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Associate Professor

Department of Natural Resources & the Environment

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Titles:

Associate Professor

Education:

2013 PhD in Geography, Boston University

2006 BE in Remote Sensing and Photogrammetry, Wuhan University

Appointments:

2023 - present Associate Professor (with tenure), Department of Natural Resources and the Environment, UConn

2023 - present Consultant, Bay Area Environmental Research Institute

2022 - 2023 Consultant, Wildfire.org

2019 - Present Assistant Professor, Department of Natural Resources & the Environment, Univeristy of Connecticut, CT

2016 - 2018 Assistant Professor, Department of Geosciences, Texas Tech University, Lubbock, TX

2016 - 2018 Faculty Associate, Climate Science Center, Texas Tech University, Lubbock, TX

2016 - 2018 Faculty Associate, Center for Geospatial Technology, Texas Tech University, Lubbock, TX

2014 - 2016 Land Change Scientist, Contractor to USGS EROS, Sioux Falls, SD

2013 - 2014 Post-doctoral Associate, Department of Earth and Environment, Boston University, Boston, MA

Professional Activities:

2023 - Member, NASA Carbon Monitoring System (CMS) Science Team

2022.09 - Volume Editor, Remote Sensing Data Processing and Analysis Methodology, Comprehensive Remote Sensing (Book), Second Edition, Elsevier.

2022.08 - Guest Editor, Remote Sensing of Environment, Special Issue

2022.08 - Interim Editor in Chief, Remote Sensing of Environment

2022.07 - Editorial Board, Journal of Geodesy and Geoinformation Science

2022 - Associate Editor, Journal of Remote Sensing

2022 - Guest Editor, Journal of Remote Sensing, Special Issue

2021 - Member, NASA Black Marble Science Team

2021 - Timeseries Application Session Chair, ARD21 Satellite Data Interoperability Workshop

2021 - Author, Fifth National Climate Assessment (NCAS)

2021 - Founding Director, CATALYST and UConn Center of Excellence

2019 - Founding Director, Global Environmental Remote Sensing Laboratory

2019 - Associate Editor, Science of Remote Sensing

2019 - Editorial Board, Remote Sensing

2018-2023 Member, USGS-NASA Landsat Science Team

2018 - Associate Editor, Remote Sensing of Environment

2018-2021 Member, Science Interface Panel, USGS EROS CalVal Center of Excellence

2017 - Editorial Board, PeerJ

2014 - Member, American Geographical Union

2019-2020 Guest Editor, Remote Sensing, Special Issue

2018-2021 Chair, American Geographical Union (AGU), San Francisco and New Orleans

2018 Chair and Organizer, Annual Meeting of Association of American Geographers, New Orleans

2017-2018 Guest Editor, Remote Sensing, Special Issue

2017-2018 Guest Editor, Forests, Special Issue

2017-2018 Associate Editor, Arabian Journal of Geosciences

2017 Chair and Organizer, Annual Meeting of Association of American Geographers, Boston

2014-2019 Member, Association of American Geographers

Awards:

2020-2023 Web of Science Highly Cited Researchers

2021 AAUP Excellence Awards - Excellence in Research & Creativity: Early Career

2016 Outstanding Contribution in Reviewing Remote Sensing of Environment

2007-2008 Presidential University Graduate Fellowships, Boston University, Boston

Research Interests:

Remote Sensing; Global Environmental Change, Land Cover and Land Use Change; Disaster and Hazard Monitoring; Time Series Analysis; Machine Learning; Biodiversity Conservation; Climate Change

Publications:

* corresponding authors, † students or postdocs under my supervision (or co-supervision)

