Zhenhua Zou Education Professional Skills Research Grants Awards

CV, Zhenhua Zou, University of Maryland

Zhenhua Zou Assistant research professor Department of Geographical Sciences, University of Maryland Email: [email protected] Google scholar citations: https://scholar.google.com/citations?user=UDLq1x0AAAAJ&hl=en Phone: (405)-343-7335 Address: 2181 Samuel J. LeFrak Hall, 7251 Preinkert Drive, College Park, MD 20742 Education Assistant research professor (July 2021-Now): University of Maryland, Department of Geographical Sciences Postdoc (June 2019-June 2021): University of Maryland, Department of Geographical Sciences PhD. (May 2019): University of Oklahoma, major: Ecology and Evolutionary Biology. MEng. (July 2015): Beijing Normal University, major: Cartography & Geographic Information Engineering. BSc. (Aug. 2012): South China Normal University, major: Geographical Sciences.

Professional skills Programming: Python, IDL, MATLAB, Javascript and Python programming in the cloud computing platform of Google Earth Engine. Parallel processing in Linux servers Software: ArcGIS, ENVI, and SPSS. Field work instrument: FieldSpec-ASD, Spectroradiometer PSR 3500+, LAI - 2000/2200, Eddy covariance system (LI-7500, LI-7700), and Drone. Certificates: Unmanned aircraft pilot certificate, Chinese high school geography teacher certificate.

Research grants  Huang, C. (PI), Zhenhua Zou (Co-I), 2020-2022: Development of Enhanced NWI Mapping Protocols for the U.S., Funding agency: U.S. Fish and Wildlife Service. Award amount for University of Maryland: $76K.  Xiao, X. (PI), Zhenhua Zou (Co-I), 2018-2019: 2018 Student Research Project, Funding agency: USGS Oklahoma Water Resource Center. Award amount for University of Oklahoma: $5000.

Awards  Department distinguished publication award ($500, 2018).  First prize in poster contest of 2018 GIS Day at the University of Oklahoma ($200, 2018).  Robberson Conference Presentation & Creative Exhibition Travel Grant ($1000, 2018).

CV, Zhenhua Zou, University of Maryland

Review editor  Review editor for Frontiers  Guest editor for the special issue of Mapping and Change Analysis of Water and Wetland in MDPI journal Water

Mentor for students  Mentor for a master student, Jennifer Kraus, through her GOEG797 Capstone Project at Fall 2020, Department of Geographical Sciences, UMD.  Mentor for a master student, Anteneh Sarbanes, through his GOEG797 Capstone Project at Spring 2021, Department of Geographical Sciences, UMD.

Teaching experience  Teaching assistant for course Environmental Remote Sensing. Class lectures for Google Earth Engine data process programming using Javascript, University of Oklahoma (Spring 2018/2019).  Teaching assistant for course Environmental Remote Sensing. Lab lectures for Spectroradiometer PSR 3500+ and field lectures for FieldSpec-ASD, University of Oklahoma (Spring 2017).  Geography substitute teacher of Guangzhou No. 86 High School. Teaching geography in 6 classes, 12 lessons per week for a whole semester (Fall, 2011).

Research experience  NWI update targeting tool (1/2021-Now). Develop geospatial datasets for stakeholders to identity regions with the most wetland changes across the entire contiguous United States (CONUS). Identify the locations of such wetland change and assess wetland gain and loss through comparing NWI dataset with NLCD 2016 map and CCAP 10-m map The study find that urbanization is the biggest reason for loss of wetlands.

 Delaware open surface water detection and impervious layer extraction (6/2020-1/2021). Developed deep learning algorithms to extract water and impervious layer from very high-resolution (0.25m) aerial images across the entire Delaware. The deep learning algorithms can successfully extract water and impervious layer across various landscapes.

 Alaska ANWR wetland mapping and change analysis (7/2019-5/2020). Generated sub- pixel water fraction maps of ANWR at 10-m resolution using Sentinel-2 data. Analyzed water regimes and its seasonal dynamics. Classified vegetation types and analyzed shrub expansion over the last three decades. We found that June had maximum inundation while the least inundation was recorded in July. Riverbeds, edges of lakes and ponds, and wetlands in topographic depressions were more hydrologically dynamic, while pond centers were more stable. Compared with NWI data produced in the 1980s, scrub-shrub

CV, Zhenhua Zou, University of Maryland

wetlands appear to have increased from 91 km2 to 258 km2 over the last three decades, which is the largest percentage change (182%) among all vegetation types.

