Dr. Na Chen

My research focuses on applying remote sensing to better understand when, where, how and why tropical forest changes and address critical environmental challenges. My work combines advanced geospatial techniques with data-driven approaches to provide valuable insights into land use land cover change (forest cover), forest dynamics, and natural resource management. My research interests are mainly tropical forest disturbance, regrowth monitoring, and forest carbon stock estimation based on multi-source remote sensing data.

Sept.2019-Nov.2023 Ph.D. in Remote Sensing, Wageningen University

Sept.2017-Mar.2019 MSc in Geo-information Science and Earth Observation, Faculty ITC, University of Twente

Aug.2012-Jan.2013 Exchange student, Murray State University

Sept.2009-Jul.2013 BSc in Geography, Gannan Normal University

Jun.2026–Present Postdoctoral Associate (Supervisor: Dr. Lalasia Bialic-Murphy), Swiss Federal Institute for Forest, Snow and Landscape Research (WSL),ETH Domain

Jun.2025–Jun.2026 Postdoctoral Associate (Supervisor: Prof. Sherrie Wang), Department of Mechanical Engineering, Massachusetts Institute of Technology

Feb.2024-May.2025 Postdoctoral Associate (Supervisor: Prof. César Terrer), Dept. of Civil and Environmental Engineering, Massachusetts Institute of Technology

Aug.2021–Jan.2022 Geospatial Analyst Intern, SDG Integration Team, United Nations Development Programme, New York, USA (Remote,Part-time)

Aug.2014–Aug.2017 Geography Teacher, Class Supervisor, Psychological Counseling Teacher,Ruijin No. 2 Middle School, Jiangxi Province, China

Aug.2013–Aug.2014 Geography Teacher, Class Supervisor, Xuwen No. 1 Middle School, Guangdong Province, China

Heinrich V., Holcomb, A., Besnard, S., Requena Suarez, D., Cook- Patton, S., Bourgoin, C., Chazdon, R., Gibbs, D. A., Mendes, F.S., McNicol, I., Wheeler, C., Silva-Junior, C.H.L., Amani, B.H.K.,Bastin, J., Nguba. T.B., Chen, N., Chen, H., Ciais, P., Dalagno, R., Dou, X., Duan, Q., Gao, X., Goodarzi, A.N., Hérault, B., House, H., Lapola, D. M., Liang, M., Meng, Z., Nabuurs, G., Poor, E., Parsons, L., Reiche, J., Sitch, S., Ruben Valbuena, R., Welsink, A., Wiltshire, S., Wu, C., Xu, Y., Zhao, J., Aragão, L. and Herold, M.(2026). A meta-analysis of carbon losses and gains from tropical moist forest degradation and regeneration. Science Advances,12(27).https://www.science.org/doi/10.1126/sciadv.adz1923

Ma H., Xu, L., Li, B., Wu, J. and Chen, N.. (2026) Defining and valuing reservoir ecosystem services: A unified framework and large-scale assessment of 400 representative Chinese reservoirs. Applied Geography, 191.https://doi.org/10.1016/j.apgeog.2026.104013

Chen, N.^*,Feng, Y., Wang, N., Yu, J., Alizadeh, M. R., Cui, Y., Ye, N., Jiao, W., Fisher, J. B., & Terrer, C. (2026). High spatiotemporal resolution monitoring of crop water stress across the contiguous United States using Harmonized Landsat and Sentinel-2 data. Agricultural Water Management, 323, 110094. https://doi.org/10.1016/j.agwat.2025.110094

Zheng Z., Li, Y., Lyu H., Huang, C., Li, R., Chen, N., Bi, S., Liu, G., Li, Y., Lei, S., Zhang, R. and Huang, C. (2025) Enhanced algorithm for water transparency estimation in turbid plateau waters using Orbita Hyperspectral (OHS) Imagery. IEEE Transactions on Geoscience and Remote Sensing, 63. http://dx.doi.org/10.1109/TGRS.2025.3543564

