| Slums from space—15 years of slum mapping using remote sensing M Kuffer, K Pfeffer, R Sliuzas Remote Sensing 8 (6), 455, 2016 | 421 | 2016 |
| Extraction of slum areas from VHR imagery using GLCM variance M Kuffer, K Pfeffer, R Sliuzas, I Baud IEEE Journal of selected topics in applied earth observations and remote …, 2016 | 171 | 2016 |
| Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing sub-standard residential areas I Baud, M Kuffer, K Pfeffer, R Sliuzas, S Karuppannan International Journal of Applied Earth Observation and Geoinformation 12 (5 …, 2010 | 163 | 2010 |
| The Scope of Earth-Observation to Improve the Consistency of the SDG Slum Indicator C Kuffer, Monika and Wang, Jiong and Nagenborg, Michael and Pfeffer, Karin ... ISPRS International Journal of Geo-Information 7 (11), 2018 | 98 | 2018 |
| The development of a morphological unplanned settlement index using very-high-resolution (VHR) imagery M Kuffer, J Barros, RV Sliuzas Computers, Environment and Urban Systems 48, 138-152, 2014 | 97 | 2014 |
| The temporal dynamics of slums employing a CNN-based change detection approach R Liu, M Kuffer, C Persello Remote sensing 11 (23), 2844, 2019 | 93 | 2019 |
| Urban morphology of unplanned settlements: The use of spatial metrics in VHR remotely sensed images M Kuffer, J Barrosb Procedia Environmental Sciences 7, 152-157, 2011 | 92 | 2011 |
| Machine learning-based slum mapping in support of slum upgrading programs: The case of Bandung City, Indonesia G Leonita, M Kuffer, R Sliuzas, C Persello Remote sensing 10 (10), 1522, 2018 | 89 | 2018 |
| An integrative methodology to improve brownfield redevelopment planning in Chinese cities: A case study of Futian, Shenzhen F Cheng, S Geertman, M Kuffer, Q Zhan Computers, environment and urban systems 35 (5), 388-398, 2011 | 89 | 2011 |
| Because space matters: conceptual framework to help distinguish slum from non-slum urban areas R Lilford, C Kyobutungi, R Ndugwa, J Sartori, SI Watson, R Sliuzas, ... BMJ global health 4 (2), e001267, 2019 | 86 | 2019 |
| Need for an integrated deprived area “slum” mapping system (IDEAMAPS) in low-and middle-income countries (LMICs) DR Thomson, M Kuffer, G Boo, B Hati, T Grippa, H Elsey, C Linard, ... Social Sciences 9 (5), 80, 2020 | 83 | 2020 |
| The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries M Kuffer, DR Thomson, G Boo, R Mahabir, T Grippa, S Vanhuysse, ... Remote sensing 12 (6), 982, 2020 | 77 | 2020 |
| Capturing the diversity of deprived areas with image-based features: The case of Mumbai M Kuffer, K Pfeffer, R Sliuzas, I Baud, M Van Maarseveen Remote sensing 9 (4), 384, 2017 | 73 | 2017 |
| “Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review A Abascal, N Rothwell, A Shonowo, DR Thomson, P Elias, H Elsey, ... Computers, environment and urban systems 93, 101770, 2022 | 70 | 2022 |
| Coupling uncertainties with accuracy assessment in object-based slum detections, case study: Jakarta, Indonesia J Pratomo, M Kuffer, J Martinez, D Kohli Remote sensing 9 (11), 1164, 2017 | 69 | 2017 |
| Identifying a slums’ degree of deprivation from VHR images using convolutional neural networks A Ajami, M Kuffer, C Persello, K Pfeffer Remote Sensing 11 (11), 1282, 2019 | 65 | 2019 |
| Modelling urban traffic air pollution dispersion G Wang, FHM Van den Bosch, M Kuffer ITC 37, 153-158, 2008 | 65 | 2008 |
| A GIS based approach for 3D noise modelling using 3D city models V Kurakula, A Skidmore, H Kluijver, J Stoter, K Dabrowska Zielinska, ... ITC, 2007 | 62 | 2007 |
| Open spaces and risk perception in post-earthquake Kathmandu city SR Shrestha, R Sliuzas, M Kuffer Applied geography 93, 81-91, 2018 | 61 | 2018 |
| Deprivation pockets through the lens of convolutional neural networks J Wang, M Kuffer, D Roy, K Pfeffer Remote sensing of environment 234, 111448, 2019 | 57 | 2019 |
