• Ph.D. in Geography, Boston University
• M.A. in Environmental Remote Sensing and GIS, Boston University
• B.E. in Geographic Information System, Tongji University

Professor Tang is a geographer who uses remote sensing and spatial analysis to study the changes to the Earth’s surface with a focus on monitoring land use/land cover change and its impact on terrestrial carbon cycle and forest ecosystems.

He specifically interested in developing new methods for monitoring changes at regional to global scales using time series analysis and multi-sensor data fusion, and the use of spatiotemporal modeling to reduce the uncertainties in estimates of carbon emissions.

Tang is exploring new research ideas on the social and economic impact of human-driven changes to the Earth’s surface and how that affects sustainability. His research takes advantage of the abundance of freely available high-quality remote sensing data and the advancement in cloud computing capacity.

• Remote Sensing
• GIS
• Data Fusion
• Time Series Analysis
• Terrestrial Carbon Cycle
• Land Use/Land Cover Change
• Geospatial Intelligence

• ISAT 449: Emerging Topics in Data Science
• GEOG 485: Processing Remotely Sensed Data

• Zhang, Y., Woodcock, C.E., Arévalo, P., Olofsson, P., Tang, X., Stanimirova R., Bullock, E.L., Tarrio, K.R., Zhu, Z, & Friedl, M.A. (2022). A global analysis of the spatial and temporal variability of usable Landsat observations at the pixel scale. Frontiers in Remote Sensing, 3, 894618.
• Bullock, E.L., Healey, S., Yang, Z., Gorelick, N., Houborg, R., Tang, X., & Andrianirina, C. (2022). Timeliness in Forest Change Monitoring: A Conceptual Demonstration using Sentinel-1 and Continuous Change Detection and Classification (CCDC). Remote Sensing of Environment, 276, 113043.
• Morreale, L.L., Thompson, J.R., Tang, X., Reinmann, A.B., & Hutyra, L.R. (2021). Elevated growth and biomass along temperate forest edges. Nature Communications, 12(1), 1-8.
• Tang, X., Woodcock, C.E., Olofsson, P., & Hutyra, L.R. (2021) Spatiotemporal assessment of land use/land cover change and associated carbon emissions and uptake in the Mekong River Basin. Remote Sensing of Environment, 256, 112336.
• Tang, X., Bullock, E.L., Olofsson, P., & Woodcock, C.E. (2020). Can VIIRS continue the legacy of MODIS for near real-time monitoring of tropical forest disturbance?. Remote Sensing of Environment, 249, 112024.
• Tang, X., Hutyra, L.R., Arévalo, P., Baccini, A., Woodcock, C.E., & Olofsson, P. (2020). Spatiotemporal tracking of carbon emissions and uptake using time series analysis of Landsat data: a spatially explicit carbon bookkeeping model. Science of the Total Environment, 720, 137409.
• Tarrio, K., Tang, X., Masek, J.G., Claverie, M., Ju, J., Zhu, Z., & Woodcock, C.E. (2020). Comparison of cloud detection algorithms for Sentinel-2 imagery. Science of Remote Sensing, 2, 100010.
• Tang, X., Bullock, E.L., Olofsson, P., Estel, S., & Woodcock, C.E. (2019). Near real-time monitoring of tropical forest disturbance: New algorithms and assessment framework. Remote Sensing of Environment, 224, 202-218.

• Continued support for estimation and monitoring of land change and forest degradation in West Africa (Institutional PI); NASA SERVIR.
• MUTATED – Modeling and understanding using temporal analysis of transient earth data (Institutional PI); IARPA Space-Based Machine Automated Recognition Technique (SMART) Program.
• Near-real-time monitoring of tropical forest disturbance by fusion of Landsat, Sentinel-1, and Sentinel-2 data (Co-I); The GEO-Microsoft Planetary Computer Programme.

• Google Scholar
• GitHub
• Twitter (@xjtang_jmu)