Estimating fractional vegetation cover from multispectral unmixing modeled with local endmember variability and spatial contextual information-Reference-Cited by-同舟云学术

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Estimating fractional vegetation cover from multispectral unmixing modeled with local endmember variability and spatial contextual information

Published:2024-03 Issue: Volume:209 Page:481-499
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Zhang Tianqi^ORCID,Liu Desheng^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Reference123 articles.

1. SLIC superpixels compared to state-of-the-art superpixel methods;Achanta;IEEE Trans. Pattern Anal. Mach. Intell.,2012

2. Improved spatial-spectral superpixel hyperspectral unmixing;Alkhatib;Remote Sens.,2019

3. Net changes in regional woody vegetation cover and carbon storage in Texas drylands, 1937–1999;Asner;Glob. Change Biol.,2003

4. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: comparing multispectral and hyperspectral observations;Asner;Int. J. Remote Sens.,2002

5. Using semivariogram indices to analyse heterogeneity in spatial patterns in remotely sensed images;Balaguer-Beser;Comput. Geosci.,2013

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