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Obtaining Remote-sensing Data

2000
Images from satellite-based remote-sensing systems are primarily used to obtain data on large areas (Barrett and Curtis 1992; Theilen-Willige 1993). The spatial resolution of a satellite-based remote-sensing system is commonly insufficient to delineate and identify small objects on the Earth surface (see Table 3.1).
Friedrich Kuehn, Bernhard Hoerig
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NEAR-LOSSLESS COMPRESSION OF REMOTE-SENSING DATA

2003
This paper describes data compression algorithms capable to preserve the scientific quality of remote-sensing data, yet allowing a considerable bandwidth reduction to be achieved. Unlike lossless techniques, by which a moderate compression ratio (CR) is attainable, due to the intrinsic noisiness of the data, and conventional lossy techniques, in which ...
Bruno Aiazzi   +3 more
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Remote Sensing Data Sources

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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Spaceborne Remote Sensing Data

2013
Since 1972, seven Landsat series, named Landsat 1 to 7 sequentially, have been launched by the U.S. National Aeronautics and Space Administration (NASA) into outer space. Landsat 6 failed at launch. Landsat 1,2, and 3 continue orbiting at an altitude of approximately 900 km and Landsat 4, 5, and 7 at an altitude of approximately 700 km.
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Rapid remote sensing data collection

2018
The acquisition of remotely sensed, high resolution, topographic data has been transformed considerably over the past decade by new technology and geospatial processing platforms. Originally developed within the computer vision industry, Structure from Motion (SfM) is a photogrammetric method for creating 3D models of a feature or topography from ...
Jones, KE   +4 more
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Remote Sensing Data Management

2019
The stereo GIS application is driven by aerial-image metadata as well as administration data like task lists and priority settings. All metadata including the interpretation results are stored in a spatial database. For analytic purposes the data is accessible by means of Structured Query Language (SQL), GIS tools or any statistical software.
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Data Assimilation and Remote Sensing Data

2020
Satellite 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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Analysis of Remotely Sensed Data

1990
The 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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Selection of Remotely Sensed Data

2003
An 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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Classification of Remotely Sensed Data

2007
The 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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