable resource. This text focuses on making;

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Multispectral Image Analysis Using the Object-Oriented Paradigm

for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and;

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Multispectral Image Analysis Using the Object-Oriented Paradigm

for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and;

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Remotely-Sensed Cities

populations and economic activity, particularly on a global scale. Remotely Sensed Cities helps to redress the balance with remote sensing books;

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Groundwater Recharge and Flow: Approaches and Challenges for Monitoring and Modeling Using Remotely Sensed Data

requires remotely sensed data and observations applied to groundwater models. Resolving the interaction of groundwater storage, flow, and recharge;

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Remote Sensing Image Classification in R

This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also;

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Assessing the Accuracy of Remotely Sensed Data

of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Now 15 chapters long, this text is the only;

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Assessing the Accuracy of Remotely Sensed Data

of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Now 15 chapters long, this text is the only;

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Computer Processing Of Remotely-Sensed Images

remotely-sensed data can be used synergistically with other spatial data sets, including hydrogeological and archaeological applications, * New;

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Remote Sensing of Urban and Suburban Areas

temporal requirements of remotely sensed data in relation to various urban phenomena; methods and techniques for analyzing and integrating remotely;

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Remote Sensing of Ice and Snow

oceanic processes. Current and potential applications of remotely sensed data are also stressed. At present, all-weather, day and night;

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Image Processing and Data Analysis with ERDAS IMAGINE (R)

Remotely sensed data, in the form of digital images captured from spaceborne and airborne platforms, provide a rich analytical and;

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Geotechnical Engineering Investigation Handbook

The Geotechnical Engineering Investigation Handbook provides the tools necessary for fusing geological characterization and investigation;

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Measuring the Oceans from Space: The Principles and Methods of Satellite Oceanography

, including some of the global applications of the data. The variety of applications of remotely sensed data to ocean science has grown significantly;

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Urban High-Resolution Remote Sensing

and algorithms focused on three very important roots of urban remote sensing: 3D urban modelling using different remotely sensed data, urban;

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