The Computational Spatial Science for Sustainability Laboratory (COMPASS Lab) is a research group in the School of Geoscience at University of South Florida. The COMPASS Lab conducts research on GIScience and Spatial Data Science to promote resilience and sustainability of human communities facing natural hazards and climate change. The lab is led by Dr. Yi Qiang, an Associate Professor at USF Geosciences.
We are actively seeking motivated graduate students to join our team. If you are interested, please consider applying to the M.A. in Geography or the Ph.D. in Geography, Environmental Science and Policy at USF Geosciences. Teaching and research assistantships are available for competitive applicants. For more information, please contact the lab director, Dr. Yi Qiang.
The COMPASS Lab has made a strong prescence in AAG 2026 in San Francisco, organized and presented in multiple sessions on topics related to GeoAI, human mobility, & disaster resilience.
Salim et al. published a study on flood map uncertainties in Int. J. Disaster Risk Reduction. [Access]
Han et al. published a study on spatial pattern on 2022 Monkeypox outbreak in Professional Geography. [Access]
Salim et al. published his study on property damages in 2022 Hurricane Ian in Remote Sensing. [Access]
Using data science and spatial analysis techniques, we detected notable changes in population movements, both within Florida and nationwide, which are potentially linked to the hurricane-induced population evacuation. The distance decay pattern of population flows from Florida demonstrates a propensity for individuals to relocate to nearby areas during the hurricane. Furthermore, the increase in population outflows from the impacted areas suggests the effectiveness of mandatory evacuation orders. A more pronounced increase in outflows from designated mandatory evacuation areas points to the public awareness of the evacuation zone designation. This study provides large-scale, fine-resolution analysis of evacuation behaviours in natural disasters which cannot be easily detected in traditional data sources.
Publications:
Li, X., Qiang, Y., & Cervone, G. (2024). Using human mobility data to detect evacuation patterns in hurricane Ian. Annals of GIS. [access]
We use night-time light remote sensing images to detect disturbance and recovery of human activities in natural disasters. Our study demonstrates that NTL remote sensing is a low cost, efficient and large-scale data acquisition method to analyze community resilience.
Publications:
Qiang, Y., Huang, Q., Xu, J., (2020) “Observing Disaster Resilience from Space: Using Nighttime Lights to Model Economic Disturbance and Recovery Pattern in Natural Disaster”, Sustainable Cities and Society [ pdf ]
Xu, J. & Qiang, Y. (2021). “Spatial Assessment of Community Resilience from 2012 Hurricane Sandy using Nighttime Light”. Remote Sensing. [pdf]
We use crowdsourced traffic data in Google Maps to monitor road network condition in extreme weather events (e.g. a winter storm). We found that accessibility to critical facilities reduces due to weather impacts and the recovery process differs in different places. This method can provide support for emergency response and assessment of road network resilience.
Publications
Qiang, Y., Xu. J., (2020) “Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data”, International Journal of Geographical Information Science. vol: 12(34) pp.2434-2450. DOI: 10.1080/13658816.2019.1694681 [pdf]
This study utilized NASA’s Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane and investigates the socio-economic disparities related to the damage. The results revealed the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience.
Publications:
Salim, Z., Qiang, Y, Dixon, B., Collins, J. (2024) “A Disparate Disaster: Spatial Patterns of Building Damages and Associated Socio-Economic Factors by 2022 Hurricane Ian” Remote Sensing, Vol 16(20). [Access]
We conduct spatio-temporal analyses of flood exposure of population and critical infrastructures. It is estimated that 21.8 million (6.87% of) U.S. population are exposed to 100-year-flood in 2015. At a national scale, the overall flood exposure in the CONUS decreased in the past two decades, indicating increasing awareness of flood risk in the country. But the local variations of flood exposure and its changing trends vary among communities.
Publications:
Xu, J., Qiang, Y., Cai, H. Zou, L. (2024) “Environmental justice implications of flood risk in the contiguous United States–a spatiotemporal assessment of flood exposure change from 2001 to 2019”. Cartography and Geographic Information Science. Vol 16(1), pp 2259-2278. [access]
Qiang, Y. (2019) “Disparities of Population Exposed to Flood Hazards in the United States”, Journal of Environmental Management. vol: 232 (15). DOI:10.1016/j.jenvman.2018.11.039 [pdf]
Compass was invented in China during the Han Dynasty (200 BC - 100 AD) where it was called the "south-governor" (sīnán 司南). The original form of compass is a spoon-shaped lodestone placed in the center of a plate. In the Age of Exploration, compass had a profound influence on geography and the shaping of the world. In the 21st century, the COMPASS Lab leverages data and computing revolutions to study environment-human interactions for a sustainable future.
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