A large-scale disturbance mapping ensemble through data-driven regionalization-Reference-Cited by-同舟云学术

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A large-scale disturbance mapping ensemble through data-driven regionalization

Published:2023-06-18 Issue:12 Volume:44 Page:3700-3725
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Bueno Inacio Thomaz¹^ORCID,Hird Jennifer²^ORCID,McDermid Gregory John³^ORCID,Galvão Lênio Soares⁴^ORCID,Acerbi Fausto Weimar⁵^ORCID

Affiliation:

1. Interdisciplinary Centre of Energy Planning, University of Campinas, Campinas, Brazil

2. Alberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, AB, Canada

3. Department of Geography, University of Calgary, Calgary, AB, Canada

4. Department of Remote Sensing, National Institute for Space Research, Campos, Brazil

5. Department of Forest Science, Federal University of Lavras, Lavras, Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2225711

Reference83 articles.

1. Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

2. Ecoregions

3. Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation

4. Random forest in remote sensing: A review of applications and future directions

5. Land cover changes in the Brazilian Cerrado and Caatinga biomes from 1990 to 2010 based on a systematic remote sensing sampling approach

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