Key Publications

The list below contains a number of selected key publications. A full list of publications can be found at https://zgis.at/publications.

Havas, C. and Resch, B. (2021) Portability of Semantic and Spatial-temporal Machine Learning Methods to Analyse Social Media for Near-real-time Disaster Monitoring. Natural Hazards (2021). DOI: https://doi.org/10.1007/s11069-021-04808-4.

Stolerman, L.M., Clemente, L., Poirier, C., Parag, K.V., Majumder, A., Masyn, S., Resch, B. and Santillana, M. (2023) Using Digital Traces to Build Prospective and Real-time County-level Early Warning Systems to Anticipate COVID-19 Outbreaks in the United States. Science Advances, https://doi.org/10.1126/sciadv.abq0199.

Havas, C., Wendlinger, L., Stier, J., Julka, S., Krieger, V., Ferner, C., Petutschnig, A., Granitzer, M., Wegenkittl, S. and Resch, B. (2021) Spatio-Temporal Machine Learning Analysis of Social Media Data and Refugee Movement Statistics. ISPRS International Journal for Geo-Information, 10(8), pp. 498, DOI: https://doi.org/10.3390/ijgi10080498.

Petutschnig, A., Resch, B., Lang, S. and Havas, C. (2021) Evaluating the Representativeness of Socio-Demographic Variables over Time for Geo-Social Media Data. ISPRS International Journal for Geo-Information, 10(5), pp. 323, DOI: https://doi.org/10.3390/ijgi10050323.

Ehrhart, M., Resch, B., Havas, C. and Niederseer, D. (2022) A Conditional GAN for Generating Time Series Data for Stress Detection in Wearable Physiological Sensor Data. Sensors, 22(16), 5969, https://doi.org/10.3390/s22165969.
https://www.mdpi.com/1424-8220/22/16/5969/htm

Crivellari, A. and Resch, B. (2022) Investigating Functional Consistency of Mobility-related Urban Zones via Motion-driven Embedding Vectors and Local POI-type Distributions. Computational Urban Science, 2(1), 19, https://doi.org/10.1007/s43762-022-00049-8.
https://link.springer.com/article/10.1007/s43762-022-00049-8

Petutschnig, A., Albrecht, J., Resch, B., Ramasubramanian, L. and Wright, A. (2022) Commuter Mobility Patterns in Social Media: Correlating Twitter and LODES Data. International Journal for Geo-Information, 11(1), 15. DOI: https://doi.org/10.3390/ijgi11010015.
https://www.mdpi.com/2220-9964/11/1/15/htm

Kogan, N.E., Clemente, L., Liautaud, P., Kaashoek, J., Link, N.B., Nguyen, A.T., Lu, F.S., Huybers, P., Resch, B., Havas, C., Petutschnig, A., Davis, J., Chinazzi, M., Mustafa, B., Hanage, W.P., Vespignani, A. and Santillana, M. (2021) An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time. Science Advances, 7(10), eabd6989. DOI: https://dx.doi.org/10.1126/sciadv.abd6989.
https://advances.sciencemag.org/content/7/10/eabd6989

Resch, B., Puetz, I., Bluemke, M., Kyriakou, K. and Miksch, J. (2020) An Interdisciplinary Mixed-methods Approach to Analyzing Urban Spaces: The Case of Urban Walkability and Bikeability. International Journal of Environmental Research and Public Health, 17(19), 6994. DOI: https://doi.org/10.3390/ijerph17196994.
https://www.mdpi.com/1660-4601/17/19/6994/htm

Pykett, J., Chrisinger, B., Kyriakou, K., Osborne, T., Resch, B., Stathi, B., Toth, E. and Whittaker, A. (2020): Developing a Citizen Social Science Approach to Understand Urban Stress and Promote Wellbeing in Urban Communities. Palgrave Communications 6(1), 85, https://doi.org/10.1057/s41599-020-0460-1.

Pykett, J., Osborne, T. and Resch, B. (2020): From Urban Stress to Neurourbanism: How Should We Research City Wellbeing?. Annals of the Association of American Geographers DOI: 10.1080/24694452.2020.1736982.

