GOOGLE SCHOLAR; RESEARCHGATE
At total of ~25,000 citations at ~250 citations per paper
* Corresponding authors, † Students or postdocs under my supervision.
104. Yang*†, X., S. Qiu, K. Kroeger, Zhiliang Zhu, S. Covington, N. Murray, and Z. Zhu*, The accelerating loss and shifting dynamics of US tidal wetlands, Nature Communications, Accept. pdf
103. Li*, F. Q. Zhu, K. Yuan, … Z. Zhu, P. Raymond, P. Ciais, R. Jackson, The underappreciated importance of small wetlands in global methane emissions, Nature Climate Change, Accept. pdf
102. Li*†, T., Z. Wang, C. Kyba, K. Seto, Y. Yang, S. Qiu ,T. Kuester, M. Fragkias, X. Chen, T. Meyer, C. Rittenhouse, X. Tai, M. Cullerton, F. Hong, A. Grinstead, K. Song, J. Suh, X. Yang, V. Kalb, C. Deng, M. Román, and Z. Zhu*, Increasing Volatility in Human Nighttime Activity Revealed by Daily and High-Resolution Satellite Imagery, Nature, Accept. pdf
101. Cheng†, X., B. Tao, S. Qiu, Z. Zhu, Alex C.R., and W. Ren*, Long-term Changing Patterns of Field-scale Corn and Soybean Phenology in the US Midwest, Journal of Geophysical Research: Biogeosciences, 131 (1), e2025JG009028, 2026. pdf
100. Cullerton*†, M., Z. Zhu, S. Qiu, C.D. Rittenhouse, J. Suh, Back in time: A novel time series and deep learning framework for mapping solar installations, Science of Remote Sensing, 12, 100322, 2025. pdf
99. Roy*, D.P., M.A. Wulder, N. Gorelick, M. Hansen, S. Healey, P. Hostert, J. Huntington, V.C. Radeloff, T. Scambos, C. Schaaf, C.E. Woodcock, Z. Zhu, The next Landsat: Mission turning point?, Remote Sensing of Environment, 332, 115087, 2026. pdf
98. Zhou*, Q., C. Neigh, J. Ju, M. Wooten, Z. Zhu, T. Miura, P. Campbell, M. Sridhar, B. Baker, and R. Leite, Global Uncertainty Assessment of Vegetation Indices from NASA’s Harmonized Landsat and Sentinel-2 Project, Remote Sensing of Environment, 332, 115084, 2026. pdf
97. Chen*, D., D. Roy, Z. Zhu, et al., A Shared Sky: A Call for Open Global Access to China’s Earth Observation Data, Nature Geosciences, 2025. pdf
96. Z. Zhu* (Ed.), Volume 2: Remote Sensing Data Processing and Analysis Methodology, Comprehensive Remote Sensing (book), Elsevier, 2025. pdf
95. Kennedy*, R., Z. Zhu, Time Series Analysis of Remotely Sensed Data, Volume 2: Remote Sensing Data Processing and Analysis Methodology, Comprehensive Remote Sensing (book), Elsevier, 2025. pdf
94. Z. Zhu*, Overview, Volume 2: Remote Sensing Data Processing and Analysis Methodology, Comprehensive Remote Sensing (book), Elsevier, 2025. pdf
93. Song*†, K., Z. Zhu*, S. Qiu, P. Olofsson, C.S.R. Neigh, J. Ju, and Q. Zhou, TIF: A Time-series-based Image Fusion Algorithm, Remote Sensing of Environment, 331, 115035, 2025. pdf
92. Qiu*, S., Z. Zhu*, Natural land disturbances are worsening but humans are not off the hook, Nature Geosciences, 18, 947-948, 2025. pdf
91. Qiu*, S., Z. Zhu* et al., A shift from human-directed to wild-undirected land disturbances in the US (Featured Cover Paper), Nature Geosciences, 18, 989-996, 2025. pdf
90. Zhang*, H.K., G. Camps-Valls, S. Liang, D. Tuia, C. Pelletier, and Z. Zhu, 2025. Preface: Advancing deep learning for remote sensing time series data analysis. Remote Sensing of Environment, 322, p.114711. pdf
89. Song*, Y., D.W. Katz, Z. Zhu, C. Beaulieu, K. Zhu, Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series, Science of Remote Sensing, p.100205, 2025. pdf