 Global water resource dynamics project (1/2018–3/2019). Generated 30-m global water body maps from 1984 to 2017 in Google Earth Engine using Javascript and Python programming languages (3.8 million images, 2.2 petabytes of data). Analyzed the dynamics of water body area and GRACE land water storage in high-performance computer using Python, GDAL, and parallel processing techniques in >300 CPUs. Analyzed the impacts of water resource long-term trends and extreme dynamics, especially droughts, floods, and sea level rise, to human society, natural environment, and global biodiversity. This project revealed the locations where water body area had significantly changed at 0.01° grid cells in the past three decades, interannual variations and multi-decadal trends of regional water body area at 5° tiles, and the consistent and divergent trends between water body area and land water storage at 5° tiles globally.

 Water quality estimation project (1/2019–5/2019). Tested existing algorithms of Chlorophyll a estimation in various Oklahoma lakes using Landsat and Sentinel images, and ~10,000 Chlorophyll-a field measurements. Try to find the best performing algorithms across Oklahoma lakes. Try to link the dynamics of Chlorophyll-a concentration to the changes of surface water bodies.

 Contiguous US water resource project (9/2016–3/2018). Mapped water body distribution for the CONUS during 1984-2016 and analyzed water body area variations and trends in the last three decades. Found dry regions in the Southwest and Northwest US were getting dryer while wet regions in the Southeast US and far north Great Plains were getting wetter due to change in precipitation and temperature. Also, the joint analysis of water body area and GRACE land water storage demonstrated that farmers switched from using surface water to groundwater in prolonged drought years and led to groundwater depletion (Published in PNAS).

 Oklahoma water body mapping project (9/2015–9/2016). Generated annual water body maps of Oklahoma during 1984-2015 in the spatial resolution of 30m. Based on this, the inter-annual variability of water body area and number and their potential influencing factors were analyzed. Continued decreasing trends of surface water resource was found because of changes in climatic factors (Published in Science of the Total Environment).

 Vegetation destruction and recovery project (2/2015–12/2015). Detected vegetation destruction pixels due to Sichuan 8.0 Ms earthquake using MODIS data. Based on the adjacent pixels with the same vegetation types and no destruction, the vegetation recovery of destructed pixels was assessed. (Presented in 2015 AGU meeting).

CV, Zhenhua Zou, University of Maryland

 Chinese forest biomass mapping project (5/2013–12/2013). My work includes MODIS forest area calibration with national forest inventory. A program was developed using MATLAB which found the best thresholds of forest area calibration (Published in Forests, third author).

Peer-review publications (3 as first author, a total of 26 articles, 729 citations in Google scholar https://scholar.google.com/citations?user=UDLq1x0AAAAJ&hl=en)  Zou, Z., C., Huang, B., DeVries, M., Lang, S. Thielke, G., McCarty, A., Robertson, J., Knopf, A., Wells, J., Ju, J., Masek, L., Du (2021), Characterizing Wetland Inundation and Vegetation Dynamics in the Arctic Coastal Plain Using Recent Satellite Data and Field Photos Remote Sensing, 13(8), p.1492.  Zou, Z., X. Xiao, J. Dong, Y. Qin, R. B. Doughty, M. A. Menarguez, G. Zhang, J. Wang. (2018), Divergent trends of open surface water body area in the contiguous US during 1984-2016, Proceedings of the National Academy of Sciences, 115, 3810-3815, https://doi.org/10.1073/pnas.1719275115.  Zou, Z., J. Dong, M. A. Menarguez, X. Xiao, Y. Qin, R. B. Doughty, K. V. Hooker, and K. David Hambright (2017), Continued decrease of open surface water body area in Oklahoma during 1984-2015, Sci Total Environ, 595, 451-460, doi: 10.1016/j.scitotenv.2017.03.259.  Wang, X., Xiao, X., Zou, Z., Dong, J., Qin, Y., Doughty, R.B., Menarguez, M.A., Chen, B., Wang, J., Ye, H. and Ma, J., 2020. Gainers and losers of surface and terrestrial water resources in China during 1989–2016. Nature Communications, 11(1), pp.1-12.  Wang, X., Xiao, X., Zou, Z., Hou, L., Qin, Y., Dong, J., Doughty, R.B., Chen, B., Zhang, X., Chen, Y. and Ma, J., 2020. Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 163, pp.312-326.  Wang, X., Xiao, X., Zou, Z., Chen, B., Ma, J., Dong, J., Doughty, R.B., Zhong, Q., Qin, Y., Dai, S. and Li, X., 2020. Tracking annual changes of coastal tidal flats in China during 1986–2016 through analyses of Landsat images with Google Earth Engine. Remote Sensing of Environment, 238, p.110987.  Du, L., McCarty, G.W., Li, X., Rabenhorst, M.C., Wang, Q., Lee, S., Hinson, A.L. and Zou, Z., 2021. Spatial extrapolation of topographic models for mapping soil organic carbon using local samples. Geoderma, 404, p.115290.  Xin, F., Xiao, X., Dong, J., Zhang, G., Zhang, Y., Wu, X., Li, X., Zou, Z., Ma, J., Du, G. and Doughty, R.B., 2020. Large increases of paddy rice area, gross primary production, and grain production in Northeast China during 2000–2017. Science of The Total Environment, 711, p.135183.  Du, L., McCarty, G.W., Zhang, X., Lang, M.W., Vanderhoof, M.K., Li, X., Huang, C., Lee, S. and Zou, Z., 2020. Mapping Forested Wetland Inundation in the Delmarva Peninsula, USA Using Deep Convolutional Neural Networks. Remote Sensing, 12(4), p.644.

