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Qiu, Haihong; Han, Hairong; Cheng, Xiaoqin; Kang, Fengfeng (2025) Predicting forest carbon storage and identifying hotspot in the Loess Plateau under future climate change–supporting China's dual carbon strategy. International Journal of Digital Earth, 18 (1). doi:10.1080/17538947.2025.2516727

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Reference TypeJournal (article/letter/editorial)
TitlePredicting forest carbon storage and identifying hotspot in the Loess Plateau under future climate change–supporting China's dual carbon strategy
JournalInternational Journal of Digital Earth
AuthorsQiu, HaihongAuthor
Han, HairongAuthor
Cheng, XiaoqinAuthor
Kang, FengfengAuthor
Year2025 (December 31)Volume18
Issue1
PublisherInforma UK Limited
DOIdoi:10.1080/17538947.2025.2516727Search in ResearchGate
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Mindat Ref. ID18595888Long-form Identifiermindat:1:5:18595888:6
GUID0
Full ReferenceQiu, Haihong; Han, Hairong; Cheng, Xiaoqin; Kang, Fengfeng (2025) Predicting forest carbon storage and identifying hotspot in the Loess Plateau under future climate change–supporting China's dual carbon strategy. International Journal of Digital Earth, 18 (1). doi:10.1080/17538947.2025.2516727
Plain TextQiu, Haihong; Han, Hairong; Cheng, Xiaoqin; Kang, Fengfeng (2025) Predicting forest carbon storage and identifying hotspot in the Loess Plateau under future climate change–supporting China's dual carbon strategy. International Journal of Digital Earth, 18 (1). doi:10.1080/17538947.2025.2516727
In(2025, December) International Journal of Digital Earth Vol. 18 (1). Informa UK Limited

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R Core Team. 2024. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
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