LINEAR SPECTRAL MIXING MODEL APPLIED IN IMAGES FROM PROBA-V SENSOR: A SPATIAL MULTIRESOLUTION APPROACH

Cerqueira Dutra, Andeise; Shimabukuro, Yosio Edemir; Arai, Egidio

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dc.contributor	Instituto Nacional de Pesquisas Espaciais, FAPESP, CNPq	en-US
dc.creator	Cerqueira Dutra, Andeise
dc.creator	Shimabukuro, Yosio Edemir
dc.creator	Arai, Egidio
dc.date	2019-08-28
dc.date.accessioned	2022-03-21T18:27:59Z
dc.date.available	2022-03-21T18:27:59Z
dc.identifier	https://revistas.ufpr.br/raega/article/view/67098
dc.identifier	10.5380/raega.v46i3.67098
dc.identifier.uri	http://biblioteca-repositorio.clacso.edu.ar/handle/CLACSO/74646
dc.description	The complexity of pixel composition of orbital images has been commonly referred to the spectral mixture problem. The acquisition of endmembers (pure pixels) direct from image under study is one of the most commonly employed approaches. However, it becomes limited in low or moderate spatial resolutions due to the lower probability of finding those pixels. In this way, this work proposes the combined use of images with different spatial resolutions to estimate the spectral responses of the endmembers in low spatial resolution image, from the obtained proportions derived from the spatial higher-resolution images. The proposed methodology was applied to products provided by PROBA-V satellite with spatial resolution of 100 m and 1 km in the Pantanal region of Mato Grosso state. Initially, the fraction images (proportions) were generated from the 100 m dataset using the endmembers selected directly in the image, considering the higher probability of finding pure pixels in such images. Following the spectral responses of the endmembers in 1 km were estimated by multiple linear regression, using the proportions of the endmembers in the pixels derived from 100 m images. For the evaluation, the endmembers fraction images were compared and field data was used. These analyses indicated that the spectral responses estimated allowed to improve the results with regard to error, to variability, and to the identification of endmembers proportions, considering that inadequate choice of pixels considered as pure in low spatial resolution images can affect the quality of the fraction images for operational use.	en-US
dc.format	application/pdf
dc.format	application/pdf
dc.language	eng
dc.language	por
dc.publisher	UFPR	pt-BR
dc.relation	https://revistas.ufpr.br/raega/article/view/67098/39192
dc.relation	https://revistas.ufpr.br/raega/article/view/67098/39184
dc.rights	Direitos autorais 2019 Raega - O Espaço Geográfico em Análise	pt-BR
dc.source	RA'E GA Journal - The Geographic Space in Analysis; v. 46, n. 3 (2019): 7º GeoPantanal - Simpósio de Geotecnologias no Pantanal; 48-62	en-US
dc.source	Raega - O Espaço Geográfico em Análise; v. 46, n. 3 (2019): 7º GeoPantanal - Simpósio de Geotecnologias no Pantanal; 48-62	pt-BR
dc.source	2177-2738
dc.source	1516-4136
dc.source	10.5380/raega.v46i3
dc.subject	Sensoriamento Remoto	en-US
dc.subject	Estimated Endmembers; Moderate Spatial Resolution; Linear Regression; Regional Scale; Pantanal	en-US
dc.title	LINEAR SPECTRAL MIXING MODEL APPLIED IN IMAGES FROM PROBA-V SENSOR: A SPATIAL MULTIRESOLUTION APPROACH	en-US
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type		pt-BR