• Zhao, Y.†*, andZ. Zhu, ASI: An artificial surface index based on Landsat-8 imagery, International Journal of Applied Earth Observation and Geoinformation, 2022
• Zhou, Q.*,Z. Zhu, G. Xian, and C. Li, A novel regression method for harmonic analysis of time series, ISRPS Journal of Photogrammetry and Remote Sensing, 2022
• Xian, G.*, K. Smith, D. Wellington, J. Horton, Q. Zhou, C. Li, R. Auch, J. Brown,Z. Zhu, and R. Reker, Implementation of CCDC to produce the LCMAP Collection 1.0 annual land surface change product, Earth Syst. Sci. Data, 2022
• Wang, J., D. Yang, S. Chen, X. Zhu, S. Wu, M. Bogonovich, Z. Guo, Z. Zhu,. and J. Wu, Automatic cloud and cloud shadow detection in tropical areas for PlanetScope satellite images. Remote Sensing of Environment, 264, p.112604, 2021
• Qiu, S.†, Z. Zhu*, R. Shang, and C. J. Crawford, Can Landsat 7 preserve its science capability with a drifting orbit? Science of Remote Sensing, 100026, 2021
• Molinier, M.*, J. Miettinen, D. Ienco, S. Qiu, andZ. Zhu, Optical Satellite Image Time-Series Analysis for Environment Applications: From Classical Methods to Deep Learning and Beyond, In Bovolo, F (Ed.):Change detection and image time-series analysis (Chapter 4), ISTE-Wiley Encyclopedia of Science. 2021
• Ye, S.†*, J. Rogan, Z. Zhu, T.J. Hawbaker, S.J. Hart, R.A. Andrus, A.J.H. Meddens, J.A. Hicke, J.R. Eastman, D. Kulakowski, Detecting subtle change from dense Landsat time series: Case studies of mountain pine beetle and spruce beetle disturbance, Remote Sensing of Environment, 263, 112560, 2021
• Zhang, J.†, R. Shang†*, C. Rittenhouse, C. Witharana, Z. Zhu*, Evaluating the impacts of models, data density and irregularity on reconstructing and forecasting dense Landsat time series. Science of Remote Sensing, 100023, 2021
• Ye, S.*†, J. Rogan, Z. Zhu. and J.R. Eastman, A near-real-time approach for monitoring forest disturbance using Landsat time series: stochastic continuous change detection. Remote Sensing of Environment, 112167, 2020
• Tarrio, K.*, X. Tang, J.G. Masek, M. Claverie, J. Ju, S. Qiu, Z. Zhu and C.E. Woodcock, Comparison of Cloud Detection Algorithms for Sentinel-2 Imagery. Science of Remote Sensing, 100010, 2020
• Qiu, S.*†, Z. Zhu, and C.E. Woodcock, Cirrus clouds that adversely affect Landsat 8 images: What are they and how to detect them?, Remote Sensing of Environment, 246, 111884, 2020
• Zhu, Z.*, J. Zhang, Z. Yang, A.H. Aljaddani, W.B. Cohen, S. Qiu, C. Zhou, Corrigendum to continuous monitoring of land disturbance based on Landsat time series, Remote Sensing of Environment, 238, 111824, 2020
• Cohen, W.B.*, S.P. Healey, Z. Yang, Z. Zhu, N. Gorelick, Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance, Remote Sensing, 12 (10), 1673, 2020
• Yang, X. *†, Q Qin, H Yésou, T Ledauphin, M Koehl, P Grussenmeyer, Z Zhu, Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data, Remote Sensing of Environment, 244, 111803, 2020
• Lin, Y. *†, Z. Zhu*, W. Guo, Y. Sun, X. Yang, V. Kovalskyy, Continuous monitoring of cotton stem water potential using Sentinel-2 imagery, Remote Sensing, 12 (7), 1176, 2020
• Berhane, T.M., C.R. Lane*, S. Mengistu, J. Christensen, H.E. Golden, S. Qiu, Z. Zhu and Q. Wu, Land-Cover Changes to Surface-Water Buffers in the Midwestern USA: 25 Years of Landsat Data Analyses (1993-2017), Remote Sensing, 12(5), 754, 2020
• Brown, J.F.*, H.J. Tollerud, C.P. Barber, Q. Zhou, J. Dwyer, J.E. Vogelmann, T. Loveland, C.E. Woodcock, S.V. Stehman, Z. Zhu, B. Pengra, K. Smith, J. Horton, G. Xian, R. Auch, T. Sohl, K. Sayler, A. Gallant, D. Zelenak, R. Reker, J. Rover. Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Project (LCMAP) approach, Remote Sensing of Environment, 238, 111356, 2020
• Zhu, Z.*, J. Zhang, Z. Yang, A.H. Aljaddani, W.B. Cohen, S. Qiu, C. Zhou, Continuous monitoring of land disturbance based on Landsat time series, Remote Sensing of Environment, 238, 111116, 2020
• Deng, C.* & Z. Zhu, Continuous subpixel monitoring of urban impervious surface using Landsat time series, Remote Sensing of Environment, 238, 110929, 2020
