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Titel:

A spatio-temporal unmixing with heterogeneity model for the identification of remotely sensed MODIS aerosols: Exemplified by the case of Africa

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Longshan Yang, Peng Luo, Zehua Zhang, Yongze Song, Kai Ren, Ce Zhang, Joseph Awange, Peter M. Atkinson, Liqiu Meng
Abstract:
Aerosols are crucial constituents of the atmosphere, with significant impacts on air quality. Aerosol optical depth (AOD) is critical in assessing solar resources and modeling sky radiance. However, comprehensive aerosol studies at a continental scale are limited, and existing methodologies need to consider spatial characteristics. This study develops a spatio-temporal unmixing with heterogeneity (STUH) model to evaluate spatial patterns and temporal trends of atmospheric aerosols across the Afr...     »
Stichworte:
Aerosol optical depth, Remote sensing, Spatio-temporal unmixing, Spatial heterogeneity Africa
Zeitschriftentitel:
International Journal of Applied Earth Observation and Geoinformation
Jahr:
2024
Volltext / DOI:
doi:https://doi.org/10.1016/j.jag.2024.104068
WWW:
www.sciencedirect.com/science/article/pii/S1569843224004229
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