Xiaoyang Zhang

Education

Ph.D. Department of Geography, King's College London, University of London, London, 02/1995-05/1999.

M.Sc. Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 09/1988-08/1991.

B.Sc. Department of Geography, Peking University, Beijing, 09/1980-07/1984.

Academic Interests

Research interests include the developments of remote sensing algorithms and global products for investigating biomass burning emissions, land surface phenology, land cover and land use change, and climate-terrestrial ecosystem interaction.

Academic Responsibilities

80% research, 10% service, 10% teaching

Current courses taught:
• GEOG 484-484L/584-584L Remote Sensing
• GEOG 485-485L/585-585L Quantitative Remote Sensing
• GSE/GEOG 760–S01 Advanced Methods in Geospatial Modeling: Computation for Remote Sensing Analysis and Product Generation
• GSE 898D Dissertation Course
• GSE 790 Geospatial Science and Engineering Seminar Course

Awards and Honors

Media Coverage of Research
• 05/24/2018: Interviewed by Research Writer in South Dakota State University
(http://www.newswise.com/articles/satellite-sensors-track-spring-greenup%2C-fall-leaf-off;
https://www.sdstate.edu/news/2018/05/satellite-sensors-track-spring-greenup-growing-season)
• 05/03/2018: featured news article (https://sciencetrends.com/comparing-viirs-and-phenocam-land-surface-phrenology/)
• 06/01/2017: Interviewed by Research Writer in South Dakota State University
(https://www.sdstatefoundation.org/news/satellite-sensors-track-spring-greenup-growing-season)
• 07/26/2017: Interviewed by EnvironmentalResearchWeb Newswire (http://environmentalresearchweb.org/cws/article/news/69988)
• 06/05/2017: Interviewed by EnvironmentalResearchWeb Newswire (http://environmentalresearchweb.org/cws/article/news/68993)
• 09/03/2015: Interviewed by The Philadelphia Inquirer
• 11/2014: Interviewed by Research Writer in SDSU and widely reported by new media including United Nation, NOAA, ScienceNews, Livescience, and SDSU.
• 12/2014: Featured news article in Cooperative Institute for Climate & Satellites-Maryland Earth System Science Interdisciplinary Center, University Maryland
• 5/2010: Interviewed by EnvironmentalResearchWeb Newswire.
• 2/2008: Interviewed by the Associated Press.
• 11/2007: Interviewed by media including New Scientist Magazine, Wired Magazine, Natural History Magazine, and LiveScience, separately.
• 7/2004 Interviewed by media: Science News (newsmagazine), NASA press release, The Atlanta Journal-Constitution, and The Republican, separately.

Grants

(1) Pending Projects
•

(2) Current projects
. Enhancement of RAVE emissions algorithm and transition to operations, NOAA, 10/2022-6/2024, $235,405, PI F. Li (SDSU), CoI X. Zhang (SDSU)
. Fire Emissions Reprocessing Activities, NOAA, 10/2022-6/2024, $188,324, PI X. Zhang (SDSU), CoI F. Li (SDSU)
• Maintenance, Evolution, and Validation of the Global Land Surface Phenology Product from Suomi NPP and JPSS VIIRS Observations, NASA, 10/2021-9/2024, $664,845, PI: X. Zhang (SDSU)
• Investigation of PlanetScope Time Series Observations for Detecting Land Surface Phenology in the Semiarid Western United States, NASA, 01/2022-06/2023, $198,495, PI: X. Zhang (SDSU)
• Near real-time wildfire smoke detection and monitoring from satellite imagery using artificial intelligence, South Dakota NASA EPSCoR RIG Program, 10/2020 –9/2022, $75,000, PI at SDSU: X. Zhang, Project PI: Shankarachary Ragi (South Dakota School of Mines & Technology)
• Development of Near Real-Time Land Surface Phenology Product by Fusing Geostationary Satellite and VIIRS Observations in Support of Agriculture and Land Management, NASA, 08/2020-07/2023, $521,777, PI: X. Zhang (SDSU), CoIs: G. Gray (NCSU) and H. Zhang (SDSU)
• WF-3 Development and readiness of satellite products for fire and smoke forecasting -- A Unified Multi-Scale Biomass Burning Emissions Product, NOAA, 05/2020-04/2023, $310,000, PI: X. Zhang (SDSU)
• Global Biomass Burning Emissions Product -Maintenance and Refinement, NOAA, 08/2020-07/2021, $35,203, PI at SDSU: X. Zhang (SDSU), Project PI: Fernando Miralles-Wilhelm (UMD- CISESS).
• Effectiveness and monitoring of large-scale carbon-loss mitigation activities in Indonesia’s peatlands, NASA, 01/2020-12/2022, $1,442,946, PI at SDSU: X. Zhang, Project PI: Mark A. Cochrane (UMCES), other Co-I: Keith Eshleman.
• Developing a new geospatial tool for USDA NASS monitoring of near real time crop progress and condition by fusing observations from both polar-orbiting and geostationary satellites. USDA, 06/2019-5/2023, $474K, PI: X. Zhang (SDSU), CoIs: E. Byamukama (SDSU), Z. Yang (USDA).
• Maintenance and Refinement of a Global Land Surface Phenology Product from NPP VIIRS for EOS-MODIS Continuity. NASA, 04/2018-03/2022, $692K, PI: X. Zhang (SDSU), CoIs: G. Henebry (SDSU) and L. Liu (SDSU).
• Filling A Critical Gap in Indonesia's National Carbon Monitoring, Reporting, and Verification Capabilities for Supporting REDD+ Activities: Incorporating, Quantifying and Locating Fire Emissions from Within Tropical Peat-Swamp Forests. NASA, 07/2017-12/2021, $1,497K, PI at SDSU: X. Zhang, Project PI: Mark Cochrane (UMD Appalachian Laboratory).

