Refereed Journal Articles
Huang, X., Wang, C. Lu, J., & Ning, H. (2019). Understand spatiotemporal development of human settlement in hurricane-prone areas using nighttime remote sensing, Natural Hazards and Earth System Science, doi: 10.5194/nhess-19-2141-2019. [download PDF]
Huang, X., Wang, C. Li, Z., & Ning, H. (2019). Identifying disaster related social media for rapid response: a visual-textual fused CNN architecture. International Journal of Digital Earth, doi: 10.1080/17538947.2019.1633425. [download PDF]
Huang, X., Wang, C. Li, Z., & Ning, H. (2018). A visual-textual fused approach to automated tagging of flood-related tweets during a flood event. International Journal of Digital Earth, doi: 10.1080/17538947.2018.1523956. [download PDF]
Huang, X., Wang, C., & Li, Z. (2018). Reconstructing flood inundation probability by enhancing near real-time imagery with real-time gauges and tweets. IEEE Transactions on Geoscience and Remote Sensing, 56(8), 4691-4701. [download PDF]
Huang, X., Wang, C., & Li, Z. (2018). A near real-time flood-mapping approach by integrating social media and post-event satellite imagery. Annals of GIS, 24(2), 113-123. [download PDF]
Wang, C., Li, Z., & Huang, X. (2018). Geospatial Assessment of Wetness Dynamics in the October 2015 SC Flood with Remote Sensing and Social Media. Southeastern Geographer, 58(2), 164-180. [download PDF]
Li, H., Wang, C., Huang, X., & Hug, A. (2018). Spatial Assessment of Water Quality with Urbanization in 2007–2015, Shanghai, China. Remote Sensing, 10(7), 1024. [download PDF]
Ning, H., Huang, X., Wang, C., & Li, Z. A rapid building change detection method based on UAV image. International Journal of Geo-Information. (accepted)
Refereed Journal Articles In Review
Huang, X., Ning, H., Wang, C., Li, Z., & Kim, H. A 100m grid population dataset in the CONUS by disaggregating census population with Microsoft building footprints, Applied Geography. In Review.
Huang, X., & Wang, C. Estimates of population at risks in the 100-year floodplain of the Conterminous United States using national building footprints, International Journal of Disaster Risk Reduction. In Review
Lu, J., Carbone, G., Lackstorm, K., & Huang, X. Mapping the vulnerability of agriculture to drought and estimating the effect of irrigation on the vulnerability in the United States, 1950-2016, Land use Policy. In Review.
Refereed Journal Articles In Prep
Huang, X., Wang, C, & Li, Z. Burst-based social sensing of infrastructure disruptions during disasters. In Prep.
Huang, X., & Wang, C. Exploring the capability of satellite imagery in population estimation via deep learning, In Prep. (Manuscript Ready)
Huang, X., Wang, C., & Mitra, A. Dynamics of human proximity to rivers in India after major floods using nighttime remote sensing. In Prep.
Ning, H., Li, Z., Hodgson, M., & Huang, X. Building Area Detection in Remote Sensing Image Based on Sliding Window and Existing Point Labels by Convolutional Neural Networks. In Prep. (Manuscript Ready)
Refereed Conference Papers
Huang, X., Wang, C., & Li, Z. (2019). Linking picture with text: tagging flood relevant tweets for rapid flood inundation mapping. Proceedings of the International Cartographic Association, 2, 45, doi: 10.5194/ica-proc-2-45-2019.
Huang, X., Wang, C, & Li, Z. (2019). High-Resolution Population Grid in the CONUS using Microsoft Building Footprints: a feasibility study. Proceedings of the 3rd ACM SIGSPTIAL Workshop on Geospatial Humanities, doi: 10.1145/3356991.3365469.
Huang, X., & Wang, C. (2019). Human settlement dynamics in hurricane-prone zones of CONUS: view from nighttime remote sensing perspective. 2019 IEEE International Geoscience and Remote Sensing Symposium. (In Press)
Huang, X. (2017). A Future Energy Harvesting Scenario for Georgia Tech Campus Using Photovoltaic Solar Panels and Piezoelectric Materials. MS-GIST Capstone Paper, Georgia Institute of Technology.
Huang, X. (2019). The fusion of remote sensing and social sensing in rapid flood mapping: motivation, opportunities and challenges, US National Report (US National Committee for the International Cartographic Association):