Global Forest Types Based on Climatic and Vegetation Data

Xu, Chen; Zhang, Xianliang; Hernandez-Clemente, Rocio; Lu, Wei; Manzanedo, Rubén D.

doi:10.3390/su14020634

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Global Forest Types Based on Climatic and Vegetation Data

Chen Xu, Xianliang Zhang, Rocio Hernandez-Clemente, Wei Lu, Rubén D. Manzanedo

Sustainability, Volume: 14, Issue: 2, Start page: 634

Swansea University Author: Rocio Hernandez-Clemente

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DOI (Published version): 10.3390/su14020634

Abstract

Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aime...

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Published in:	Sustainability
ISSN:	2071-1050
Published:	MDPI AG 2022
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URI:	https://cronfa.swan.ac.uk/Record/cronfa59121
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spelling	2022-01-21T09:32:22.6632654 v2 59121 2022-01-10 Global Forest Types Based on Climatic and Vegetation Data 0b007e63ef097cd47d6bc60b58379103 Rocio Hernandez-Clemente Rocio Hernandez-Clemente true false 2022-01-10 FGSEN Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aimed to improve the distribution of forest types to be more realistic and useful for biodiversity preservation, forest management, and ecological and forestry research. The forest types were classified using an unsupervised cluster analysis method by combining climate variables with normalized difference vegetation index (NDVI) data. Unforested regions were masked out to constrict our study to forest type distributions, using a 20% tree cover threshold. Descriptive names were given to the defined forest types based on annual temperature, precipitation, and NDVI values. Forest types had distinct climate and vegetation characteristics. Regions with similar NDVI values, but with different climate characteristics, which would be merged in previous classifications, could be clearly distinguished. However, small-range forest types, such as montane forests, were challenging to differentiate. At macroscale, the resulting forest types are largely consistent with land-cover types or vegetation types defined in previous studies. However, considering both potential and current vegetation data allowed us to create a more realistic type distribution that differentiates actual vegetation types and thus can be more informative for forest managers, conservationists, and forest ecologists. The newly generated forest type distribution is freely available to download and use for non-commercial purposes as a GeoTIFF file via doi: 10.13140/RG.2.2.19197.90082). Journal Article Sustainability 14 2 634 MDPI AG 2071-1050 forest types, NDVI, AVHRR GIMMS, temperature range, precipitation range 7 1 2022 2022-01-07 10.3390/su14020634 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University Education Department of Hebei Province Grant: BJ2020025 2022-01-21T09:32:22.6632654 2022-01-10T14:35:34.3169261 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Geography Chen Xu 1 Xianliang Zhang 2 Rocio Hernandez-Clemente 3 Wei Lu 4 Rubén D. Manzanedo 5 59121__22090__7919b41368264a92bc67cda4a1949032.pdf sustainability-14-00634.pdf 2022-01-10T14:35:34.3167541 Output 3287340 application/pdf Version of Record true Copyrightr© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title	Global Forest Types Based on Climatic and Vegetation Data
spellingShingle	Global Forest Types Based on Climatic and Vegetation Data Rocio Hernandez-Clemente
title_short	Global Forest Types Based on Climatic and Vegetation Data
title_full	Global Forest Types Based on Climatic and Vegetation Data
title_fullStr	Global Forest Types Based on Climatic and Vegetation Data
title_full_unstemmed	Global Forest Types Based on Climatic and Vegetation Data
title_sort	Global Forest Types Based on Climatic and Vegetation Data
author_id_str_mv	0b007e63ef097cd47d6bc60b58379103
author_id_fullname_str_mv	0b007e63ef097cd47d6bc60b58379103_***_Rocio Hernandez-Clemente
author	Rocio Hernandez-Clemente
author2	Chen Xu Xianliang Zhang Rocio Hernandez-Clemente Wei Lu Rubén D. Manzanedo
format	Journal article
container_title	Sustainability
container_volume	14
container_issue	2
container_start_page	634
publishDate	2022
institution	Swansea University
issn	2071-1050
doi_str_mv	10.3390/su14020634
publisher	MDPI AG
college_str	Faculty of Science and Engineering
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department_str	School of Biosciences, Geography and Physics - Geography{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Geography
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description	Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aimed to improve the distribution of forest types to be more realistic and useful for biodiversity preservation, forest management, and ecological and forestry research. The forest types were classified using an unsupervised cluster analysis method by combining climate variables with normalized difference vegetation index (NDVI) data. Unforested regions were masked out to constrict our study to forest type distributions, using a 20% tree cover threshold. Descriptive names were given to the defined forest types based on annual temperature, precipitation, and NDVI values. Forest types had distinct climate and vegetation characteristics. Regions with similar NDVI values, but with different climate characteristics, which would be merged in previous classifications, could be clearly distinguished. However, small-range forest types, such as montane forests, were challenging to differentiate. At macroscale, the resulting forest types are largely consistent with land-cover types or vegetation types defined in previous studies. However, considering both potential and current vegetation data allowed us to create a more realistic type distribution that differentiates actual vegetation types and thus can be more informative for forest managers, conservationists, and forest ecologists. The newly generated forest type distribution is freely available to download and use for non-commercial purposes as a GeoTIFF file via doi: 10.13140/RG.2.2.19197.90082).
published_date	2022-01-07T04:16:11Z
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Global Forest Types Based on Climatic and Vegetation Data

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