(3) Completed projects
• Global Biomass Burning Emissions (GBBEP) Product and JPSS-1 Blended Biomass Burning. NOAA, 07/01/2016-06/30/2020, $230K. PI: X. Zhang (SDSU).
• Investigation of GOES-16 Active Wildfire Detections and FRP Measurement for Estimating Biomass Burning Emissions. NOAA/IMSG, 12/1/2018-9/30/2019, $95K, PI: X. Zhang (SDSU).
• A Multi-Scale Satellite-Based Indicator of Climate Change Impacts on Land-Surface Phenology. NASA, 07/2016-06/2019, $434K, PI at SDSU: X. Zhang, Project PI: J. Gray (NCSU), NASA.
• Development and Validation of a Global Land Surface Phenology Product from NPP VIIRS for EOS-MODIS Continuity. NASA, 11/2014-12/2018, $685K, PI: X. Zhang (SDSU), CoIs: G. Henebry (SDSU) and M.A. Friedl (BU).
• Global Biomass Burning Emissions (GBBEP) Product (BG-133E-15-SE-1613). NOAA, 09/11/2015-03/31/2017, $80K. PI: X. Zhang (SDSU).
• Suomi NPP VIIRS BRDF/Albedo/NBAR Products to Extend the Long Term Consistent MODIS Standard Data Record. NASA, 08/2014-07/2017, $592K, PI at SDSU: X. Zhang, Project PI: C.B. Schaaf (UMass-Boston).
• Monitoring land surface vegetation phenology from VIIRS. NOAA JPSS Risk Reduction Programs, 07/2013-06/2016, $380K, PI at SDSU: X. Zhang, Project Administrative PI at NOAA: Y. Yu.
• Real-Time Monitoring and Short-term Forecasting of Phenology from GOES-R ABI for the Use in Numerical Weather Prediction Models. NOAA, 07/2014-06/2017, $346K, PI at SDSU: X. Zhang (SDSU), Project Administrative PI at NOAA: Y. Yu.
• Change in our MIDST: Detection and Analysis of Land Surface Dynamics in North and South America Using Multiple Sensor Data streams. NASA, 07/01/2014-06/30/2018, $1.1M, G. Henebry (PI), X. Zhang (Co-I), K. M. de Beurs (Co-I).
• Develop Near Real Time Biomass Burning Emissions Product Covering the Whole Globe from Polar and Geostationary Satellites for NEMS-GFS-GOCART. NASA-NOAA Joint Center for Satellite Data Assimilation, 08/2011-6/2014, $610K, PI at SDSU: X. Zhang, Project Administrative PI at NOAA: S. Kondragunta.
• Vegetation phenology and enhanced vegetation index products from multiple long term satellite data records. NASA, 08/01/08-07/31/13, $3,441,131, PI at ERT/NOAA: X. Zhang, Project PI: K. Didan (UA).
• Biomass Burning Emissions Product from GOES-R ABI. NOAA Contract No. /Task No. DG133R-07-NC-1616, Mod 12/8407-003, 8/2011-7/2012, $53,000, X. Zhang (task leader), S. Kondragunta (task monitor).
• Global Biomass Burning Emissions Product (GBBEP) from a Constellation of Geostationary Satellites for Operational Use in NWS/NCEP GFS-GOCART. NOAA Contract No. / Task No. DG133R-07-NC-1616, Mod 12/8407-001, 8/2011-7/2012, $50,000, X. Zhang (task leader), S. Kondragunta (task monitor).
• Global Biomass Burning Emissions Product (GBBEP) from Multiple Geostationary Satellites. NOAA Contract No./Task No. DG133E-06-CQ-0030/N154-001, 7/2010-12/2011, $200,000, X. Zhang (task leader), S. Kondragunta (task monitor).
• Derive Biomass Burning Emissions from GOES WildFire Automated Biomass Burning (WF_ABBA) Fire Products. NOAA Contract No./Task No. DG133E-06-CQ-0030/T102, 04/2005-12/2011, $550,000, X. Zhang (task leader), S. Kondragunta (task monitor).
• POES/METOP Product Validation--Assess AVHRR NDVI product through generation and validation of phenology applications. NOAA Contract No./Task No. DG133E-06-CQ-0030/T140, 08/2009-10/2011, $40,000, X. Zhang (task leader), M. Goldberg (task monitor).
• Develop GOES-R ABI Aerosol & Trace Gas Emissions Algorithm. NOAA Contract No./Task No. DG133E-06-CQ-0030/T124A, 6/2009-12/2011, X. Zhang (task leader), S.Kondragunta (task monitor).
• Adaptation of the GOES Emissions Algorithm to GOES-R ABI. NOAA SciTech Contract: DG133E-06-CQ-0030/8003-080, 6/2007-5/2009, X. Zhang (task leader), S. Kondragunta (task monitor).
• Analysis of AVHRR Climate-Quality Land Products. NOAA Contract No./Task No. DG133E-06-CQ-0030/8003-034, 04/2005—12/2007, $150,000, X. Zhang (task leader), D. Tarpley (task monitor).
• Global land cover and land cover dynamics from MODIS: algorithm refinement in support of global change research. NASA, 1/2004-12/2006, $698,049, PI: M.A. Friedl (BU), CO-I, X. Zhang (BU).
• Real Time Estimation and Assimilation of Remotely Sensed Surface Properties for Numerical Weather Prediction Models. NOAA, 6/2004-5/2007, $454,987, PI: M.A. Friedl (BU), Co-I: X. Zhang (BU).
• Retrieval of Time-Varying Land Cover and Vegetation Properties from MODIS in Support of the NCEP-WRF Land Surface Mode. NOAA, 8/2003-7/2004, $100,000, PI: M.A. Friedl (BU), Co-I: X. Zhang (BU).
• Land Cover/Land-Cover Change, Albedo, BRDF/Directional Reflectance and Spatial Structure Products from MODIS-N and MODIS-T. NASA, 1/1992 - 12/2003, $9,464,991, PI: A.H. Strahler (BU), Research Associate: X. Zhang (BU).
• Remote Sensing for Estimating Rice Yield in Central China. Supported by Chinese National Eighth Five-Year Plan, 1990-1995, X. Zhang (PI).
• Studies on Fishery Ecology in the Shallow Lake of Middle and Low Reaches of the Yangtze River. Supported by Eighth Five-Year Plan of the Chinese Academy of Science, 1992-1995, S. Cai (PI), X. Zhang (Co-I).
• Remotely Sensed Investigation of Natural Resources & Environment in China and their Dynamics. Supported by Five-Year Plan of the Chinese Academy of Science, 1992-1995, S. Cai (PI), X. Zhang (Co-I).
• Studies of Exploitation of Aquatic Biological Productivity and Improvement of Ecological Environment in Lake Honghu. Supported by Seventh Five-Year Plan of the Chinese Academy of Science, 1987-1990, S. Cai (PI), X. Zhang (Co-I).
• Relationship between Human Activities and Environmental Changes in Honghu Area. An International Joint Research with Liverpool University (UK), supported by the Chinese National Foundation of Natural Science, 1991-1994, S. Cai (PI), X. Zhang (Co-I).
• Studies of Natural Resources & Environment and Adjustment of Ecological Agriculture in Sihui District. Supported by Seventh Five-Year Plan of the Hubei Province, 1984-1990, S. Cai (PI), X. Zhang (Co-I).
• Effects of the Three Gorge Project on Lake Environmental Evolution, Potential Gleization, and Creation of Marshes in the North and South of Jingjiang River (Four Lake District). Supported by Chinese National Seventh Five-Year Plan, 1985-1991. S. Cai (PI), X. Zhang (Co-I).
• Planning of Agriculture and Ecological Economy in Four Lake District. Supported by Seventh Five-Year Plan of the Hubei Province, 1986-1990, S. Cai (PI), X. Zhang (Co-I).
• The Evolution of Jianghan-Tongting Lakes. Supported by Chinese National Foundation of Natural Science, 1984-1987, S. Cai (PI), X. Zhang (Co-I).