Zheng Z., Liu, Y., Chen, N., Liu, G., Lei, S., Xu, J., Li, J., Ren, J. and Huang, C. (2024) A 35-Year Analysis of Vegetation Cover in Rare-Earth Mining Areas Using Landsat Data. Forests, 15(11), 1999.https://doi.org/10.3390/f15111999

Cui, Y., Dong, J., Zhang, C., Yang, J., Chen, N., Guo, P., Di, Y., Chen, M., Li, A. and Liu, R. (2024) Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets. Scientific Data, 11, 671.https://doi.org/10.1038/s41597-024-03508-5

Li, J., Zheng Z., Li, Y., Lyu, H., Ren, J., Cai, X., Du, C., Chen, N., Liu, G., Lei, S., Zhang, R. and Huang, C. (2024) A hybrid algorithm for estimating total nitrogen from a large eutrophic plateau lake using Orbita hyperspectral (OHS) satellite imagery. International Journal of Applied Earth Observation and Geoinformation, 131, 103971.https://doi.org/10.1016/j.jag.2024.103971

Chen, N.^*, Tsendbazar, N.-E., Requena Suarez, D., C. H. L. Silva-Junior Verbesselt, J. and Herold, M. (2024) Revealing the Spatial Variation in Biomass Uptake Rates of Brazil’s Secondary Forests. ISPRS Journal of Photogrammetry and Remote Sensing. 208, 233-244. https://doi.org/10.1016/j.isprsjprs.2023.12.013

Chen, N.^*, Tsendbazar, N.-E., Requena Suarez, D., Verbesselt, J. and Herold, M. (2023) Characterizing aboveground biomass and tree cover of regrowing forests in Brazil using multi-source remote sensing data. Remote Sensing in Ecology and Conservation. 9(4), 553 - 567.https://doi.org/10.1002/rse2.328

Zheng Z., Huang, C., Li, Y., Lyu, H., Huang, C., Chen, N., Liu, G., Guo, Y., Lei, S., Zhang, R., Li, J. (2023) A semi-analytical model to estimate Chlorophyll-a spatial-temporal patterns from Orbita Hyperspectral image in inland eutrophic waters. Science of The Total Environment, 904, 166785.https://doi.org/10.1016/j.scitotenv.2023.166785

Li J., Zheng, Z., Liu, J., Chen, N., Lei, S., Du, C., Xu, J., Li, Y., Zhang, R., Huang, C. (2023). Estimating Effects of Natural and Anthropogenic Activities on Trophic Level of Inland Water: Analysis of Poyang Lake Basin, China, with Landsat-8 Observations. Remote Sensing, 15(6), 1618.https://doi.org/10.3390/rs15061618

Ye, N., Morgenroth, J., Xu, C., Chen, N., (2021) Indigenous forest classification in New Zealand – a comparison of classifiers and sensor. International Journal of Applied Earth Observation and Geoinformation,102, 102395.https://doi.org/10.1016/j.jag.2021.102395

Chen, N.^*, Tsendbazar, N.-E., Hamunyela, E., Verbesselt, J. and Herold, M. (2021) Sub-annual tropical forest disturbance monitoring using harmonized Landsat and Sentinel-2 data. International Journal of Applied Earth Observation and Geoinformation, 102, 102386.https://doi.org/10.1016/j.jag.2021.102386

Chen, N.^* (2020) Mapping mangrove in Dongzhaigang, China using Sentinel-2 imagery. Journal of Applied Remote Sensing, 14(1), 014508.https://doi.org/10.1117/1.JRS.14.014508

Duan, Y., Chen, N., Chen, Y. (2019) A novel PolSAR image classification method based on optimal polarimetric features and contextual information. Canadian Journal of Remote Sensing, 45(6), 795 - 813.https://doi.org/10.1080/07038992.2019.1697222