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Chunhua Yan

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

2

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100

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0

Scholarly Papers (2)

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1.

Unveiling Seaward Expansion Pattern in Mangrove Forests Using Uav Remote Sensing and Deep Learning

Downloads 74 (852,604)

Unveiling Seaward Expansion Pattern in Mangrove Forests Using Uav Remote Sensing and Deep Learning

Number of pages: 55 Posted: 08 May 2025
Zhi Zhang, Chunhua Yan, Ruili Li, Bing Li and Xiaoxue Shen
affiliation not provided to SSRN, affiliation not provided to SSRN, Peking University - Shenzhen Graduate School, Tsinghua University and affiliation not provided to SSRN
Downloads 40 (1,224,220)

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Mangrove, UAV remote sensing, Deep learning, Seaward expansion pattern, Species composition, Stand structure

Unveiling Seaward Expansion Pattern in Mangrove Forests Using Uav Remote Sensing and Deep Learning

Number of pages: 55 Posted: 16 Apr 2025
Zhi Zhang, Chunhua Yan, Ruili Li, Bing Li and Xiaoxue Shen
affiliation not provided to SSRN, affiliation not provided to SSRN, Peking University - Shenzhen Graduate School, Tsinghua University and affiliation not provided to SSRN
Downloads 34 (1,296,409)

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Mangrove, UAV remote sensing, Deep Learning, Seaward expansion pattern, Species composition, Stand structure

2.

Transformer-based mapping of 10 m spatiotemporally seamless daily urban evapotranspiration using geospatial foundation embeddings

Number of pages: 53 Posted: 08 Apr 2026
Jiawei Jiang, Wenli Zhao, Chunhua Yan, Guo Yu Qiu, Wenjie Yan, Kaiyu Li, Dengkui Mo, Biqing Zhu and Yujiu Xiong
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Peking University - Shenzhen Graduate School, affiliation not provided to SSRN, affiliation not provided to SSRN, Central South University of Forestry and Technology, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 26 (1,436,435)

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Urban evapotranspiration, spatiotemporally seamless, geospatial foundation embeddings, transformer, Machine Learning, Shenzhen