Patents

Professional Memberships

- American Geophysical Union (AGU)
- Association of American Geographers (AAG)
- International Association of Wildland Fire (IAWF)
- American Meteorological Society (AMS)
- International Association for Landscape Ecology (IALE)

Work Experience

6/2018-present: Full Professor of Geography & Senior Research Scientist at the Geospatial Sciences Centers of Excellence (GSCE), South Dakota State University (SDSU), Brooking, SD. USA
8/2013-5/2018: Associate Professor of Geography & Senior Research Scientist at the Geospatial Sciences Centers of Excellence (GSCE), South Dakota State University (SDSU), Brooking, SD. USA
6/2012-8/2013: Visiting Associate Research Scientist, University of Maryland at NOAA/NESDIS/STAR, College Park, MD, USA
4/2005-5/2012: Senior research scientist, Earth Resources Technology (ERT) at NOAA/NESDIS/STAR, Camps Springs, MD, USA
6/1999-3/2005: Research Associate and made as Research Assistant Professor in 2003, Department of Geography, Boston University
10/1988-2/1995: Research Assistant Professor (1988-1992) and Research Associate Professor (1992-1995), Deputy of Department of Natural Resources and Land Use, Institute of Geodesy & Geophysics, Chinese Academy of Science, Wuhan, China
7/1984-9/1988: Research Assistant, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China

Creative Activities

Operational Products
• Global near real time biomass burning emissions product from polar and geostationary satellites (GBBEPx) (NOAA)
• NOAA Blended Polar Geo Biomass Burning Emissions Product (Blended-BBEP) (NOAA)
• Geostationary Operational Environmental Satellite Biomass Burning Emission Product (GBBEP) (NOAA)
• AVHRR-MODIS long-term global land surface phenology product (NASA)
• VIIRS global land surface phenology product (NASA)

Edited Books

1. Zhang, X. (Ed.), 2012. Phenology and Climate Change, ISBN: 978-953-51-0336-3, InTech, Available from: http://www.intechopen.com/books/phenology-and-climate-change.

