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A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires

Quanli Xu Wenhui Li Jing Liu Xiao Wang

森林生态系统（英文版）2023，Vol.10Issue(2)：195-214,20.

A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires

Quanli Xu ¹Wenhui Li ¹Jing Liu ¹Xiao Wang¹

作者信息

1. Faculty of Geography,Yunnan Normal University,Kunming 650500,China||GIS Technology Engineering Research Centre for West-China Resources and Environment of Ministry of Education,Kunming,650500,China||Yunnan Geospatial Information Technology Engineering Research Center,Kunming 650500,China||Key Laboratory of Resources and Environment Remote Sensing in Yunnan University,Kunming 650500,China
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摘要

关键词

Spatial prediction of forest fires/Data-driven models/Geographic similarity/Non-fire point data/Data confidence

Key words

Spatial prediction of forest fires/Data-driven models/Geographic similarity/Non-fire point data/Data confidence

引用本文复制引用

Quanli Xu,Wenhui Li,Jing Liu,Xiao Wang..A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires[J].森林生态系统（英文版）,2023,10(2):195-214,20.

基金项目

This study was financially supported by the National Natural Science Fundation of China(Grant Nos.42161065 and 41461038).We would also like to express our sincere gratitude to the editors and reviewers who invested considerable time and effort in their comments on this paper.We would also like to thank Editage(www.editage.cn)for the English language editing. （Grant Nos.42161065 and 41461038）

森林生态系统（英文版）

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ISSN：2095-6355

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