• Jin, S.*, C. Homer, L. Yang, P. Danielson, J. Dewitz, C. Li, Z. Zhu, G. Xian, Overall Methodology Design for the United States National Land Cover Database 2016 Products, Remote Sensing, 11 (24), 2971, 2019
• Shang, R.*†, Z. Zhu, Harmonizing Landsat 8 and Sentinel-2: A time-series-based reflectance adjustment approach, Remote Sensing of Environment, 235, 111439, 2019
• Zhu, Z.*, Science of Landsat Analysis Ready Data, Remote Sensing, 11(18), 2166, 2019
• Liu, C., X. Huang*, Z. Zhu, H. Chen, X. Tang, J. Gong, Automatic extraction of built-up are from ZY3 multi-view satellite imagery: Analysis of 45 global cities, Remote Sensing of Environment, 226, 51-73, 2019
• Qiu, S.†, Z. Zhu*, and B. He*, Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4-8 and Sentinel-2 imagery, Remote Sensing of Environment, 231, 111205, 2019
• Zhu, Z.*, Y Zhou, KC Seto, EC Stokes, C Deng, STA Pickett, H Taubenböck, Understanding an urbanizing planet: Strategic directions for remote sensing, Remote Sensing of Environment, 228, 164-182, 2019
• Zhu, Z*, M.A. Wulder, D.P. Roy, C.E. Woodcock, M.C. Hansen, V.C. Radeloff, S.P. Healey, C. Schaaf, P. Hostert, P. Strobl, J. Pekel, L. Lymburner, N. Pahlevan, T.A. Scambos, Benefits of the free and open Landsat data policy, Remote Sensing of Environment, 224, 382-385, 2019
• Wulder, M.A.*, T.R. Loveland, D.P. Roy, C.J. Crawford, J.G. Masek, C.E. Woodcock, R.G. Allen, M.C. Anderson, A.S. Belward, W.B. Cohen, J. Dwyer, A. Erb, F. Gao, P. Griffiths, D. Helder, T. Hermosilla, J.D. Hipple, P. Hostert, M.J. Hughes, J. Huntington, D.M. Johnson, R. Kennedy, A. Kilic, Z. Li, L. Lymburner, J. McCorkel, N. Pahlevan, T.A. Scambos, C. Schaaf, J.R. Schott, Y. Sheng, J. Storey, E. Vermote, J. Vogelmann, J.C. White, R.H. Wynne, and Z. Zhu, Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225, 127-147, 2019
• Qiu, S.†, Y. Lin, R. Shang*, J. Zhang, L. Ma, and Z. Zhu*, 2019. Making Landsat Time Series Consistent: Evaluating and Improving Landsat Analysis Ready Data. Remote Sensing, 11(1), p.51, 2019
• Zhu, Z.*, S. Qiu, B. He, C. Deng, Cloud and cloud shadow detection for Landsat images: the fundamental basis for analyzing Landsat time series, In Weng, Q. (Ed.): Remote Sensing Time Series Image Processing (1st ed., pp. 3-24), Boca Raton, FL: CRC Press/Taylor & Francis, 2018
• Healey, S.P.*, W.B Cohen, Z. Yang, C.K. Brewer, E.B. Brooks, N. Gorelick, A. Hernandez, C. Huang, M.J. Hughes, R.E. Kennedy, T.R. Loveland, G.G. Moisen, T.A. Schroeder, S.V. Stehman, J.E. Vogelmann, C.E. Woodcock, L. Yang, & Z. Zhu, Mapping forest change using stacked generalization: an ensemble approach, Remote Sensing of Environment, 204, 717-728, 2018
• Deng, C.*, C. Li, & Z. Zhu, W. Lin, & L. Xi, Subpixel urban impervious surface mapping: The impact of input Landsat images, ISPRS Journal of Photogrammetry and Remote Sensing, 133, 89-103, 2017
• Qiu, S.†, B. He*, Z. Zhu*, Z. Liao, & X. Quan, Improving Fmask cloud and cloud shadow detection in mountainous area for Landsat 4-8 images. Remote Sensing of Environment, 199, 107-119, 2017
• Zhu, Z.*, Change detection using Landsat time series: a review of frequencies, preprocessing, algorithms, and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 370-384, 2017
• Jin, S.*, L. Yang, Z. Zhu, & C. Homer, A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011, Remote Sensing of Environment, 195, 44-55, 2017
• Foga, S.*, P.L. Scaramuzza, S. Guo, Z. Zhu, R.D. Dilley, T. Beckman, G.L. Schmidt, J.L. Dwyer, M.J. Hughes, B. Laue, Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sensing of Environment, 194, 379-390, 2017
• Xin, X., B. Liu*, K. Di, Z. Zhu, Z. Zhao, J. Liu, Z. Yue, G. Zhang, Monitoring urban expansion using time series of night-time light data: a case study in Wuhan, China, International Journal of Remote Sensing, 1-19, 2017
• Cohen, W.B.*, S.P. Healey, Z. Yang, S.V. Stehman, C.K. Brewer, E.B. Brooks, N. Gorelick, C. Huang, M.J. Hughes, R.E. Kennedy, T.R. Loveland, G.G. Moisen, T.A. Schroeder, J.E. Vogelmann, C.E. Woodcock, L. Yang, Z. Zhu, How similar are forest disturbance maps derived from different Landsat time series algorithms? Forests, 8, 98, 2017
