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GlobeSAR was a very important Program that propelled Canada and the Canada Centre for Remote Sensing as a key contributor to the international Earth Observation Community, and positioned companies such as Radarsat International Inc (now part of MacDonald Detwiller and Associates) and Intermap (formerly Intera) as key commercial partners in providing data and services based on Synthetic ...
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).
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 .
Hence the remote sensing data has to be classified first, followed by processing by various data enhancement techniques so as to help the user to understand the features that are present in the image. Such classification is a complex task which involves rigorous validation of the training samples depending on the classification algorithm used.
It also allows to connect to data using multiple pre-built connectors [28] Data Type. Tableau express automatically data types and fields. Tableau will make use of the data type that the data source has defined if it exists, or it will choose a data type if the data source does not specify one. In Tableau, the following data types are supported ...
Water Remote Sensing is the observation of water bodies such as lakes, oceans, and rivers from a distance in order to describe their color, state of ecosystem health, and productivity. Water remote sensing studies the color of water through the observation of the spectrum of water leaving radiance.