88. Zhou, Z., G. Zhang*, J. Wang, Z. Zhu, R.L. Woolway, X. Han, F. Xu, J. Peng, A novel framework for accurate, automated and dynamic global lake mapping based on optical imagery, ISPRS Journal of Photogrammetry and Remote Sensing, 221, 280-298, 2025. pdf
87. Hong, F.†*, S.B. Hedges, Z. Yang, J.W. Suh, S. Qiu, J. Timyan, Z. Zhu, Decoding primary forest changes in Haiti and the Dominican Republic using Landsat time series, Remote Sensing of Environment, 318, 114590, 2025. pdf
86. Zhou, Q.*, C. Neigh, J. Ju, P. Dabney, B. Cook, Z. Zhu, C. Crawford, F. Gascon, P. Strobl, M. Sridhar, Towards Seamless Global 30-meter Terrestrial Monitoring: Evaluating 2022 Cloud Free Coverage of Harmonized Landsat and Sentinel-2 (HLS) v2.0, GIScience & Remote Sensing, 2025. pdf
85. Chen, C.*, L. Yang, X. Wang, X. Luo, Y. Li, Y. Cheng, Z. Zhu, Biophysical effects of croplands on land surface temperature, Nature Communications, 15, 10901, 2024. pdf
84. Yang, X.†*, Z. Zhu, K. Kroeger, S. Qiu, S. Covington, J.R. Conrad, Zhiliang Zhu., Tracking mangrove condition changes using dense Landsat time series, Remote Sensing of Environment, 315, 114461, 2024. pdf
83. Zhang, H.K.*, S. Qiu, J. Suh, D. Luo, Z. Zhu., Machine Learning and Deep Learning in Remote Sensing Data Analysis, Volume 2: Remote Sensing Data Processing and Analysis Methodology, Comprehensive Remote Sensing (book), Elsevier, 2024. pdf
82. Fu, Y.*, Z. Zhu, et al., Remote Sensing Time Series Analysis: A Review of Data and Applications, Journal of Remote Sensing, 4, 0285, 2024. pdf
81. Li, Y.*, M.A. Wulder, Z. Zhu, J. Verbesselt, D. Masiliūnas, Y. Liu, G. Bohrer, Y. Cai, Y. Zhou, Z. Ding, K. Zhao, Detecting breakpoints in multispectral time series – a multivariate algorithm, Remote Sensing of Environment, 315, 114402, 2024. pdf
80. Fu, Y.*, R. Li, Z. Zhu, X. Wang, H. Ding, B. Guo, and W. Xia, A new strategy for estimating carbon density based on the improved cascade random forest and Landsat time series, Remote Sensing of Environment, 314, 114348 2024. pdf
79. Suh, J.†*, Z. Zhu, and Y. Zhao, Monitoring construction changes using dense satellite time series and deep learning, Remote Sensing of Environment, 309, 114207, 2024. pdf
78. Worthley, T., A. Bunce, A.T. Morzillo, C. Witharana, Z. Zhu, …, and R.T. Fahey*, Stormwise: Innovative Forest Management to Promote Storm Resistance in Roadside Forests. Journal of Forestry, p.fvae011, 2024. pdf
77. Ye, S.†*, Z. Zhu, J. Suh, Leveraging past information and machine learning to accelerate land disturbance monitoring, Remote Sensing of Environment, 305, 114071, 2024. pdf
76. Radeloff*, V., …, and Z. Zhu, Need and vision for global medium-resolution Landsat and Sentinel-2 data products, Remote Sensing of Environment, 300, 113918, 2024. pdf
75. Stanimirova, R., K. Tarrio, K. Turlej, …, and Z. Zhu, A global land cover training dataset from 1984 to 2020, Scientific Data, 10, 2023. pdf
74. Thornton, P.E., B.C. Reed, G.Z. Xian, L. Chini, A.E. East, J.L. Field, C.M. Hoover, B. Poulter, S.C. Reed, G. Wang, and Z. Zhu, 2023: Ch. 6. Land cover and land-use change. In: Fifth National Climate Assessment. Crimmins, A.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, B.C. Stewart, and T.K. Maycock, Eds. U.S. Global Change Research Program, Washington, DC, USA. https://doi.org/10.7930/NCA5.2023.CH6, 2023. pdf
73. Crawford, C.J.*, Roy, D.P., Arab, S., Barnes, C., Vermote, E., Hulley, G., Gerace, A., Choate, M., Engebretson, C., Micijevic, E. and Schmidt, G., …, Z. Zhu, and S. Zahn, The 50-year Landsat Collection 2 Archive. Science of Remote Sensing, p.100103, 2023. pdf
