Wang Feng

Prof.  Wang Feng

Organization: Research Institute of Ecology Conservation and Restoration, Chinese Academy of Forestry

Research category: Ecology

Research field: Ecological modeling and remote sensing

E-mail: wangfeng@caf.ac.cn

Main work

Professor Feng Wang is the leader of Development Strategy and Policy Lab on Desertification Combating in Institute of Ecological Conservation and Restoration, Institute of Desertification Studies, Chinese Academy of Forestry. Professor Wang focuses on the ecohydrological mechanism of vegetation structure, pattern, and water cycle on dryland by "satellite-UAV-ground" observation technology to monitor the sparse vegetation on dryland. His primary research sites are in sandy land in Northern China, where he explored the "greening" area and driving factors on dryland. Professor Wang conducts research at a number of spatial and temporal scales; from small-scale control experiment, "in situ" ecological observation up to global analyses of climate trends on dryland. A major focus of his research is the development of new methods to improve the measurement and prediction of dryland ecosystem carbon and water exchange. He was a recipient of the Distinguished Young Scientist Award from Chinese Academy of Forestry (2016), an Early Career Award from China State Forestry and Grassland Administrator (2019), and Leading scientist in the field of Forestry and Grassland by National Forestry and Grassland Administration (2023).

Key research projects

  • National Key Research and Development Program of China. Developmentand demonstration of close-to-nature restoration and ecological equality promotion technology in typical Korqin grassland. 2023.12-2027.11

  • National Natural Science Foundation of China (General Program), Mapping elm open woodland and estimating their potential primary production based on high-resolution satellite image and solar-induced chlorophyll fluorescence. 2022.1-2025.12

  • Chinese Academy of Forestry Science Funds (Young Scientists Corporation Program): Retrieval of solar-induced chlorophyll fluorescence and its associated with vegetation primary production. 2020.1-2024.12.

  • National Key Research and Development Program of China, Monitoring technology integration and application demonstration of ecological equality of forest, dryland and wetland   ecosystem. 2017.7-2021.6

  • National Natural Science Foundation of China (General Program), Linking the spatial pattern and structural characteristics of vegetation and hydrological process in Elm (Ulmus pumila) woodland landscapes in Hunshandake sandy land: An ecohydrological perspective, 2016.1-2019.12

Awards & achievements

  • 2023, Leading scientist in the field of Forestry and Grassland by National Forestry and Grassland Administration

  • 2023, Scientific Management technique and water-use mechanism of Pinus Sylvestris var. Mongolica plantation adapt to environment change" awarded the second prize on "Liangxi" science and technology by Chinese Society of Forestry

  • 2022, "Classification, Partition and Mapping of Gobi Desert in China" awarded the second prize on science and technology by Chinese Society of Soil and Water Conservation

  • 2020, awarded the third prize in the "Liangxi" excellent papers competition

  • 2019, Early Career Award from China State Forestry and Grassland Administrator (Young Distinguished Scientist in Forestry)

  • 2016, awarded as the distinguished young scientist of Chinese Academy of Forestry

Published articles & books

  • Cong W., Li X., Pan X., Liu X., Lu Q., Wang F*. 2022. A new scientific framework of dryland ecological quality assessment based on 1OAO principle. Ecological Indicators, 136, 108595.

  • Wang F*, Pan X, Gerlein‐Safdi C, Cao X, Wang S, Gu L, Wang D, & Lu Q*. 2020. Vegetation restoration in Northern China: A contrasted picture. Land Degradation & Development, 31(6), 669–676.

  • Wang H, Han D, Mu Y, Jiang L, Yao X, Bai Y, Lu Q, Wang F*. 2019. Landscape-level vegetation classification and fractional woody and herbaceous vegetation cover estimation over the dryland ecosystems by unmanned aerial vehicle platform. Agricultural and Forest Meteorology, 278: 107665.

  • Mu Y, Wang F*, Zheng B, Guo W, Feng Y*. 2018. A rapid image-based method to determine the morphological characteristics of gravels on desert pavement. Geomorphology. 304, 89–98.

  • Li X, Tian X, Duan T, Cao X, Yang K, Lu Q, Wang F*. 2023. Estimation of fractional woody and herbaceous vegetation cover in Temperate Sparse Forest Grassland using fusion of UAV and Satellite imagery National Remote Sensing Bulletin, 27(9):2139-2152.

Other results

Patent:

  • A image-based method to compute the landscape-level vegetation coverage use by UAV. China patent number, ZL 201610913357.8. Inventor: Wang Feng, Han Dong, Wang Haozhou, Lu Qi, Pan Xubin. ZL20160913357.8

Softwares:

  • UAV High precision image   analysis platform Ver3.0[UAV-HiRAP Ver.3.0], 2019, People's Republic of China Software Copyright Registration Number: 2019SR0286422

  • A WebGIS-based database of geographic information on sandy land in China Ver2.0[GIP-DLC Ver.2.0]. 2018. People's Republic of China Software Copyright Registration Number: 2018SR921265.

  • UAV High precision image analysis platform (UAV-HPIAP) [UAV-HiRAP Ver.2.0]. Software Copyright Registration Number: 2017R11L741172

  • UAV High precision image analysis platform (UAV-HPIAP) [Ver. 1.0.] Software Copyright Registration Number: 2016SR198498

  • A WebGIS-based database of geographic information on sandy land in China. Software Copyright Registration Number: 2016SR036010