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Zhe Zhu
Assistant Professor
Department of Natural Resources & the Environment

University of Connecticut
U-4087, 1376 Storrs Road
Storrs, CT 06269-4087

Room: #321A
Phone: (860) 486-6885
Fax: (860) 486-5408

zhe@uconn.edu
GERS Laboratory Website
CV Download

Education

2013 Ph.D. in Geography Boston University
2001 B.E. in Remote Sensing and Photogrammetry Wuhan University
 

Professional Experience

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
 

Research Interests                                            

  • Remote Sensing, Particularly of Forests, Urban, and Clouds
  • Land Cover and Land Cover Change
  • Time Series Analysis
  • Digital Image Processing
  • Climate Change
 

Publications     

  • 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, In Press.
  • Zhu, Z*, J. Zhang, Z. Yang, A.H. Aljaddani, W.B. Cohen, S. Qiu, C. Zhou, et al., Continuous monitoring of land disturbance based on Landsat time series, Remote Sensing of Environment, In Press.
  • 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, In Press.
  • 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, In Press.
  • Deng, C.* & Z. Zhu, Continuous subpixel monitoring of urban impervious surface using Landsat time series, Remote Sensing of Environment, In Press.
  • 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 - First review of cloud and cloud shadow detection in Landsat data
  • 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, Evaluating the impacts of atmospheric correction, seasonality, environmental settings, and multi-temporal images on subpixel urban impervious surface area mapping with Landsat data, 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 - First review of change detection based on Landsat time series
  • 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 - Algorithm for USGS National Land Cover Database (NLCD) 2011 Alaska products
  • 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 - Adopted by USGS for Land Change Monitoring, Assessment, and Projection (LCMAP) initiative
  • 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 - Adopted by USGS for Land Change Monitoring, Assessment, and Projection (LCMAP) initiative
  • 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 - Implemented by USGS for operational cloud, cloud shadow, and snow detection in Landsat images
  • 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 Landsatbased 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 - Adopted by USGS for Land Change Monitoring, Assessment, and Projection (LCMAP) initiative
  • 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 - Implemented by USGS for operational cloud, cloud shadow, and snow detection in Landsat images
  • 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
Department of Natural Resources and the Environment
College of Agriculture and Natural Resources
University of Connecticut
1376 Storrs Road, Unit 4087
Storrs, Connecticut 06269-4087
Phone: 860-486-2840