72. Yang, X.†*, S. Qiu, Z. Zhu, C. Rittenhouse, D. Riordan, Mapping understory species in deciduous forests from Sentinel-2 time series, 293, 113601, Remote Sensing of Environment, 2023. pdf
71. Hu, J., A.E. Hartemink, A.R. Desai, P.A. Townsend, R.Z. Abramoff, Z. Zhu, D. Sihi, J. Huang, A Continental-Scale Estimate of Soil Organic Carbon Change At NEON Sites and 2 Their Environmental and Edaphic Controls, Journal of Geophysical Research Biogeosciences, 128, e2022JG006981, 2023. pdf
70. Jin, S.*, J. Dewitz, C. Li, D. Sorenson, Z. Zhu, R. Shogib, P. Danielson, B. Granneman, C. Costello, A. Case, L. Gass, National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance product, Journal of Remote Sensing, 2023. pdf
69. Ye, S.†*, Z. Zhu, and G. Cao, Object-based continuous monitoring of land disturbance, Remote Sensing of Environment, 2023. pdf
68. Tollerud, H.*, Z. Zhu, K. Smith, R. Hussain, D. Wellington, Towards consistent change detection with uneven availability of remote sensing input data: modification of the Continuous Change Detection and Classification, Remote Sensing of Environment, 285, 113372, 2023. pdf
67. Qiu, S.†*, Z. Zhu, P. Olofsson, C. Woodcock, and S. Jin, Evaluation of Landsat Image Compositing Algorithms for Landsat Imagery, Remote Sensing of Environment, 285, 113375, 2023. pdf
66. Jin, S.*, J. Dewitz, P. Danielson, B. Granneman, C. Costello, K. Smith, and Z. Zhu, National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images, Journal of Remote Sensing, 2023. pdf
65. Zhu, Z.*, S. Qiu*, and S. Ye*, Remote Sensing of Land Change: A Multifaceted Perspective, Remote Sensing of Environment, 282, 113266, 2022. pdf
64. Tian, L.†*, Z. Zhu, Z. Wang, M. Román, V. Kalb, and Y. Zhao, Continuous Monitoring of Nighttime Light Changes Based on Daily NASA’s Black Marble Product Suite, Remote Sensing of Environment, 282, 113269, 2022. pdf
63. Wulder, M.A.*, D.P. Roy, V.C. Radeloff; T.R. Loveland, M.C. Anderson, D.M. Johnson, S. Healey, Z. Zhu, T.A. Scambos, N. Pahlevan, M. Hansen, N. Gorelick, C.J. Crawford, J.G. Masek, T. Hermosilla, J.C. White, A.S. Belward, C. Schaaf, C. Woodcock, J.L. Huntington, L. Lymburner, P. Hostert, F. Gao, A. Lyapustin, J-F. Pekel, P. Strobl, and B.C. Cook, Fifty years of Landsat science and impacts, Remote Sensing of Environment, 280, 113195, 2022. pdf
62. Zhang, Y.*, C. Woodcock, P. Arévalo, P. Olofsson, X. Tang, R. Stanimirova, E.L. Bullock, K.R. Tarrio, Z. Zhu and M. Friedl, A global analysis of the spatial and temporal variability of usable Landsat observations at the pixel scale, Frontiers in Remote Sensing, 3, 894618, 2022. pdf
61. M.A. Friedl*, C. Woodcock, P. Olofsson, Z. Zhu, T.R. Loveland, R. Stanimirova, P.A. Arévalo, E. Bullock, K. Hu, Y. Zhang, K. Turlej, K. Tarrio, K. Mcavoy, N. Gorelick, J.A. Wang, C.P. Barber, and C.M. Souza, Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades from Landsat, Frontiers in Remote Sensing, 3, 894571, 2022. pdf
60. Zhou, Q.*, G. Xian, J. Horton, D. Wellington, G. Domke, R. Auch, C. Li, and Z. Zhu, CONUS Tree Regrowth Map from LCMAP Collection 1.0 Land Cover Products, GIScience & Remote Sensing, 59(1), 959-974, 2022. pdf
59. Auch, R.F., D.F. Wellington, J.L. Taylor, S.V. Stehman, H.J. Tollerud, J.F. Brown, T.R. Loveland, B.W. Pengra, J.A. Horton, Z. Zhu, and A.A. Midekisa, 2022. Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series, Land, 11(2), 298, 2022. pdf