Refereed Journal Papers (English) (* first author is my PhD students or Postdocs, or I am the corresponding author but not the first author)

1. Zhang, X., Shen, Y., Gao, S., Wang,W., & Schaaf, C., 2022, Diverse responses of multiple satellite-derived vegetation greenup onsets to dry periods in the Amazon, Geophysical Research Letters, 49, e2022GL098662. https://doi.org/10.1029/2022GL098662
2. *Ye, Y., Zhang, X., Shen, Y., Wang, J., Crimmins, T., Scheifinger, H., 2022, An optimal method for validating satellite-derived land surface phenology using in-situ observations from national phenology networks, ISPRS Journal of Photogrammetry and Remote Sensing, 194: 74-90, https://doi.org/10.1016/j.isprsjprs.2022.09.018
3. *Tran, K.H., Zhang, X., Ketchpaw, A.R., Wang, J., Ye, Y., Shen, Y., 2022, A novel algorithm for the generation of gap-free time series by fusing harmonized Landsat 8 and Sentinel-2 observations with PhenoCam time series for detecting land surface phenology, Remote Sensing of Environment, 282, 113275, https://doi.org/10.1016/j.rse.2022.113275
4. *Lu, X., Zhang, X., Li, F., Cochrane, M.A., 2022, Improved estimation of fire particulate emissions using a combination of VIIRS and AHI data for Indonesia during 2015–2020, Remote Sensing of Environment, 281,113238, https://doi.org/10.1016/j.rse.2022.113238
5. *Li, F., Zhang, X., Kondragunta, S., Lu, X., Csiszar, I., Schmidt, C.C., 2022, Hourly biomass burning emissions product from blended geostationary and polar-orbiting satellites for air quality forecasting applications, Remote Sensing of Environment, 281, 113237, https://doi.org/10.1016/j.rse.2022.113237
6. Liu, Y., Wu, C., Tian, F., Wang, X., Gamon, J.A., Wong, C. Zhang, X., Gonsamo, A., Jassal R.S., 2022, Modeling plant phenology by MODIS derived photochemical reflectance index (PRI), Agricultural and Forest Meteorology, 324, 109095, https://doi.org/10.1016/j.agrformet.2022.109095
7. Campbell, P.C., Tong, D., Saylor, R., Li, Y., Ma, S., Zhang, X., Kondragunta, S., Li, F., 2022, Pronounced increases in nitrogen emissions and deposition due to the historic 2020 wildfires in the western US, Science of The Total Environment, 839, 156130, https://doi.org/10.1016/j.scitotenv.2022.156130
8. Wu, C., Peng, J., Ciais, P., Peñuelas, J., Wang, H., Beguería, S., Black, T.A., Jassal, R.S., Zhang, X., Yuan, W., Liang, E., Wang, X., Hua, H., Liu, R., Ju, W., Fu, Y.H., Ge, Q., 2022, Increased drought effects on the phenology of autumn leaf senescence, Nature Climate Change, 1-7, https://doi.org/10.1038/s41558-022-01464-9
9. Li, Y., Tong, D., Ma, S., Freitas, S. R., Ahmadov, R., Sofiev, M., Zhang, X., Kondragunta, S., Kahn, R., Tang, Y., Baker, B., Campbell, P., Saylor, R., Grell, G., and Li, F., 2022, Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: A comparison of three schemes (Briggs, Freitas, and Sofiev), EGUsphere, https://doi.org/10.5194/egusphere-2022-713
10. Zhang, L., Montuoro, R., McKeen, S. A., Baker, B., Bhattacharjee, P. S., Grell, G. A., Henderson, J., Pan, L., Frost, G. J., McQueen, J., Saylor, R., Li, H., Ahmadov, R., Wang, J., Stajner, I., Kondragunta, S., Zhang, X., and Li, F., 2022, Development and evaluation of the Aerosol Forecast Member in the National Center for Environment Prediction (NCEP)'s Global Ensemble Forecast System (GEFS-Aerosols v1), Geoscientific Model Development, 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022.
11. Wu, J., Kong, S., Yan, Y., Yao, L., Yan, Q., Liu, D., Shen, G., Zhang, X., Qi, S., 2022, Neglected biomass burning emissions of air pollutants in China-views from the corncob burning test, emission estimation, and simulations, Atmospheric Environment, 278, 119082, https://doi.org/10.1016/j.atmosenv.2022.119082
12. Wu, J., Kong, S., Yan, Y., Yao, L., Yan, Q., Liu, D., Shen, G., Zhang, X., Qi, S., 2022, The toxicity emissions and spatialized health risks of heavy metals in PM2. 5 from biomass fuels burning, Atmospheric Environment, 284, 119178, https://doi.org/10.1016/j.atmosenv.2022.119178
13. Pan, Y., Wang, Y., Zheng, S., Huete, A.R., Shen, M., Zhang, X., Huang, J., He, G., Yu, L., Xu, X., Xie, Q., Peng, D., 2022, Characteristics of Greening along Altitudinal Gradients on the Qinghai–Tibet Plateau Based on Time-Series Landsat Images, Remote Sensing, 14(10), 2408, https://doi.org/10.3390/rs14102408
14. Lou, Z., Peng, D., Zhang, X., Yu, L., Wang, F., Pan, Y., Zheng, S., Hu, J., Yang, S., Chen, Y., Liu, S., 2022, Soybean EOS Spatiotemporal Characteristics and Their Climate Drivers in Global Major Regions, Remote Sensing, 14 (8), 1867, https://doi.org/10.3390/rs14081867
