March 5, 2024, 2:49 p.m. | Lei Li, Tianfang Zhang, Zhongyu Jiang, Cheng-Yen Yang, Jenq-Neng Hwang, Stefan Oehmcke, Dimitri Pierre Johannes Gominski, Fabian Gieseke, Christian Ig

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.01932v1 Announce Type: new
Abstract: Accurate and consistent methods for counting trees based on remote sensing data are needed to support sustainable forest management, assess climate change mitigation strategies, and build trust in tree carbon credits. Two-dimensional remote sensing imagery primarily shows overstory canopy, and it does not facilitate easy differentiation of individual trees in areas with a dense canopy and does not allow for easy separation of trees when the canopy is dense. We leverage the fusion of three-dimensional …

abstract arxiv build carbon carbon credits change climate climate change consistent cs.cv data differentiation easy management sensing shows strategies support sustainable tree trees trust type

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