58. Rittenhouse, C.D.*, E. Berlin, N. Mikle, S. Qiu, D. Riordan, and Z. Zhu, An Object-Based Approach to Map Young Forest and Shrubland Vegetation Based on Multi-Source Remote Sensing Data, Remote Sensing, 14(5), 1091, 2022. pdf
57. Aljaddani, A.†*, X. Song, and Z. Zhu, Characterizing the Patterns, Trends of Urban Growth in Saudi Arabia’s 13 Capital Cities Using Landsat Time Series, Remote Sensing, 14910, 2382, 2022. pdf
56. Shang, R.†*, Z. Zhu, J. Zhang, S. Qiu, Z. Yang, T. Li, and X. Yang, Near-real-time monitoring of land disturbance with harmonized Landsats 7-8 and Sentinel-2 data, Remote Sensing of Environment, 278, 113073, 2022. pdf
55. Yang, X.†*, Z. Zhu, S. Qiu, K. Kroeger, Z. Zhu, S. Covington, Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series, Remote Sensing of Environment, 276, 113047, 2022. pdf
54. Zhao, Y.†*, and Z. Zhu, ASI: An artificial surface index based on Landsat-8 imagery, International Journal of Applied Earth Observation and Geoinformation, 107, 102703, 2022. pdf
53. 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, 185, 48-61, 2022. pdf
52. 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, 14, 143-162, 2022. pdf
51. 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. pdf
50. 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. pdf
49. Molinier, M.*, J. Miettinen, D. Ienco, S. Qiu, and Z. 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. pdf
48. Ye, S.†*, J. Rogan, 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. pdf
47. Zhang, J.†, R. Shang†*, C. Rittenhouse, C. Witharana, Zhu*, Evaluating the impacts of models, data density and irregularity on reconstructing and forecasting dense Landsat time series. Science of Remote Sensing, 100023, 2021. pdf
46. Ye, S.*†, J. Rogan, 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. pdf
45. Tarrio, K.*, X. Tang, J.G. Masek, M. Claverie, J. Ju, S. Qiu, Zhu and C.E. Woodcock, Comparison of Cloud Detection Algorithms for Sentinel-2 Imagery. Science of Remote Sensing, 100010, 2020. pdf
44. Qiu, S.*†, 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. pdf
43. 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. pdf
42. Cohen, W.B.*, S.P. Healey, Z. Yang, Zhu, N. Gorelick, Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance, Remote Sensing, 12 (10), 1673, 2020. pdf
41. 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. pdf
40. Lin, Y. *†, 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. pdf
39. Berhane, T.M., C.R. Lane*, S. Mengistu, J. Christensen, H.E. Golden, S. Qiu, 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. pdf
38. Brown, J.F.*, H.J. Tollerud, C.P. Barber, Q. Zhou, J. Dwyer, J.E. Vogelmann, T. Loveland, C.E. Woodcock, S.V. Stehman, 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. pdf
37. 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. pdf
36. Deng, C.* & Zhu, Continuous subpixel monitoring of urban impervious surface using Landsat time series, Remote Sensing of Environment, 238, 110929, 2020. pdf
35. Jin, S.*, C. Homer, L. Yang, P. Danielson, J. Dewitz, C. Li, Zhu, G. Xian, Overall Methodology Design for the United States National Land Cover Database 2016 Products, Remote Sensing, 11 (24), 2971, 2019. pdf
34. Shang, R.*†, Zhu, Harmonizing Landsat 8 and Sentinel-2: A time-series-based reflectance adjustment approach, Remote Sensing of Environment, 235, 111439, 2019. pdf
33. Zhu, Z.*, Science of Landsat Analysis Ready Data, Remote Sensing, 11(18), 2166, 2019. pdf
32. Liu, C., X. Huang*, 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. pdf
