MULTIPLE ENDMEMBER SPECTRAL MIXTURE ANALYSIS OF DESIS IMAGE TO IDENTIFY ROOFTOPS IN KIGALI

نویسندگان

چکیده

Abstract. The development and increase of multi hyperspectral sensors in the recent years have significantly improved urban structure analysis interpretation. current study is first to investigate potential DESIS images for detection or identification roof materials. After field campaigns 2014, 2015 2018 collect ground truth points rooftops radiometric properties; a linear spectral mixture, implemented using non-negative least squares (NNLS) regression based on sequential coordinate-wise algorithm (SCA) was applied image from 2020 Kigali city identify different material color. Although results show that most endmembers were predicted with very low probability, proved combination mixture data such as great rootops material. presented also highlghted number challenges resulting choice colinearity between

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ژورنال

عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

سال: 2022

ISSN: ['1682-1777', '1682-1750', '2194-9034']

DOI: https://doi.org/10.5194/isprs-archives-xlvi-1-w1-2021-39-2022