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Quantitative remote sensing is a branch of remote sensing. The quantitative remote sensing system does not directly measure land surface parameters of interest. Instead, the signature remote sensors receive is electromagnetic radiation reflected, scattered, and emitted from both the surface and the atmosphere . [ 1 ]
The quality of remote sensing data consists of its spatial, spectral, radiometric and temporal resolutions. Spatial resolution The size of a pixel that is recorded in a raster image – typically pixels may correspond to square areas ranging in side length from 1 to 1,000 metres (3.3 to 3,280.8 ft).
The data processed in the cube is made analysis ready [4] before being ingested and indexed into the AGDC. Analysis ready data is pre-processed data that has applied corrections for instrument calibration (gains and offsets), geolocation (spatial alignment) and radiometry (solar illumination, incidence angle, topography, atmospheric interference).
Remote sensing applications are similar to graphics software, but they enable generating geographic information from satellite and airborne sensor data. Remote sensing applications read specialized file formats that contain sensor image data, georeferencing information, and sensor metadata .
The Flow-chart diagram (right), excerpted from the final report of that project, [23] shows how to infer variables of interest such as canopy state, radiative fluxes, environmental budget, production in quantity and quality, from remote sensing data and ancillary information. In that diagram, the small blue-green arrows indicate the direct way ...
[1] [2] Accurate calibration of the relationships and/or models used is an important condition for successful inversion on water remote sensing techniques and the determination of concentration of water quality parameters from observed spectral remote sensing data. [1]
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