31. Qiu, S.†, 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. pdf
30. 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. pdf
29. 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. pdf
28. 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 Zhu, Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225, 127-147, 2019. pdf
27. Qiu, S.†, Y. Lin, R. Shang*, J. Zhang, L. Ma, and Zhu*, 2019. Making Landsat Time Series Consistent: Evaluating and Improving Landsat Analysis Ready Data. Remote Sensing, 11(1), p.51, 2019. pdf
26. 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, pp. 3-24), Boca Raton, FL: CRC Press/Taylor & Francis, 2018. pdf
25. 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, & Zhu, Mapping forest change using stacked generalization: an ensemble approach, Remote Sensing of Environment, 204, 717-728, 2018. pdf
24. Deng, C.*, C. Li, & 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. pdf
23. Qiu, S.†, 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. pdf
22. 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. pdf
21. Jin, S.*, L. Yang, 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. pdf
20. Foga, S.*, P.L. Scaramuzza, S. Guo, 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. pdf
19. Xin, X., B. Liu*, K. Di, 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. pdf
18. 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, Zhu, How similar are forest disturbance maps derived from different Landsat time series algorithms? Forests, 8, 98, 2017. pdf
17. Zhu, Z.*, 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. pdf
16. Pengra, B.*, A.L. Gallant, 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. pdf
15. Schott, J.*, A. Gerace, C.E. Woodcock, S. Wang, 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. pdf
14. 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. pdf
13. Vogelmann, J.E.*, A.L. Gallant, S. Hua, & Zhu, Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data, Remote Sensing of Environment, 185, 258-270, 2016. pdf
12. Qin, Y., X. Xiao*, J. Dong, Y. Zhou, 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. pdf
11. 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. pdf
10. Zhu, Z.*, 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. pdf
9. 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. pdf
8. 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, & Zhu, Bringing an ecological view of change to Landsat-based remote sensing, Frontiers in Ecology and Environment, 12(6), 339-346, 2014. pdf
7. 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, & Zhu, Landsat-8: science and product vision for terrestrial global change research, Remote Sensing of Environment, 145, 154-172, 2014. pdf
6. Zhu, Z.* & E. Woodcock, Continuous change detection and classification of land cover using all available Landsat data, Remote Sensing of Environment, 144, 152-171, 2014. pdf
5. Xin, Q.*, 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. pdf
4. Melaas, E. K.*, 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. pdf
3. Zhu, Z.*, E. Woodcock, & P. Olofsson, Continuous monitoring of forest disturbance using all available Landsat imagery, Remote Sensing of Environment, 122, 75-91, 2012. pdf
2. Zhu, Z.*, & E. Woodcock, Object-based cloud and cloud shadow detection in Landsat imagery, Remote Sensing of Environment, 118(15), 83-94, 2012. pdf
1. Zhu, Z.*, 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. pdf