15. An, S., Chen, X.Q., Shen, M.G., Zhang, X., Lang, W.G., and Liu, G.H., 2022, Increasing Interspecific Difference of Alpine Herb Phenology on the Eastern Qinghai-Tibet Plateau. Front. Plant Sci. 13:844971, https://doi.org/10.3389/fpls.2022.844971
16. An, S., Zhang, X., Ren, S., 2022, Spatial Difference between Temperature and Snowfall Driven Spring Phenology of Alpine Grassland Land Surface Based on Process-Based Modeling on the Qinghai–Tibet Plateau, Remote Sens., 14(5), 1273, https://doi.org/10.3390/rs14051273
17. Bela, M.M., Kille, N., McKeen, S.A., Romero‐Alvarez, J., Ahmadov, R., James, E., Pereira, G., Schmidt, C., Pierce, R.B., O’Neill, S.M., Zhang, X., Kondragunta, S., Wiedinmyer, C., Volkamer, R., 2022, Quantifying carbon monoxide emissions on the scale of large wildfires, Geophysical Research Letters, 49 (3), https://doi.org/10.1029/2021GL095831
18. Donnelly, A., Yu, R., Jones, K., Belitz, M., Li, B., Duffy, K., Zhang, X., Wang, J., Seyednasrollah, B., Gerst, K.L., Li, D., Kaddoura, Y., Zhu, K., Morisette, J., Ramey, C., Smith, K., 2022, Exploring discrepancies between in situ phenology and remotely derived phenometrics at NEON sites, Ecosphere 13 (1), e3912, https://doi.org/10.1002/ecs2.3912
19. *Shen, Y., Zhang, X., Yang, Z., 2022, Mapping corn and soybean phenometrics at field scales over the United States Corn Belt by fusing time series of Landsat 8 and Sentinel-2 data with VIIRS data, ISPRS Journal of Photogrammetry and Remote Sensing, 186, 55-69, https://doi.org/10.1016/j.isprsjprs.2022.01.023
20. Zhang, X., Gao, F., Wang, J., Ye, Y., 2021, Evaluating a spatiotemporal shape-matching model for the generation of synthetic high spatiotemporal resolution time series of multiple satellite data, International Journal of Applied Earth Observation and Geoinformation, 104, https://doi.org/10.1016/j.jag.2021.102545
21. Li, Y., Tong, D., Ma, S., Zhang, X., Kondragunta, S., Li, F., Saylor, R. 2021, Dominance of Wildfires Impact on Air Quality Exceedances During the 2020 Record‐Breaking Wildfire Season in the United States, Geophysical Research Letters, 48 (21), e2021GL094908, https://doi.org/10.1029/2021GL094908
22. *Shen, Y., Zhang, X., Wang, W., Nemani, R., Ye, Y., and Wang, J., 2021, Fusing Geostationary Satellite Observations with Harmonized Landsat-8 and Sentinel-2 Time Series for Monitoring Field-Scale Land Surface Phenology, Remote Sensing, 13(21), 4465; https://doi.org/10.3390/rs13214465
23. *Ye, Y., Zhang, X., 2021, Exploration of global spatiotemporal changes of fall foliage coloration in deciduous forests and shrubs using the VIIRS land surface phenology product, Science of Remote Sensing, 4, 100030, https://doi.org/10.1016/j.srs.2021.100030
24. Lu, X., Zhang, X., Li, F., Gao, L., Graham, L., Vetrita, Y., Saharjo, B., Cochran, M., 2021, Drainage canal impacts on smoke aerosol emissions for Indonesian peatland and non-peatland fires, Environmental Research Letters, 16(9), 095008, https://doi.org/10.1088/1748-9326/ac2011
25. Liu, Y, Mackenzie, C.M., Primack, R.B., Hill, M.J., Zhang, X., Wang, Z., and Schaaf, C.B., 2021, Using remote sensing to monitor the spring phenology of Acadia National Park across elevational gradients, Ecosphere, 12(12), http://doi.org/10.1002/ecs2.3888
26. Peng, J., Wu, C., Zhang, X., Ju, W., Wang, X., Lu, L., Liu, Y., 2021, Incorporating water availability into autumn phenological model improved China’s terrestrial gross primary productivity (GPP) simulation, Environmental Research Letters,16(9), https://doi.org/10.1088/1748-9326/ac1a3b
27. Liu, H., He, B., Zhou, Y., Yang, X., Zhang, X., Xiao, F., Feng, Q., Liang, S., Zhou, X., Fu, C., 2021, Eutrophication monitoring of lakes in Wuhan based on Sentinel-2 data, GIScience & Remote Sensing, 58(5):1-23, https://doi.org/10.1080/15481603.2021.1940738
28. Gao, F., Zhang, X., 2021, Mapping crop phenology in near real-time using satellite remote sensing: Challenges and opportunities, Journal of Remote Sensing, 8379391, https://doi.org/10.34133/2021/8379391
29. Lu, X., Zhang, X., Li, F., Cochrane, M.A., Ciren, P., 2021, Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions, Remote Sensing, 13 (2), 196, https://doi.org/10.3390/rs13020196
30. *Wang, J., Zhang, X., Rodman, K., 2021, Land cover composition, climate, and topography drive land surface phenology in a recently burned landscape: An application of machine learning in phenological modeling, Agricultural and Forest Meteorology, https://doi.org/10.1016/j.agrformet.2021.108432
31. Wu, C., Wang, J., Ciais, P., Peñuelas, J., Zhang, X., Sonnentag, O.,Tian, F., Wang, X., Wang, H., Liu, R., Fu, Y., and Ge, Q., 2021, Widespread decline in winds delayed autumn foliar senescence over high latitudes, PNAS, 118 (16), https://doi.org/10.1073/pnas.2015821118
