https://scholar.google.com/citations?user=KjqUEb4AAAAJ&hl=en
https://www.researchgate.net/profile/Kaiguang-Zhao
https://github.com/zhaokg/
https://stats.stackexchange.com/users/346751/zhaokg
Research Statement
My research focuses on mapping, monitoring, modeling, and managing terrestrial environments across scales, especially in the context of global environmental changes. My research employs a combined toolset (e.g., geotechnology, spatial analysis, machine learning, biophysical & climate modeling, ecological modeling, Bayesian statistics, and eddy-covariance) to characterize the status and change in ecosystems, and examine biophysical and ecological responses of terrestrial ecosystems to disturbances and climate change. Example of my research questions include how much carbon forests store, where terrestrial ecosystems have been disturbed and why, how compositions of vegetation communities can be mapped over extensive areas from the air, how long-term vegetation activities have been driven by climate change, where and how forestry and land-use activities generate best climate regulation services, and how crop productivity may change in a warming or dry world? One of my particular emphases is to develop geospatial applications, using tools such as hyper spectral imaging, high-resolution imagery, hyper-temporal remote sensing, and lidar, to characterize ecosystem structure and functioning.
Prospective graduate students
I am looking for self-motivated individuals who want to pursue research in areas that generally align well with mine, especially those with quantitative and computational backgrounds who would like to apply such skills to address environmental issues related to either natural or human-dominated ecosystems. Although my current research is biased toward remote sensing, students without a remote sensing background are equally considered. Inquires for potential GRA opportunities are encouraged, together with a CV/resume, a list of previous coursework (or transcripts), and a brief research plan describing what research topics you like to pursue and how your background will fit my research program.
Education
Ph.D. in Forestry, Texas A&M University, 2008
M.S. in Geography, Beijing Normal University, 2004
B.S. in Physics, Beijing Normal University, 2001
Selected Publications
Hu, T., Zhang, X., Bohrer, G., Liu, Y., Zhou, Y., Martin, J., Li, Y. and Zhao, K., 2023. Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield. Agricultural and Forest Meteorology, 336, p.109458.
Hu, T., Li, Y., Zhang, X., Zhao, K., Dongarra, J., and Moler, C., 2023. Package Rbeast: Bayesian Change-Point Detection and Time Series Decomposition. (https://CRAN.R-project.org/package=Rbeast)
Li, Y., Liu, Y., Bohrer, G., Cai, Y., Wilson, A., Hu, T., Wang, Z. and Zhao, K., 2022. Impacts of forest loss on local climate across the conterminous United States: Evidence from satellite time-series observations. Science of the Total Environment, 802, p.149651.
Nickerson, S., Chen, G., Fearnside, P.M., Allan, C.J., Hu, T., de Carvalho, L.M. and Zhao, K., 2022. Forest loss is significantly higher near clustered small dams than single large dams per megawatt of hydroelectricity installed in the Brazilian Amazon. Environmental Research Letters, 17(8), p.084026.
Hu, T., Toman, E.M., Chen, G., Shao, G., Zhou, Y., Li, Y., Zhao, K. and Feng, Y., 2021. Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 176, pp.250-261.
Zone, P.P., Culman, S.W., Haden, V.R., Lindsey, L.E., Fulford, A.M. and Zhao, K., 2020. Do soil test levels and fertilization with phosphorus and potassium impact field crop tissue concentrations?. Agronomy Journal, 112(4), pp.3024-3036.
Liu, Z., Ma, F.Y., Hu, T.X., Zhao, K.G., Gao, T.P., Zhao, H.X. and Ning, T.Y., 2020. Using stable isotopes to quantify water uptake from different soil layers and water use efficiency of wheat under long-term tillage and straw return practices. Agricultural Water Management, 229, p.105933.
Salas, E.A.L., Subburayalu, S.K., Slater, B., Zhao, K., Bhattacharya, B., Tripathy, R., Das, A., Nigam, R., Dave, R. and Parekh, P., 2020. Mapping crop types in fragmented arable landscapes using AVIRIS-NG imagery and limited field data. International Journal of Image and Data Fusion, 11(1), pp.33-56. ( the 2022 Best Paper award)
Zhao, K., Ryu, Y., Hu, T., Garcia, M., Li, Y., Liu, Z., Londo, A. and Wang, C., 2019. How to better estimate leaf area index and leaf angle distribution from digital hemispherical photography? Switching to a binary nonlinear regression paradigm. Methods in Ecology and Evolution, 10(11), pp.1864-1874.
Zhao, K., Wulder, M.A., Hu, T., Bright, R., Wu, Q., Qin, H., Li, Y., Toman, E., Mallick, B., Zhang, X. and Brown, M., 2019. Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm. Remote sensing of Environment, 232, p.111181. (code available at https://github.com/zhaokg/Rbeast)
Zhao, K., Suarez, J.C., Garcia, M., Hu, T., Wang, C. and Londo, A., 2018. Utility of multitemporal lidar for forest and carbon monitoring: Tree growth, biomass dynamics, and carbon flux. Remote Sensing of Environment, 204, pp.883-897. (Most-Read Papers)
Bright, R.M., Davin, E., O’Halloran, T., Pongratz, J., Zhao, K. and Cescatti, A., 2017. Local temperature response to land cover and management change driven by non-radiative processes. Nature Climate Change, 7(4), pp.296-302.
Zhou, Y., Smith, S.J., Zhao, K., Imhoff, M., Thomson, A., Bond-Lamberty, B., Asrar, G.R., Zhang, X., He, C. and Elvidge, C.D., 2015. A global map of urban extent from nightlights. Environmental Research Letters, 10(5), p.054011.