CV, Zhenhua Zou, University of Maryland

 Zhou, Y., Dong, J., Xiao, X., Liu, R., Zou, Z., Zhao, G. and Ge, Q., 2019. Continuous monitoring of lake dynamics on the Mongolian Plateau using all available Landsat imagery and Google Earth Engine. Science of the Total Environment, 689, pp.366-380.  Chang, Q., Xiao, X., Jiao, W., Wu, X., Doughty, R., Wang, J., Du, L., Zou, Z. and Qin, Y., 2019. Assessing consistency of spring phenology of snow-covered forests as estimated by vegetation indices, gross primary production, and solar-induced chlorophyll fluorescence. Agricultural and Forest Meteorology, 275, pp.305-316.  Niu, Q., Xiao, X., Zhang, Y., Qin, Y., Dang, X., Wang, J., Zou, Z., Doughty, R.B., Brandt, M., Tong, X. and Horion, S., 2019. Ecological engineering projects increased vegetation cover, production, and biomass in semiarid and subhumid Northern China. Land Degradation & Development, 30(13), pp.1620-1631.  Qin, Y., Xiao, X., Dong, J., Zhang, Y., Wu, X., Shimabukuro, Y., Arai, E., Biradar, C., Wang, J., Zou, Z. and Liu, F., 2019. Improved estimates of forest cover and loss in the Brazilian Amazon in 2000–2017. Nature Sustainability, 2(8), pp.764-772.  Wang, X., Xiao, X., Zou, Z., Chen, B., Ma, J., Dong, J., Li, X. (2018). Tracking annual changes of coastal tidal flats in China during 1986–2016 through analyses of Landsat images with Google Earth Engine. Remote Sensing of Environment.  Du, L., Mikle, N., Zou, Z., Huang, Y., Shi, Z., Jiang, L. Luo, Y. (2018). Global patterns of extreme drought-induced loss in land primary production: Identifying ecological extremes from rain-use efficiency. Science of the Total Environment, 628, 611-620.  Wang, J., Xiao, X., Qin, Y., Doughty, R. B., Dong, J., & Zou, Z. (2018). Characterizing the encroachment of juniper forests into sub-humid and semi-arid prairies from 1984 to 2010 using PALSAR and Landsat data. Remote Sensing of Environment, 205, 166-179.  Xu, W., Y. Qin, X. Xiao, G. Di, R. Doughty, Y. Zhou, Z. Zou, L. Kong, Q. Niu, and W. Kou. "Quantifying spatial-temporal changes of tea plantations in complex landscapes through integrative analyses of optical and microwave imagery." International Journal of Applied Earth Observation and Geoinformation 73 (2018): 697-711.  Doughty, R., Xiao, X., Wu, X., Zhang, Y., Bajgain, R., Zhou, Y., Qin, Y., Zou, Z., McCarthy, H., Friedman, J., Wagle, P., Basara, J., & Steiner, J. (2018). Responses of gross primary production of grasslands and croplands under drought, pluvial, and irrigation conditions during 2010–2016, Oklahoma, USA. Agricultural Water Management, 204, 47- 59.  Qin Y., X. Xiao, J. Dong, Y. Zhou, J. Wang, R. B. Doughty, Y. Chen, Z. Zou, B. Moore. (2017) Annual dynamics of forest areas in South America during 2007–2010 at 50-m spatial resolution, Remote Sens Environ 201:73-87.  Zhou, Y., J. Dong, X. Xiao, T. Xiao, Z. Yang, G. Zhao, Z. Zou, and Y. Qin (2017), Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors, Water-Sui, 9(4), doi: 10.3390/w9040256.  Lin, Q., Z. Zou, L. Lin, and Y. Wang (2017), Combining spectral and morphometric properties of landslides for separating individual landslides based on object-oriented

