Refereed Journal Articles

 

Lu, J., Carbone, G. J., Huang, X., Lackstrom, K., & Gao, P. (2020). Mapping the sensitivity of agriculture to drought and estimating the effect of irrigation in the United States, 1950–2016. Agricultural and Forest Meteorology, 292, 108124. [download PDF]

Huang, X., & Wang, C. (2020). Estimates of exposure to the 100-year floods in the conterminous United States using national building footprints. International Journal of Disaster Risk Reduction, doi: 10.1016/j.ijdrr.2020.101731. [download PDF]

Huang, X., Wang, C., Li, Z., & Ning, H. (2020). A 100 m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints. Big Earth Data, 10.1080/20964471.2020.1776200. [download PDF]

Xu, D., Huang, X., Li, Z., & Li, X. (2020). Local Motion Simulation using Deep Reinforcement Learning, Transactions in GIS, doi: 10.1111/tgis.12620. [download PDF]

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. Detecting new building construction in urban areas based on images of small unmanned aerial system. Papers in Applied Geography, doi: 10.1080/23754931.2019.1707108. [download PDF]

Refereed Journal Articles In Review

Huang, X., Li, Z., Jiang, Y., Deng, C., Zhang, J. The Characteristics of multi-source mobility datasets and how they reveal the luxury nature of social distancing in the US during the COVID-19 pandemic. Applied Geography. In Review.

Huang, X., Li, Z., Jiang, Y., Li, X., Porter, D. Twitter, human mobility, and COVID-19., PLOS ONE. In Review.

Zhang, R., Shao, Z., Huang, X., Wang, J., Li, D. Object detection in UAV images via global density fused convolutional network. Remote Sensing. In review.

Zhang, R., Shao, Z., Li, D., Wang, J., Wang, Y., Huang, X. Adaptive dense pyramid network for objection in UAV imagery. Pattern Recognition. 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.

Huang, X., Xu, D., Li, Z., & Wang, C. (2019). The potential of conditional generative networks in translating multispectral imagery to nighttime imagery, International Journal of Geo-Information. In Preparation.

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

Li, Z., Huang, X., Zhang, J., Zeng, C., Olatosi, B., Li, X., Weissman, S. (2020). Human Mobility, Policy, and COVID-19: A Case Study of South Carolina. Proceedings of the 3rd SIGSPATIAL International Workshop on Advances on Resilient and Intelligent Cities. (In review)

Huang, X., Xu, D., Li, Z., & Wang, C. (2019). Translating multispectral imagery to nighttime imagery via conditional generative networks. 2019 IEEE International Geoscience and Remote Sensing Symposium. (Accepted).

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, July). Human Settlement Dynamics in Hurricane-Prone Zones of Conterminous US: A View from Nighttime Remote Sensing. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 1538-1541). IEEE.

Other publications

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): https://cartogis.org/usnc-ica/us-national-report/.

Huang, X.(2020). Remote Sensing and Social Sensing for Improved Flood Awareness and Exposure Analysis in the Big Data Era. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/5851

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.