prof.dr. M. Kuffer (Monika)

Associate Professor
ITC-PGM
BMS-TPS-CSTM
Langezijds 1301
m.kuffer@utwente.nl
+31534874301
Business card

Monika Kuffer is working as a Professor at the Behavioural, Management and Social Sciences (BMS) as well as at the Faculty of Geo-Information Science and Earth Observation (ITC, University of Twente). My research focuses on sustainable development (SDGs), in particular poverty (deprivation), living quality, and economic development in urban/rural environments using remote sensing, Geographic Information Systems (GIS), and AI-based methods. I co-chair an international network on deprivation area mapping IDEAMAPS and (co) lead several research projects on urban deprivation and environment, e.g., IDEAtlas,  SPACE4ALL, IDEAMAPS Ecosystem, and ONEKANA. I am the project director of two NUFFIC-funded training grants (IDeAMapSudan - Capacity strengthening for gender-responsive and sustainable urban development and DATA4HUMANRIGHTS, Nigeria). I am a Steering Committee Member of the Joint Urban Remote Sensing Event (JURSE), the Dutch representative of the European Association of Remote Sensing Laboratories (EARSeL), SIG chair for Developing Countries, and a member of the Steering Committee: EO for Sustainable Cities and Communities Toolkit.

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Expertise

  • Earth and Planetary Sciences

    • Metropolitan Area
    • Datum
    • Area
    • Cartography
    • Earth
    • Observation
    • Image
    • Investigation

Organisations

Monika Kuffer received her PhD from the University of Twente (NL) and one MSc in Human Geographer (TU Munich), and a second MSc in Geographic Information Science (University of London). She is working as an Associate Professor at the Faculty of Geo-Information Science and Earth Observation (ITC, University of Twente). Her main research foci are urban remote sensing, monitoring deprived areas (e.g., slums), and analyzing urban form and dynamics with remote sensing, spatial statistics, and spatial metrics. Her research is driven by providing spatial information to support planning and decision-making processes in complex cities, toward inclusive, livable, and sustainable cities.