CV, Zhenhua Zou, University of Maryland

method, paper presented at Workshop on World Landslide Forum, Springer.  Qin, Y., X. Xiao, J. Dong, K. Ewing, B. Hoagland, D. Hough, T. Fagin, Z. Zou, G. Geissler, G. Xian, T. Loveland (2016), Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery, Rem Sens, 8(11), doi: 10.3390/rs8110933.  Wang, Y., Zou, Z., & Li, J. (2015). Influencing factors of households disadvantaged in post- earthquake life recovery: a case study of the Wenchuan earthquake in China. Natural Hazards, 75(2), 1853-1869.  Du, L., T. Zhou, Z. Zou, X. Zhao, K. Huang, and H. Wu (2014), Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China, Forests, 5(6), 1267-1283, doi: 10.3390/f5061267.  Wang, Y., Li, J., Chen, H., & Zou, Z. (2014). The time process of post‐earthquake recovery: the Yao'an earthquake in China. Disasters, 38(4), 774-789.

Books Chapters

 Li M., Zou Z., Xu G., Shi P. (2015) Mapping Earthquake Risk of the World. In: Shi P., Kasperson R. (eds) World Atlas of Natural Disaster Risk. IHDP/Future Earth-Integrated Risk Governance Project Series. pp. 25-39. Springer, Berlin, Heidelberg

Workshops  Z. Zou, B. DeVries, C. Huang, Introduction to Google Earth Engine (GEE) Dynamic Surface Water Extent (DSWE), Workshops to scientists and researchers at Fish and Wildlife Service, Jun. 24, 2020.

Conference presentations  Zhenhua Zou, Xiangming Xiao, Jinwei Dong, Yuanwei Qing, Russell B. Doughty, Michael A. Menarguez, Geli Zhang, Jie Wang., Spatiotemporal Dynamics of Open Surface Water Body Area in the Contiguous United States (CONUS) from 1984 to 2016, 2018 AGU Fall Meeting Oral Presentation, Dec 14, 2018, Washington DC.  Zhenhua Zou, Xiangming Xiao, Trends of Open Surface Water Body Area and GRACE Land Water Storage in Southern Great Plains, GrazingCAP project annual meeting oral presentation, Aug 22, 2018, Stillwater, OK.  Zhenhua Zou, Xiangming Xiao, Jinwei Dong, Yuanwei Qin, Russell B. Doughty, Michael A. Menarguez, Geli Zhang, Jie Wang. Divergent trends of open surface water body area in CONUS during 1984–2016. EPSCoR project annual meeting poster presentation, Apr 24, 2018, OKC.  Zhenhua Zou, Xiangming Xiao, Michael A. Menarguez, Jinwei Dong, and Yuanwei Qin. Mapping inter-annual dynamics of open surface water bodies in Oklahoma from Landsat

CV, Zhenhua Zou, University of Maryland

images in 1984 to 2015 at 30-m spatial resolution. 2016 AGU Fall Meeting poster presentation, Dec 15, 2016, San Francisco, CA.

Referee for peer-review journals (21 in total)

