A MACHINE LEARNING DATASET FOR LARGE-SCOPE HIGH RESOLUTION REMOTE SENSING IMAGE INTERPRETATION CONSIDERING LANDSCAPE SPATIAL HETEROGENEITY

A MACHINE LEARNING DATASET FOR LARGE-SCOPE HIGH RESOLUTION REMOTE SENSING IMAGE INTERPRETATION CONSIDERING LANDSCAPE SPATIAL HETEROGENEITY

The demand for timely information about earth’s surface such as land cover and land use (LC/LU), is consistently increasing. Machine learning method shows its advantage on collecting such information from remotely sensed images while requiring sufficient training sample. For satellite remote sensing...

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Bibliographic Details
Main Authors: Y. Xu, X. Hu, Y. Wei, Y. Yang, D. Wang
Format: Article
Language:English
Published: Copernicus Publications 2019-06-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/731/2019/isprs-archives-XLII-2-W13-731-2019.pdf

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