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Data Assimilation and Remote Sensing Data
2020Satellite remote sensing with a wide range of platforms and on-board sensors has changed our view of Earth and its hydrology remarkably. They offer various type of observations on large scales and now covering more than decades of measurements.
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Remote Sensing Data Compression
2008The interest in remote sensing images is growing at an enormous pace in the last years. However, transmission and storage of remote sensing images pose a special challenge, and multiple efficient image compression systems have appeared. This chapter contributes an overview of several techniques for image coding systems, focusing on lossy approaches.
Joan Serra-Sagristà +1 more
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Data base systems for remote sensing
1980Landsat and other satellites are returning ever-increasing amounts of data, with the eventual possibility of building a total data base of the order of 1018 bits. The data, from a multiplicity of sources, must be validated, calibrated, and accurately geographically located to be of highest value.
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Dealing with Data Corruption in Remote Sensing
2005Remote sensing has resulted in repositories of data that grow at a pace much faster than can be readily analyzed. One of the obstacles in dealing with remotely sensed data and others is the variable quality of the data. Instrument failures can result in entire missing observation cycles, while cloud cover frequently results in missing or distorted ...
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Analysis of Remotely Sensed Data
1990The prospects for obtaining new information on a global scale rest on suitable access to, and organization and processing of, immense volumes of remotely sensed and other data. This chapter addresses the issue of processing high-dimensional spectral data for extraction of information on surface conditions or processes.
Jeremy F. Wallace, Norm Campbell
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Classification of Remotely Sensed Data
2007The use of classifications for land cover mapping from satellite imagery is shown. Environmental and land cover maps represent the prob- able environmental statement of various types of land use and development of landscape. Remotely sensed data could be particularly efficient for environmental and land use mapping in order to outline main ...
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2019
Remote sensing techniques and data have been used in the Swiss National Forest Inventory (NFI) since its beginnings in the 1970s. Over the decades, the image data used has changed from first analogue black and white aerial images to digitised RGB true-colour images, and then to the digital colour infrared (CIR) sensor data in use today.
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Remote sensing techniques and data have been used in the Swiss National Forest Inventory (NFI) since its beginnings in the 1970s. Over the decades, the image data used has changed from first analogue black and white aerial images to digitised RGB true-colour images, and then to the digital colour infrared (CIR) sensor data in use today.
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Selection of Remotely Sensed Data
2003An increasing number of sensors are available for forest ecologists and managers seeking to map attributes of forest canopy cover, forest structure and composition, and their dynamics. This Chapter seeks to put these advances within the context of the needs of forest managers and scientists.
Michael A. Lefsky, Warren B. Cohen
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Verification of Remotely Sensed Data
2000Ground or field checks are an important part of any remote sensing study and are necessary to provide an accurate and useful interpretive product. Field checking is necessary to confirm the validity of spectral, spatial, and morphological interpretations.
Trude V. V. King, Roger N. Clark
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