 Fuqin Li , David L B Jupp, Thomas Schroeder, Stephen Sagar, Joshua Sixsmith, Passang Dorji, Assessing an atmospheric correction algorithm for satellite products over water surfaces using match-up sites Australian coastal waters, Remote Sensing, remotesensing- 1192642  Le Jiao, Yue Zhang, Tao Sun *, Wei Yang, Dongdong Shao, Peng Zhang, Qiang Liu, Spatial analysis as a tool for plant population conservation: a case study of Tamarix chinensis in the Yellow River Delta, China, Sustainability, sustainability-1258158  Xudong Guan, Chong Huang, Guangbei Lei, Juan Yang, Ainong Li, Remote sensing image classification with a graph-based pre-trained neighborhood spatial relationship, Sensors, sensors-1296472  Hao Chen; YunusAli Pulpadan; Sravanthi Nukapothula; Ram Avtar, Modelling Arctic Coastal Plain Lake Depths Using Machine Learning and Google Earth Engine, Physics and Chemistry of the Earth, JPCE-D-21-00039  Rebecca Naomi ter Borg, Jennie Barron, Quantification of water retention structures in agricultural landscapes in Gotland Län and Kalmar Län 2000-2020, Acta Agriculturae Scandinavica, SAGB-2021-0243  Kolli, Meena Kumari, Opp, Christian, Karthe, Daniel, Web-based Decision Support System for Managing the Food-Water-Soil-Ecosystem Nexus in the Kolleru Lake Freshwater Ecosystem using Google Earth Engine, Geo-spatial Information Science, TGSI-2021-0013  YoungSeok Hwang, Stephan Schlüter, Seong-Il Park, Jung-Sup Um, Comparative evaluation of mapping accuracy between UAV video versus photo mosaic for scattered urban photovoltaic panel, Remote Sensing, remotesensing-1261699  Gema Marco Dos Santos *, Jose Navarro Pedreño *, Ignacio Melendez-Pastor, Ignacio Gómez Lucas, Using Landsat images to determine water storing capacity in Mediterranean environments, Hydrology, hydrology-1235350  Iryna Dronova, Chippie Kislik, Zack Dinh, Maggi Kelly, A review of unoccupied aerial vehicle use in wetland applications: Emerging opportunities in approach, technology, and data, Drones, drones-1225629  R., Wang, L., Pan, W., Niu, R., Li, X., Zhao, X., Bian, H., Xiao, T., Chen, Long-Term Monitoring of Xiaolangdi Reservoir Surface Water spatiotemporal dynamics Using Google Earth Engine, Open Geosciences, OPENGEO-D-21-00093

CV, Zhenhua Zou, University of Maryland

 Santiago Peña-Luque, Sylvain Ferrant, Mauricio C.R. Cordeiro, Jean-Michel Martinez, Regional Sentinel-1&2 Multitemporal Water Surface Detection Accuracies, Evaluated at Reservoirs Level, Remote Sensing, remotesensing-1275776  Mahendra Bahadur Baniya, Takeshi Fujino, Rocky Talchabhadel, Saroj Karki, Arjun Baniya, K.C. Shivaram, Biswo Jha, Kali Gandaki Dam Downstream Hydro-ecological Environment Response in Central Himalaya, Nepal, Watershed Ecology and the Environment, WSEE-D-21-00003  Muhammad Jamal Nasir, Lawal Billa; Said Alam, Waqas Ahmad, Soil Erosion Susceptibility Assessment of river sub-watersheds using morphometric based compound factor approach and GIS techniques, Watershed Ecology and the Environment, WSEE-D- 21-00007  L., Kewei, E., Xu, High-accuracy continuous mapping of surface water dynamics using automatic update of training samples and temporal consistency modification based on Google Earth Engine: A case study from Huizhou, China, ISPRS, PHOTO-D-21-00287  H., Zhang, Multisource Evaluation of Satellite Indices for Inland Surface Water Mapping, Journal of Hydroinformatics, HYDRO-D-18-00091  T., Dube, C., Shoko, T., Bhaga, Satellite monitoring of surface water variability over time in the drought prone Western Cape Province, South Africa, Geo-spatial Information Science, TGSI-2020-0009  M., Caroline, S., Kampf, J., Hammond, C., Wilson, S., Anderson, Geologic, topographic and climatic controls on streamflow densities in semiarid catchments, Water, water- 1040461  H. Yue, Y. Liu, A Method of Delineating Open Water Bodies Based on Deeply Clear Water Extraction Index, IEEE Access, Access-2018-18851, reviewed in 2019  T. Long, Z. Zhang, G. He, W. Jiao, C. Tang, B. Wu, X. Zhang, G. Wang, R. Ying, 30m resolution Global Annual Burned Area Mapping based on Landsat images and Google Earth Engine, ISPRS, PHOTO-D-18-00407R1  X., Yang, Y., Chen, J., Wang, Dynamic monitoring of surface water extent using Sentinel-2 on Google Earth Engine, ISPRS, TRES-LET-2019-0494  D., Feng, C. Gleason, X. Yang, T. Pavelsky, Comparing discharge estimates in high-order Arctic rivers derived solely from optical CubeSat, Landsat, and Sentinel-2 data, Water Resources Research, Paper #2019WR025599

Signature Date 7/20/2021