Remote sensing data management and its use for classification and inference purposes is at the forefront of research tasks nowadays. There are, however, some inherent drawbacks and difficulties when dealing with, and ...
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ISBN:
(纸本)9798350360332;9798350360325
Remote sensing data management and its use for classification and inference purposes is at the forefront of research tasks nowadays. There are, however, some inherent drawbacks and difficulties when dealing with, and understanding how satellite information is provided (particularly when referring to multiband/multispectral satellite platforms) and how different and disparate datasets related to soil content can be used and merged with this imagery. We present WALGREEN. The aim of this tool is to provide a secure environment to handle the whole process to use polygons or, geographical coordinates in tiff/geotiff images, have real-time access to images, save and get soil organic carbon real measurements, and generate datasets for machine learning training and inferential methods. We also aim to providing a framework to preprocess soil organic carbon information from different but accepted sources, like the Land Use/Cover Area frame statistical Survey database, so that even without real measurements, researchers may be able to start training different machine learning methodologies.
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