32. Jia, W., Zhao, S., Zhang, X., S Liu, S., Henebry, G.M., Liu, L., 2021, Urbanization imprint on land surface phenology: The urban–rural gradient analysis for Chinese cities, Global Change Biology, https://doi.org/10.1111/gcb.15602
33. Liang, L., Henebry, G.M., Liu, L., Zhang, X., Hsu, LC, 2021, Trends in land surface phenology across the conterminous United States (1982–2016) analyzed by NEON domains, Ecological Applications, https://doi.org/10.1002/eap.2323
34. Wu, J., Kong, S., Zeng, X., Cheng, Y., Yan, Q., Zheng, H., Yan, Y., Zheng, S., Liu, D., Zhang, X., Fu, P., Wang, S., Qi, S., 2021, First High-Resolution Emission Inventory of Levoglucosan for Biomass Burning and Non-Biomass Burning Sources in China, Environ Sci Technol, https://doi.org/10.1021/acs.est.0c06675
35. *Peng, D., Wang, Y., Xian, G., Huete, A.R., Huang, W., Shen, M., Wang, F., Yu, L., Liu., L., Xie, Q., Liu, L., Zhang, X., 2021, Investigation of land surface phenology detections in shrublands using multiple scale satellite data, Remote Sensing of Environment, 252, https://doi.org/10.1016/j.rse.2020.112133
36. *Liu, L., Zhang, X., 2020, Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016, Scientific Reports (10), 17952, https://doi.org/10.1038/s41598-020-74804-4
37. Wang, X., Wu, C., Zhang, X., Li, Z., Liu, Z., Gonsamo, A., and Ge, Q., 2020, Satellite-observed decrease in the sensitivity of spring phenology to climate change under high nitrogen deposition, Environmental Research Letters, 15, 094055, https://doi.org/10.1088/1748-9326/aba57f
38. Li, Y., Tong, D.Q., Ngan, F., Cohen, M.D., Stein, A.F., Kondragunta, S., Zhang, X., Ichoku, C., Hyer, E.J., Kahn, R.A., 2020, Ensemble PM2.5 Forecasting During the 2018 Camp Fire Event Using the HYSPLIT Transport and Dispersion Model, Journal of Geophysical Research: Atmospheres, 125 (15), e2020JD032768, https://doi.org/10.1029/2020JD032768
39. *Li, F ., Zhang, X., Kondragunta, S., Lu, X., 2020, An evaluation of advanced baseline imager fire radiative power basedwildfire emissions using carbon monoxide observed by the TroposphericMonitoring Instrument across the conterminous United States, Environmental Research Letters, 15, 094049, https://doi.org/10.1088/1748-9326/ab9d3a
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120. Tian Y, Dickinson, R.E., Zhou, L., Zeng, X., Dai, Y., Myneni, R.B., Knyazikhin, Y., Zhang, X., Friedl, M., Yu, II., Wu, W., Shaikh, M. 2004. Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. Journal of Geophysical Research-Atmospheres, 109 (D1): Art. No. D01103, http://dx.doi.org/10.1029/2003JD003777.
121. Penuelas, J., Filella, I., Zhang, X., LLorens, L., Ogaya, R., Lloret, F., Comas, P., Estiarte, M., Terradas, J., 2004. Complex spatiotemporal phenological shifts as a response to rainfall changes. New Phytologist, 161(3): 837-846, http://dx.doi.org/10.1111/j.1469-8137.2004.01003.x.
122. Zhang, X., Schaaf, C. B., Friedl, M. A., Strahler, A. H., Gao F., Hodges, J. F., Reed, B. C., Huete, A., 2003. Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84(3), 471-475, http://dx.doi.org/10.1016/S0034-4257(02)00135-9.
123. Zhang, X., Drake, N. A., and Wainwright, J. 2002. Scaling land-surface parameters for global scale soil-erosion estimation. Water Resources Research, 38(9), 191-199, http://dx.doi.org/10.1029/2001WR000356. (This paper was highlighted by EOS, 83(43), Oct., 2002).
124. Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., Strugnell, N. C., Zhang, X., Jin, Y., Muller, J. P. et al. 2002. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83(1-2), 135-148, http://dx.doi.org/10.1016/S0034-4257(02)00091-3.
125. Friedl, M. A, McIver, D. K, Hodges, J. C., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schnieder, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C. B. 2003. Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment, 83(1-2), 287-302, http://dx.doi.org/10.1016/S0034-4257(02)00078-0.
126. Yun Du, Y., Cai, S., Zhang, X. and Zhao, Y. 2001. Interpretation of the environmental change of Dongting Lake, middle reach of Yangtze River, China, by 210Pb measurement and satellite image analysis. Geomorphology, 41(2-3), 171-181, http://dx.doi.org/10.1016/S0169-555X(01)00114-3.
127. Zhang, X., Drake, N. A., Wainwright, J. and Mulligan, M. 1999. Comparison of slope estimates from low resolution DEMs: scaling issues and a fractal method for their solution. Earth Surface Processes and Landforms, 24(9), 763-779, http://dx.doi.org/10.1002/(SICI)1096-9837(199908)24:9<763::AID-ESP9>3.0.CO;2-J.
128. Zhang, X. 1998. On the estimation of biomass of submerged vegetation using Landsat thematic mapper (TM) imagery: case study of the Honghu Lake, PR China. International Journal of Remote Sensing, 19(1), 11-20, http://dx.doi.org/10.1080/014311698216396.