• Zhu, Z.*, A.L. Gallant, C.E. Woodcock, B. Pengra, P. Olofsson, T.R. Loveland, S. Jin, D. Dahal, L. Yang, & R.F. Auch, Optimizing the strategy for operational land cover classification for the LCMAP initiative: the effect of training and auxiliary data, ISPRS Journal of Photogrammetry and Remote Sensing, 122, 206-221, 2016
• Pengra, B.*, A.L. Gallant, Z. Zhu, & D. Dahal, Evaluation of the Initial Thematic Output from a Continuous Change-Detection Algorithm for Use in Automated Operational Land-Change Mapping by the US Geological Survey, Remote Sensing, 8(10), 811, 2016
• Schott, J.*, A. Gerace, C.E. Woodcock, S. Wang, Z. Zhu, & R.H. Wynne, C.E. Blinn, The impact of improved signal to noise ratios on algorithm performance: Case studies for Landsat class instruments, Remote Sensing of Environment, 185, 37-45, 2016
• Zhu, Z.*, Y. Fu*, C.E. Woodcock, J.E. Vogelmann, P. Olofsson, C. Holden, M. Wang, S. Dai, & Y. Yu, Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000-2014), Remote Sensing of Environment, 185, 243-257, 2016
• Vogelmann, J.E.*, A.L. Gallant, S. Hua, & Z. Zhu, Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data, Remote Sensing of Environment, 185, 258-270, 2016
• Qin, Y., X. Xiao*, J. Dong, Y. Zhou, Z. Zhu, G. Zhang, G. Du, C. Jin, W. Kou, J. Wang, & X. Li, Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery, ISPRS Journal of Photogrammetry and Remote Sensing, 105, 220-233, 2015
• Zhu, Z.*, C.E. Woodcock, C. Holden, & Z. Yang, Generating synthetic Landsat images based on all available Landsat data: predicting Landsat surface reflectance at any given time, Remote Sensing of Environment, 162, 67-83, 2015
• Zhu, Z.*, S. Wang, & C.E. Woodcock, Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images, Remote Sensing of Environment, 159, 269-277, 2015
• Zhu, Z.* & C.E. Woodcock, Automated cloud, cloud shadow, and snow detection based on multitemporal Landsat data: an algorithm designed specifically for monitoring land cover change, Remote Sensing of Environment, 152, 217-234, 2014
• Kennedy, R.*, S. Andréfouët, W. Cohen, C. Gómez, P. Griffiths, M. Hais, S. Healey, E. Helmer, P. Hostert, M. Lyons, G. Meigs, D. Pflugmacher, S. Phinn, S. Powell, P. Scarth, S. Sen, T. Schroeder, A. Schneider, R. Sonnenschein, J.E. Vogelmann, M. Wulder, & Z. Zhu, Bringing an ecological view of change to Landsat-based remote sensing, Frontiers in Ecology and Environment, 12(6), 339-346, 2014
• Roy, D.P.*, M.A. Wulder, T.R. Loveland, C.E. Woodcock, R.G. Allen, M.C. Anderson, D. Helder, J.R. Irons, D.M. Johnson, R. Kennedy, T.A. Scambos, C.B. Schaaf, J.R. Schott, Y. Sheng, E.F. Vermote, A.S. Belward, R. Bindschadler, W.B. Cohen, F. Gao, J.D. Hipple, P. Hostert, J. Huntington, C.O. Justice, A. Kilic, V. Kovalskyy, P.Z. Lee, L. Lymburner, J.G. Masek, J. McCorkel, Y. Shuai, R. Trezza, J. Vogelmann, R.H. Wynne, & Z. Zhu, Landsat-8: science and product vision for terrestrial global change research, Remote Sensing of Environment, 145, 154-172, 2014
• Zhu, Z.* & C.E. Woodcock, Continuous change detection and classification of land cover using all available Landsat data, Remote Sensing of Environment, 144, 152-171, 2014
• Xin, Q.*, P. Olofsson, Z. Zhu, B. Tan, & C.E. Woodcock, Towards near real-time monitoring of forest disturbance by fusion of MODIS and Landsat data, Remote Sensing of Environment, 135, 234-247, 2013
• Melaas, E. K.*, M.A. Friedl, & Z. Zhu, Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM+ data, Remote Sensing of Environment, 132, 176-185, 2013
• Zhu, Z.*, C.E. Woodcock, & P. Olofsson, Continuous monitoring of forest disturbance using all available Landsat imagery, Remote Sensing of Environment, 122, 75-91, 2012
• Zhu, Z.*, & C.E. Woodcock, Object-based cloud and cloud shadow detection in Landsat imagery, Remote Sensing of Environment, 118(15), 83-94, 2012
• Zhu, Z.*, C.E. Woodcock, J. Rogan, & J. Kellndorfer, Assessment of spectral, polarimetric, temporal, and spatial dimensions for urban and peri-urban land cover classification using Landsat and SAR data, Remote Sensing of Environment, 117(15), 72-82, 2012