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Get Free AccessTrees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.6% of the national aboveground carbon stocks. Natural forests cover 11% of the total tree count and 51.4% of the national carbon stocks, with an overall carbon stock uncertainty of 16.9%. The mapping of all trees allows partitioning to any landscapes classification and is urgently needed for effective planning and monitoring of restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.
Maurice Mugabowindekwe, Martin Brandt, Jérôme Chave, Florian Reiner, David L. Skole, Ankit Kariryaa, Christian Igel, Pierre Hiernaux, Philippe Ciais, Ole Mertz, Xiaoye Tong, Sizhuo Li, Gaspard Rwanyiziri, Thaulin Dushimiyimana, Alain Ndoli, Valens Uwizeyimana, Jens‐Peter Barnekow Lillesø, Fabian Gieseke, Compton Tucker, Sassan Saatchi, Rasmus Fensholt (2022). Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda. Nature Climate Change, 13(1), pp. 91-97, DOI: 10.1038/s41558-022-01544-w.
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Type
Article
Year
2022
Authors
21
Datasets
0
Total Files
0
Language
English
Journal
Nature Climate Change
DOI
10.1038/s41558-022-01544-w
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