Results

Public traffic speed data usually cover only some parts of city road networks. In this paper, the authors present a clear framework to estimate missing street-level traffic speeds in Berlin….
A new paper presented at the AGILE 2026 conference investigates how hand-drawn annotations in participatory sketch maps can be automatically extracted and digitized. The authors formulate annotation extraction as an…
This study introduces detour-based indices for alcohol exposure along walking commutes. Survey data estimate detour budgets to assess path-based availability. Results show how different retail regimes affect exposure, informing effective…
This study analyzes five socio-economic factors shaping COVID-19 incidence rates across the 400 German districts. A regression analysis using spatial eigenvector mapping indicates that socio-economic factors might influence incidence less…
Food insecurity projections are a central component of anticipatory action frameworks, particularly in drought contexts. Presented at the AGILE 2026 conference, this paper compares FEWS NET and IPC food insecurity…

Deep Learning (DL) has become a core methodological pillar in remote sensing and GeoAI, enabling large-scale applications such as Land Use Land Cover (LULC) mapping, object detection, and spatiotemporal prediction….

A new Open Access paper published in the volume Geography According to Foundation Models by IOS Press explores how Large Language Models could help design stated-preference studies in urban mobility…

Hidden Energy Poverty (hEP) represents an underestimated form of energy vulnerability in which households consume less energy than required to achieve adequate indoor thermal comfort conditions. This phenomenon is particularly…

Wir haben das Büro verlassen, um die Stadt durch die Augen älterer Menschen zu erleben. Aber bevor wir dazu kommen, möchten wir einen Schritt zurückgehen und erklären, warum. Das Silver…

Leveraging openly available airborne imagery this study presents a scalable framework for automated road pavement crack detection for spatially guided highway-maintenance….
A new study published in Scientific Reports examines the effectiveness of biological larviciding in controlling invasive mosquito populations in Heidelberg, Germany. Using detailed data, the research highlights how treatment effects…

What role does the human-in-the-loop play in AI-assisted mapping? AI-assisted mapping is rapidly changing how geospatial data is created, enabling features to be generated at a scale and speed that…

This blog article was originally posted on Medium by Maciej Adamiak, machine learning expert at HeiGIT. It’s very easy to take many things around us for granted, especially when you live…

The editorial for the special issue of Environment and Planning B: Urban Analytics and City Science delineates the scope of a collection of research articles centering on Urban Artificial Intelligence…

The Silver Ways project is an international research initiative that aims to enhance the walkability and urban mobility of older adults by developing a tailored routing system that goes beyond…

Automatically generated map data has become far more common, reducing the amount of direct human involvement. AI-assisted mapping, where human validation refines machine-generated output, is increasingly used to update crowdsourced…

A recent study within the UndercoverEisAgenten project demonstrates that citizen science can effectively support Arctic permafrost research. Volunteers mapped ice-wedge polygons in Alaska and Canada with high accuracy, enabling geomorphological…

Air pollution caused by fine particulate matter (PM₂.₅) is a major public health concern worldwide. Prolonged exposure to PM₂.₅ is associated with higher rates of cardiovascular and respiratory diseases, which…

Ein neuer globaler Datensatz des HeiGIT (Heidelberg Institute for Geoinformation Technology) ermöglicht es weltweit zwischen befestigten und unbefestigten Straßen mit bisher unerreichter Konsistenz zu unterscheiden. Die aus hochauflösenden Satellitenbildern abgeleiteten Daten…

This study investigates sugarcane farmland abandonment in Rio de Janeiro State, Brazil, employing spatial regression techniques to identify the biophysical and accessibility factors that determine where abandonment occurs at the…