Refereed Book Chapters (English)

129. Zhang, X., 2018. Land Surface Phenology: Climate Data Record and Real-Time Monitoring. In Liang, S. (ed), Comprehensive Remote sensing: Terrestrial ecosystems, ELSE, Vol 3: 35-52. https://doi.org/10.1016/B978-0-12-409548-9.10351-3
130. Zhang, X., Ni-meister, W., 2014. Remote sensing of Forest biomass. In Hanes, J. (ed), Biophysical Applications of Satellite Remote Sensing, Springer, New York, pp 63-98. https://doi.org/10.1007/978-3-642-25047-7_3
131. Zhang, X., Friedl, M.A., Tan, B., Goldberg, M.D. and Yu, Y., 2012. Long-Term Detection of Global Vegetation Phenology from Satellite Instruments. In X. Zhang (Ed.), Phenology and Climate Change, ISBN: 978-953-51-0336-3, InTech.
132. Zhang, X., Drake, N. A., Wainwright, J., 2013. Spatial Modelling and Scaling Issues. In Wainwright, J. and Mulligan, M. (eds.), Environmental Modeling: Finding Simplicity in Complexity (Second Edition), John Wiley and Sons, Chichester.
133. Friedl, M.A., Zhang, X., Strahler, A.H, 2011. Characterizing global land cover type and seasonal land cover dynamics at moderate spatial resolution using MODIS. In Ramachandran, B., Justice, C., and Abrams, M. (Eds), Land Remote Sensing and Global Environmental Change: NASA’s Earth Observing System and the Science of ASTER and MODIS, Springer, New York,pp709-721.
134. Zhang, X., Drake, N. A., and Wainwright, J. 2004. Scaling issues in environmental modeling. In Wainwright, J. and Mulligan, M. (eds.), Environmental Modeling: Finding Simplicity in Complexity, John Wiley and Sons, Chichester, pp. 319-334.
135. Drake, N.A., Zhang, X., Symeonakis, E., Patterson, G., Bryant, A.R. 2004. Near Real-time Modeling of Regional scale soil erosion using AVHRR and METEOSAT data: a tool for monitoring the impact of sediment yield on the biodiversity of Lake Tanganyika. In Kelly, R., Drake, N., and Barr, S. (eds.), Spatial Modelling of the Terrestrial Environment. John Wiley and Sons, Chichester, pp. 157-174.
136. Drake, N. A., Zhang, X., Berkhout, E., Bonifacio, R., Grimes, D., Wainwright, J. and Mulligan, M. 1999. Modeling soil erosion at global and regional scales using remote sensing and GIS techniques. In Atkinson, P. M. and Tate, N. J. (eds.), Advances in Remote Sensing and GIS Analysis, John Wiley and Sons, Chichester, pp. 241-261.
137. Zhang, X. 1992. Study on the swamping of lakes and lowland in Jianghan and Dongting plain by using remote sensing techniques. In Embleton, C. (ed.), Geo-hazards and their Reduction, Science Press, Beijing, pp. 61-69.
138. Zhang, X. and Cai, S. 1994. Study on wetland and its dynamic changes in Jianhan plain by using remote sensing. In Wetland Environment and Peatland Utilization: Wetland Environment and Peatland Utilization, Changchun, China, Jilin People's Publishing House, Changchun, China, pp. 296-302.

