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Assessing the Accuracy of Remotely Sensed Data

The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles;

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Assessing the Accuracy of Remotely Sensed Data

The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles;

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Neurocomputation in Remote Sensing Data Analysis

networks, as a new form of computational paradigm, seem well suited to many of the tasks involved in remotely sensed image analysis. This book;

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Real-Time Auto Geotagging and Visualization of Remotely Sensed Data

location of the remotely sensed data in real time.;

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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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Quantitative Remote Sensing of Land Surfaces

presents practical quantitative algorithms for estimating various land surface variables from remotely sensed observations. A concise review of the;

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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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Classification Methods for Remotely Sensed Data

Since the publishing of the first edition of Classification Methods for Remotely Sensed Data in 2001, the field of pattern recognition has;

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Remote Sensing and GIS Accuracy Assessment

The development of robust accuracy assessment methods for the validation of spatial data represents a difficult challenge for the;

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Remote Sensing and GIS Accuracy Assessment

The development of robust accuracy assessment methods for the validation of spatial data represents a difficult challenge for the;

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Remote Sensing and GIS Integration

book addresses the need to combine remotely sensed data with cartographic, socioeconomic, and environmental data and GIS functionalities;

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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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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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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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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 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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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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Data Quality

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling;

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Multispectral Image Analysis Using the Object-Oriented Paradigm

, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.;

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Multispectral Image Analysis Using the Object-Oriented Paradigm

, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.;

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Remote Sensing of Ice and Snow

for analysis of remotely sensed data are not straightforward, Chapter 1 serves to introduce the reader to some of the optical, thermal and;

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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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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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Map Librarianship

, downloading, delivering, and assessing maps, remotely sensed imagery, and other geospatial resources and services, primarily from trusted government;

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Contributions of Land Remote Sensing for Decisions About Food Security and Human Health

workshop on the potential contributions of remotely sensed data to land-use and land-cover change and ways to use physical, biological, temporal;

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