Deep learning-based generation of building stock data from remote sensing for urban heat demand modeling

M Wurm, A Droin, T Stark, C Geiß, W Sulzer… - … International Journal of …, 2021 - mdpi.com
Cities are responsible for a large share of the global energy consumption. A third of the total
greenhouse gas emissions are related to the buildings sector, making it an important target …

Empiric recommendations for population disaggregation under different data scenarios

M Sapena, M Kühnl, M Wurm, JE Patino, JC Duque… - Plos one, 2022 - journals.plos.org
High-resolution population mapping is of high relevance for developing and implementing
tailored actions in several fields: From decision making in crisis management to urban …

Quantifying uncertainty in slum detection: advancing transfer-learning with limited data in noisy urban environments

T Stark, M Wurm, XX Zhu… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
In the intricate landscape of mapping urban slum dynamics, the significance of robust and
efficient techniques is often underestimated and remains absent in many studies. This not …

Peri-urban growth into natural hazard-prone areas: Mapping exposure transformation of the built environment in Nairobi and Nyeri, Kenya, from 1948 to today

A Fekete - Natural Hazards, 2023 - Springer
Kenya experiences massive urban growth, also into natural hazard-prone areas, exposing
settlements and the natural environment to riverine and pluvial floods and other natural …

Cross-border urban change detection and growth assessment for mexican-usa twin cities

A Fekete, P Priesmeier - Remote Sensing, 2021 - mdpi.com
Remote sensing applications of change detection are increasingly in demand for many
areas of land use and urbanization, and disaster risk reduction. The Sendai Framework for …

Efficiency of CNNs for building extraction: Comparative analysis of performance and time

D Stiller, T Stark, V Strobl, M Leupold… - 2023 Joint Urban …, 2023 - ieeexplore.ieee.org
Openly available geodata of buildings are still incomplete or missing for many regions of the
world. Convolutional neural networks (CNNs) have shown to be suitable for building …