Refereed Journal Papers (Chinese) (5)

139. Liu, L., Pang, Y., Zhang, X., Solberg, S., Fan,W., Li, Z., Li, M., 2012. Monitoring Forest Growth Disturbance Using Time Series MODIS EVI Data. Forest Science, China, 28: 54-62.
140. Zhang, X., Li, J., 1995. The derivation of a reflectance model for the estimation of leaf area index using perpendicular vegetation index. Remote Sensing Technology and Application, 10(3):13-18.
141. Zhang, X., Du, Y. and Cai, S. 1995. An analysis on evolutional tendency of Dongting Lake. Resources and Environment in the Yangtze Valley, China, 4(1), 64-69.
142. Zhang, X., Cai, S. and Sun, S. 1994. Evolution of Dongting Lake since Holocene, Limnology Science, China, 16(1).
143. Yu, L., Xu, Y, Cai, S. and Zhang, X. 1993. The application of GIS to a lake environmental change study. Limnology Science, China, 15(4).

Refereed Journal Book Chapters (Chinese) (15)

144. Zhang, X., Huang, J., Li, J., Chen, S. and Liu, K. 1995. Remote sensing for modeling rice yield in Hubei province, PRC. In Zhou, R. et al (ed.), Rice Yield Estimation Using Remote Sensing in China, Science Press, Beijing.
145. Zhang, X. 1995. The relationship between biomass of submerged vegetation and spectral properties. In Chen, Y. and Xu Y. (eds.), Hydrobiology and Resource Exploitation in the Honghu Lake, Sciences Press, Beijing.
146. Zhang, X. 1995. Investigating biomass of submerged vegetation using PCA analysis. In Chen, Y. and Xu Y. (eds.), Hydrobiology and Resource Exploitation in the Honghu Lake, Sciences Press, Beijing.
147. Zhang, X. and Cai, S. 1994. The effect of the Three Gorge Project on Dongting Lake. In Pu, P. (ed.), The Effect of Three Gorge Project on The Environment of Lakes And Wetland In The Middle Reaches of Yangtze River, Sciences Press, Beijing.
148. Zhang, X., Li, R., Chen, S. and Liu, K. 1993. Exploring a remote sensing model of rice yield estimation. In Chen, S. (ed.), Estimation of Wheat, Maize and Rice Yield Using Remote Sensing Techniques, Chinese Science and Technology Press, Beijing.
149. Zhang, X., Li, R. and Du, Y. 1993. Sampling frame for rice yield estimation based on the remote sensing techniques in Jiangli County. In Chen, S. (ed.), Estimation of Wheat, Maize and Rice Yield Using Remote Sensing Techniques, Chinese Science and Technology Press, Beijing.
150. Liu, K., Yang, B. and Zhang, X. 1993. Numerical simulation of rice yield. In Chen, S. (ed.), Estimation of Wheat, Maize and Rice Yield Using Remote Sensing Techniques, Chinese Science and Technology Press, Beijing.
151. Zhang, X. and Cai, S. 1991. Recent change of Dongting Lake. In Chinese Association of Geomorphology and Quaternary (ed.), Research Progress of Geomorphology and Quaternary, Survey and Drawing Press, Beijing.
152. Zhang, X. and Cai, S. 1991. Analysis of the swamping process and the dynamic change in emergent vegetation on the basis of remote sensing data. In Honghu Research Group, Institute of Hydrobiology, Academia Sinica (ed.), Studies on Comprehensive Exploitation of Aquatic Biological Productivity and Improvement of Ecological Environment in Lake Honghu, China Ocean Press, Beijing.
153. Zhang, X. and Cai, S. 1991. Estimation of the emergent vegetation biomass in Lake Honghu by means of remote sensing. In Honghu Research Group, Institute of Hydrobiology, Academia Sinica (ed.), Studies on Comprehensive Exploitation of Aquatic Biological Productivity and Improvement of Ecological Environment in Lake Honghu, China Ocean Press, Beijing.
154. Cai, S. and Zhang, X. 1991. Co-ordinate development of fishery and agriculture in the Honghu basin. In Honghu Research Group, Institute of Hydrobiology, Academia Sinica (ed.), Studies on Comprehensive Exploitation of Aquatic Biological Productivity and Improvement of Ecological Environment in Lake Honghu, China Ocean Press, Beijing.
155. Cai, S., Yi, C., and Zhang, X. 1991. Process of swamping and pedogenesis in Honghu Lake and utilization. In Honghu Research Group, Institute of Hydrobiology, Academia Sinica (ed.), Studies on Comprehensive Exploitation of Aquatic Biological Productivity and Improvement of Ecological Environment in Lake Honghu, China Ocean Press, Beijing.
156. Cai, S., Zhang, X., Zhou, S. and Wang, K. 1989. Map of the change of lakes in Sihu district. In Atlas of Ecosystems and Environments in the Three Gorges of the Yangtze River, Science Press, Beijing.
157. Cai, S. and Zhang, X. 1989. Map of the change of Dongting Lake. In Atlas of Ecosystems and Environments in the Three Gorges of the Yangtze River, Science Press, Beijing.
158. Cai, S., Guan, Z, Zou, J. Zhang, X., Yi, L. and Yang H. 1987. Effects of the Three Gorge project on lake environmental evolution and potential gleization and creation of marshes in the north and south of Jingjiang River. In Impacts of the Three Gorges Project on Ecosystems and Environment and Possible Countermeasures, Science Press, Beijing.