Global and local endmembers spectral patterns to estimate the urban structure in Porto Alegre (Brazil) in Landsat images using the Linear Spectral Mixture Model procedure

Abstract. This study investigates the spectral patterns of global and local endmembers to assess urban structure estimation within Porto Alegre city, Brazil. Two distinct sets of endmembers were examined: one derived from global patterns acquired from 100 Landsat image subsets and the other from local patterns gathered across 27 analyzed images. Results reveal that the utilization of global endmember patterns tends to overestimate the presence of urban shadow in all analyzed images compared to estimates derived from local patterns. Consequently, this overestimation impacts the relative proportions of other endmembers. Despite the disparities in magnitude between fractions estimated with each set of endmembers, temporal variations exhibit similar interannual trends. The findings of this study suggest that, beyond the choice between standardized or localized models, the features that must be represented in the resulting maps should also be considered in the selection between global and local endmembers.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2024-11-07
DOI
https://doi.org/10.5194/isprs-archives-xlviii-3-2024-217-2024
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Global and local endmembers spectral patterns to estimate the urban structure in Porto Alegre (Brazil) in Landsat images using the Linear Spectral Mixture Model procedure

Mayumi C. M. Hirye, Eliana Lima da Fonseca
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Remote Sensing in Agriculture
article

Global and local endmembers spectral patterns to estimate the urban structure in Porto Alegre (Brazil) in Landsat images using the Linear Spectral Mixture Model procedure

Mayumi C. M. Hirye, Eliana Lima da Fonseca
article en

Abstract

Abstract. This study investigates the spectral patterns of global and local endmembers to assess urban structure estimation within Porto Alegre city, Brazil. Two distinct sets of endmembers were examined: one derived from global patterns acquired from 100 Landsat image subsets and the other from local patterns gathered across 27 analyzed images. Results reveal that the utilization of global endmember patterns tends to overestimate the presence of urban shadow in all analyzed images compared to estimates derived from local patterns. Consequently, this overestimation impacts the relative proportions of other endmembers. Despite the disparities in magnitude between fractions estimated with each set of endmembers, temporal variations exhibit similar interannual trends. The findings of this study suggest that, beyond the choice between standardized or localized models, the features that must be represented in the resulting maps should also be considered in the selection between global and local endmembers.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-3-2024
Universidade Federal do Rio Grande do Sul (BR), University of California, Los Angeles (US), Sustainability Institute (ZA), Geotecno (Brazil) (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Universidade Federal do Rio Grande do Sul
Sustainable cities and communities
Openalex Percentile: Top 80%
Remote Sensing in Agriculture
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Global and local endmembers spectral patterns to estimate the urban structure in Porto Alegre (Brazil) in Landsat images using the Linear Spectral Mixture Model procedure — Mayumi C. M. Hirye, Eliana Lima da Fonseca · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (2024) | TGRS Research Map | TGRS