Doerrzapf, L., Kovács-Gyori, A., Resch, B. and Zeile, P. (2019): Defining and Assessing Walkability: An Integrated Approach Using Surveys, Biosensors and Geospatial Analysis. Urban Development Issues 62, 5-15, DOI: 10.2478/udi-2019-0008.

Kyriakou, K. and Resch, B. (2019): Spatial Analysis of Moments of Stress Derived from Wearable Sensor Data. Adavances in Cartography and GIScience of the ICA 2, 9, DOI: 10.5194/ica-adv-2-9-2019.

Kyriakou, K., Resch, B., Sagl, G., Petutschnig, A., Werner, C., Niederseer, D., Liedlgruber, M., Wilhelm, F.H., Osborne, T. and Pykett, J. (2019): Detecting Moments of Stress from Measurements of Wearable Physiological Sensors. Sensors 19(17), pp. 3805, DOI: 10.3390/s19173805.

Kinne, J. and Resch, B. (2018): Analyzing and Predicting Micro-Location Patterns of Software Firms. ISPRS International Journal of Geo-Information (IJGI) 7(1), pp. 1, DOI: 10.3390/ijgi7010001.

Kounadi, O. and Resch, B. (2018): A Geoprivacy by Design Guideline for Research Campaigns that use Participatory Sensing Data. Journal of Empirical Research on Human Research Ethics 13(3), 203-222, DOI: 10.1177/1556264618759877.

Kounadi, O., Resch, B. and Petutschnig, A. (2018): Privacy Threats and Protection Recommendations for the Usage of Geosocial Network Data in Research. Social Sciences 7(10), pp. 191, DOI: 10.3390/socsci7100191.

Bluemke, M., Resch, B., Lechner, C., Westerholt, R. and Kolb, J.-P. (2017): Integrating Geographic Information into Survey Research: Current Applications, Challenges and Future Avenues. Survey Research Methods 11(3), 307-327, DOI: 10.3390/ijgi7010001.

Resch, B. , Usländer, F. and Havas, C. (2017): Combining Machine-learning Topic Models and Spatio-temporal Analysis of Social Media Data for Disaster Footprint and Damage Assessment. Cartography and Geographic Information Science , 362-376, DOI: 10.1080/15230406.2017.1356242.

Resch, B., Summa, A., Zeile, P. and Strube, M. (2016): Citizen-centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm. Urban Planning 1(2), 114-127, DOI: 10.17645/up.v1i2.617.

Westerholt, R., Steiger, E., Resch, B. and Zipf, A. (2016): Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis. PLOS ONE 11(9), 1-31, doi:10.1371/journal.pone.0162360.

Resch, B., Summa, A., Sagl, G., Zeile, P. and Exner, J.-P. (2015): Urban Emotions – Geo-semantic Emotion Extraction from Technical Sensors, Human Sensors and Crowdsourced Data. In: Gartner, G. and Haosheng Huang (eds.) (2015) Progress in Location-Based Services 2014 , Springer International Publishing, Switzerland, 199-212.

Steiger, E., Resch, B. and Zipf, A. (2015): Exploration of Spatiotemporal and Semantic Clusters of Twitter Data Using Unsupervised Neural Networks. International Journal of Geographical Information Science 30, 1694-1716, DOI: 10.1080/13658816.2015.1099658.

Steiger, E., Westerholt, R., Resch, B. and Zipf, A. (2015): Twitter as an Indicator for Whereabouts of People? Correlating Twitter with UK Census Data. Computers, Environment and Urban Systems 54, 255-265.

Westerholt, R., Resch, B. and Zipf, A. (2015): A Local Scale-Sensitive Indicator of Spatial Autocorrelation for Assessing High/Low Value Clustering. International Journal of Geographical Information Science 29(5), 868-887, DOI:10.1080/13658816.2014.1002499.

Blaschke, T. and Merschdorf, H. (2014): Geographic Information Science as a Multidisciplinary and Multi-paradigmatic Field. Cartography and Geographic Information Science 41(3), 196-213.

Resch, B. (2013): People as Sensors and Collective Sensing – Contextual Observations Complementing Geo-Sensor Network Measurements. In: Krisp, J. (2013) Advances in Location-Based Services, ISBN 978-3-642-34202-8, Springer, Berlin Heidelberg, 391-406.