Publications

2024
AI perceives like a local: predicting citizen deprivation perception using satellite imagery, Article 20, 1-14. Abascal, A., Vanhuysse, S., Grippa, T., Rodriguez-Carreño, I., Georganos, S., Wang, J., Kuffer, M., Martinez-Diez, P., Santamaria-Varas, M. & Wolff, E.https://doi.org/10.1038/s42949-024-00156-xDo informal settlements contribute to sprawl in Sub-Saharan African cities?, 105663 (E-pub ahead of print/First online). Kolowa, T. J., Daams, M. N. & Kuffer, M.https://doi.org/10.1016/j.scs.2024.105663Feature-guided deep learning model for mapping deprived areasIn 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. IEEE. Filho, P. S., Tareke, B., Persello, C., Kuffer, M., Maretto, R., Abascal, A., Wang, J. & MacHado, R.https://doi.org/10.1109/MIGARS61408.2024.10544988Monitoring, trends and impacts of light pollution, 417-430. Linares Arroyo, H., Abascal, A., Degen, T., Aubé, M., Espey, B. R., Gyuk, G., Hölker, F., Jechow, A., Kuffer, M., Sánchez de Miguel, A., Simoneau, A., Walczak, K. & Kyba, C. C. M.https://doi.org/10.1038/s43017-024-00555-9Making Urban Slum Population Visible: Citizens and Satellites to Reinforce Slum CensusesIn Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 287-302). Abascal, A., Georganos, S., Kuffer, M., Vanhuysse, S., Thomson, D., Wang, J., Manyasi, L., Otunga, D. M., Ochieng, B., Ochieng, T., Klinnert, J. & Wolff, E.https://doi.org/10.1007/978-3-031-49183-2_14Detection of Unmonitored Graveyards in VHR Satellite Data Using Fully Convolutional NetworksIn Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 167-188). Debray, H., Kuffer, M., Klaufus, C., Persello, C., Wurm, M., Taubenböck, H. & Pfeffer, K.https://doi.org/10.1007/978-3-031-49183-2_9Putting the Invisible on the Map: Low-Cost Earth Observation for Mapping and Characterizing Deprived Urban Areas (Slums)In Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 119-137). Vanhuysse, S., Kuffer, M., Georganos, S., Wang, J., Abascal, A., Grippa, T. & Wolff, E.https://doi.org/10.1007/978-3-031-49183-2_7Urban and Peri-Urban? Investigation of the Location of Informal Settlements Using Two DatabasesIn Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 77-98). Samper, J., Kuffer, M. & Boanada-Fuchs, A.https://doi.org/10.1007/978-3-031-49183-2_5Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning, Article 102075, 102075. Owusu, M., Nair, A., Jafari, A., Thomson, D., Kuffer, M. & Engstrom, R.https://doi.org/10.1016/j.compenvurbsys.2024.102075A Global Estimate of the Size and Location of Informal Settlements, Article 18, 1-17. Boanada-Fuchs, A., Kuffer, M. & Samper, J.https://doi.org/10.3390/urbansci8010018The Impact of Respondents’ Background Towards Slum Conceptualisations and Transferability Measurement of Remote Sensing–Based Slum Detections. Case Study: Jakarta, IndonesiaIn Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 139-166). Springer. Pratomo, J., Pfeffer, K. & Kuffer, M.https://doi.org/10.1007/978-3-031-49183-2_8IntroductionIn Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 1-9). Springer International Publishing. Georganos, S. & Kuffer, M.https://doi.org/10.1007/978-3-031-49183-2_1Urban Inequalities from Space: Earth Observation Applications in the Majority World. Springer Nature. Kuffer, M. & Georganos, S.https://doi.org/10.1007/978-3-031-49183-2
2023
Capturing deprived areas using unsupervised machine learning and open data: a case study in São Paulo, Brazil, Article 2214690. Trento Oliveira, L., Kuffer, M., Schwarz, N. & Pedrassoli, J. C.https://doi.org/10.1080/22797254.2023.2214690Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa, Article 116. Owusu, M., Engstrom, R., Thomson, D., Kuffer, M. & Mann, M. L.https://doi.org/10.3390/urbansci7040116The relationship between multiple hazards and deprivation using open geospatial data and machine learning, 907-941. Kabiru, P., Kuffer, M., Sliuzas, R. & Vanhuysse, S.https://doi.org/10.1007/s11069-023-05897-zMapping the Invisibles: Global urban inequalities through night lightsIn 2023 Joint Urban Remote Sensing Event (JURSE) (pp. 1-4). IEEE. Abascal, A., Kyba, C., Hölker, F., Kuffer, M., Linares Arroyo, H., Walczak, K., De Miguel, A. S., Degen, T. & Roman, M. O.https://doi.org/10.1109/JURSE57346.2023.10144207IDeaMapSudan: Geo-spatial modelling of urban povertyIn 2023 Joint Urban Remote Sensing Event (JURSE) (pp. 1-4). IEEE. Kuffer, M., Ali, I. M. M., Gummah, A., Da Silva Mano, A., Sakhi, W., Kushieb, I., Girgin, S., Eltiny, N., Kumi, J., Abdallah, M., Bad, M., Ahmed, F., Hamza, M., Wang, J., Elzaki, T., Gevaert, C. & Flasse, C.https://doi.org/10.1109/JURSE57346.2023.10144211Monitoring slums and informal settlements in Europe: Opportunities for geospatial and earth observation techniques. Publications Office of the European Union. Kuffer, M., P, P. & A, S.https://doi.org/10.2760/325575%20(online)Three-dimensional modelling of past and present Shahjahanabad through multi-temporal remotely sensed data, Article 2924. Rajan, V., Koeva, M. N., Kuffer, M., Da Silva Mano, A. & Mishra, S.https://doi.org/10.3390/rs15112924EO + Morphometrics: Understanding cities through urban morphology at large scale, Article 104691. Wang, J., Fleischmann, M., Venerandi, A., Romice, O., Kuffer, M. & Porta, S.https://doi.org/10.1016/j.landurbplan.2023.104691Planning walkable cities: Generative design approach towards digital twin implementation, Article 1088. Kumalasari, D., Koeva, M., Vahdatikhaki, F., Petrova Antonova, D. & Kuffer, M.https://doi.org/10.3390/rs15041088Bringing economic complexity to the intra-urban scale: The role of services in the urban economy of Belo Horizonte, Brazil, Article 102837. Magalhães, L., Kuffer, M., Schwarz, N. & Haddad, M.https://doi.org/10.1016/j.apgeog.2022.102837Toward 3D Property Valuation—A Review of Urban 3D Modelling Methods for Digital Twin Creation, Article 2. Ying, Y., Koeva, M., Kuffer, M. & Zevenbergen, J.https://doi.org/10.3390/ijgi12010002Data and urban poverty: Detecting and characterising slums and deprived urban areas in low- and middle-income countriesIn Advanced Remote Sensing for Urban and Landscape Ecology. Springer Nature. Kuffer, M., Abascal, A., Vanhuysse, S., Georganos, S., Wang, J., Thomson, D. R., Boanada, A. & Roca, P.https://doi.org/10.1007/978-981-99-3006-7_1

Research profiles

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

Ongoing research projects on Earth Observation and mapping deprived urban areas: 

The IDEAMAPS Network is developing and maintaining an Integrated DEprived Area MAPping System (IDEAMAPS) that leverages the strengths of our current silo-ed approaches to “slum” area mapping.
More info: https://ideamapsnetwork.org/

ACCOUNT (Accounting for the unaccounted) is developing a machine-learning based framework for estimating the population of invisible spaces in support of the SDG Slum Indicator.
More info: https://slummap.net/index.php/account/ 

The SLUMAP project (Remote Sensing for Slum Mapping and Characterization in sub-Saharan African Cities) is a two-year research project (2019-2021) funded by the STEREO-III programme of the Belgian Science Policy (BELSPO).
More info: http://slumap.ulb.be/ 

IDEAMAPSUDAN (Integrated Deprivation Area Mapping System for Displacement Durable Solutions and socioeconomic reconstruction in Khartoum, Sudan) is implementing a training project in Sudan on Capacity strengthening for gender-responsive and sustainable urban development.
More info: https://slummap.net/index.php/projects-overview/ 

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