| Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters MR Desjardins, A Hohl, EM Delmelle Applied geography 118, 102202, 2020 | 383 | 2020 |
| Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States A Hohl, EM Delmelle, MR Desjardins, Y Lan Spatial and spatio-temporal epidemiology 34, 100354, 2020 | 161 | 2020 |
| Accelerating the discovery of space-time patterns of infectious diseases using parallel computing A Hohl, E Delmelle, W Tang, I Casas Spatial and spatio-temporal epidemiology 19, 10-20, 2016 | 43 | 2016 |
| Social media mining under the COVID-19 context: Progress, challenges, and opportunities X Huang, S Wang, M Zhang, T Hu, A Hohl, B She, X Gong, J Li, X Liu, ... International Journal of Applied Earth Observation and Geoinformation 113 …, 2022 | 42 | 2022 |
| Geovisualization of COVID-19: State of the Art and Opportunities Y Lan, MR Desjardins, A Hohl, E Delmelle Cartographica: The International Journal for Geographic Information and …, 2021 | 35 | 2021 |
| Uncertainty in geospatial health: challenges and opportunities ahead EM Delmelle, MR Desjardins, P Jung, C Owusu, Y Lan, A Hohl, C Dony Annals of epidemiology 65, 15-30, 2022 | 31 | 2022 |
| Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic: an update A Hohl, E Delmelle, M Desjardins Sigspatial Special 12 (1), 27-33, 2020 | 29 | 2020 |
| Computationally enabled 4D visualizations facilitate the detection of rock fracture patterns from acoustic emissions A Hohl, A D. Griffith, MC Eppes, E Delmelle Rock Mechanics and Rock Engineering 51 (9), 2733-2746, 2018 | 25 | 2018 |
| Spatiotemporal Point Pattern Analysis Using Ripley’s K Function A Hohl, M Zheng, W Tang, E Delmelle, I Casas Karimi & Karimi: Geospatial Data Science: Techniques and Applications, 155-175, 2017 | 25 | 2017 |
| SPATIOTEMPORAL DOMAIN DECOMPOSITION FOR MASSIVE PARALLEL COMPUTATION OF SPACE-TIME KERNEL DENSITY A Hohl, E Delmelle, W Tang ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2015 | 19 | 2015 |
| A space–time parallel framework for fine-scale visualization of pollen levels across the Eastern United States MR Desjardins, A Hohl, A Griffith, E Delmelle Cartography and Geographic Information Science 46 (5), 428-440, 2019 | 16 | 2019 |
| Go with the flow: geospatial analytics to quantify hydrologic landscape connectivity for passively dispersed microorganisms A Hohl, T Václavík, RK Meentemeyer International Journal of Geographical Information Science 28 (8), 1626-1641, 2014 | 15 | 2014 |
| Parallel space-time kernel density estimation E Saule, D Panchananam, A Hohl, W Tang, E Delmelle 2017 46th International Conference on Parallel Processing (ICPP), 483-492, 2017 | 13 | 2017 |
| Modeling spatiotemporal associations of obesity prevalence with biking, housing cost and green spaces in Chicago, IL, USA, 2015–2017 A Hohl, A Lotfata Journal of Transport & Health 26, 101412, 2022 | 8 | 2022 |
| Detecting space–time patterns of disease risk under dynamic background population A Hohl, W Tang, I Casas, X Shi, E Delmelle Journal of geographical systems 24 (3), 389-417, 2022 | 8 | 2022 |
| Spatial distribution of hateful tweets against Asians and Asian Americans during the COVID-19 pandemic, November 2019 to May 2020 A Hohl, M Choi, AJ Yellow Horse, RM Medina, N Wan, M Wen American journal of public health 112 (4), 646-649, 2022 | 7 | 2022 |
| Investigating spatiotemporal indoor contact patterns using ABM and STKDE M Choi, A Hohl Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoSpatial …, 2021 | 7 | 2021 |
| Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns A Hohl, I Casas, EM Delmelle, W Tang GIScience 2016, Montreal, Canada, 2016 | 6 | 2016 |
| Spatial association of respiratory health with social and environmental factors: case study of Cook County, Illinois, USA A Lotfata, A Hohl Cities & health 6 (4), 791-803, 2022 | 5 | 2022 |
| Spatiotemporal simulation: local Ripley's K function parameterizes adaptive kernel density estimation A Hohl, P Chen Geosim’19: 2nd ACM SIGSPATIAL International Workshop on Geospatial Simulation, 2019 | 5 | 2019 |
Eric DelmelleDrexel University; Vrije Universiteit BrusselBestätigte E-Mail-Adresse bei drexel.edu
