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Analysis of classification algorithms for crop detection using LANDSAT 8 images
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Remote sensing - the acquisition of information about an object or phenomenon
without making physical contact with the object - is applied in a multitude of
different areas, ranging from agriculture, forestry, cartography, hydrology, geology,
meteorology, aerial traffic control, among many others. Regarding agriculture, an
example of application of this information is regarding crop detection, to monitor
existing crops easily and help in the region’s strategic planning.
In any of these areas, there is always an ongoing search for better methods that
allow us to obtain better results. For over forty years, the Landsat program has
utilized satellites to collect spectral information from Earth’s surface, creating a
historical archive unmatched in quality, detail, coverage, and length. The most
recent one was launched on February 11, 2013, having a number of improvements
regarding its predecessors.
This project aims to compare classification methods in Portugal’s Ribatejo region,
specifically regarding crop detection. The state of the art algorithms will be used
in this region and their performance will be analyzed.
Descrição
Palavras-chave
Land cover Remote sensing Landsat Classification Crop detection