This data publication provides the OpenBuildingMap dataset, organized per zoom-level 6 Quadkey. The dataset provides information about the occupancy and height of individual buildings. The main purpose of this data collection is risk assessment for natural hazards, however it can be used by anyone in need of a building exposure dataset.
Buildings play a critical role in understanding human settlement patterns and are essential for applications such as crisis management, urban planning, energy efficiency, and multi-hazard risk assessment. To address the need for comprehensive and accessible global building data, we introduce a dataset containing 2.7 billion building footprints, enriched with structured attributes such as occupancy type and height information classified using the GEM Building Taxonomy. This dataset is derived from the integration of the AI-derived Open Buildings and the Global ML Building Footprints datasets, and the crowdsourced OpenStreetMap, hence creating the most detailed and extensive building dataset to date. The quality of the dataset has been researched using intrinsic quality checks and external reference datasets, including cadaster data and the Global Human Settlement Layer. It is provided as a GeoPackage, to ensure it is easily accessible.
This work has received funding from the European Union thought the Geo-INQUIRE project (GA 101058518), within the Research Infrastructures Programme of Horizon Europe.
This data publication provides a European assessment of building exposure, organized country-by-country. The dataset provides information about the number of buildings; the number of occupants; structural information and structural costs of buildings per geographical area. The main purpose of this data collection is risk assessment for natural hazards, however it can be used by anyone in need of a building exposure dataset.
The data holds information about single buildings, with global estimates of built-up area on 10m x 10m pixels and exposure information per district. All OpenStreetMap (OSM) buildings existing in an OSM excerpt from 1 July 2023, 00:00 UTC (OpenStreetMap contributors, 2023), all buildings from the Global ML Building Footprint (GMLBF, Microsoft, 2023) dataset have been processed and for each building the occupancy type and number of stories have been identified based on data in OSM, such as land use and points of interest. The Global Human Settlement Built-up Characteristics 2022A Layer has been used as initial distribution of built area (Pesaresi, 2022). Aggregated exposure information, including the structural information and the number of occupants, stems the ESRM20 (Crowley et al., 2020).
The resulting dataset is distributed per country as an SQLite/SpatiaLite database. Each database contains three tables and one view. The database is organized around three key concepts, that each have their own table. An Entity is a geographical unit that contains exposure. In this dataset, the entities are tiles in a multi-resolution grid, according to the Quad tree structure (Finkel & Bentley, 1974), with the tiles projected using the Web Mercator projection (EPSG:3857). The zoom-level of the Quadkeys inside the grid varies from level-15 to level-18, depending on the number of buildings inside each tile to preserve privacy-sensitive information. Practically, the size of the tiles varies between around 100m x 100m and 1km x 1km. Each entity consists of one or more Assets, defining the number of buildings of a particular structural type and their population and structural value. The structural type is described using a taxonomy string, describing for example structural properties, occupancy type and the expected number of stories. The exact definition of a taxonomy that is used in this dataset is described in the GEM Building Taxonomy v2.0 (Brzev et al., 2013). On top of the tables, one key view has been defined too. A view is essentially a query on the table that give some insights into the data. The `key_values_per_tile` provides the total number of buildings, total number of occupants at night and total structural costs summed over all assets in one tile entity.
This work has received funding from the European Union thought the Geo-INQUIRE project (GA 101058518), within the Research Infrastructures Programme of Horizon Europe.
TS-GAUSS is a toolbox including (i) software and (ii) datasets for instant calculations of tsunami time-series for an arbitrary seismic source at pre-selected coastal locations. The toolbox exploits the concept of the surface Green's functions (Molinari et al., 2016; https://doi.org/10.5194/nhess-16-2593-2016) and consists of the two consequent steps: (1) ruptGen code to simulate initial tsunami conditions for an arbitrary seismic source and (2) code to make linear combination of the pre-computed Gaussian Green's functions. Correspondingly, TS-GAUSS toolbox also includes datasets of Green's functions for selected geographical regions to download.
This work has received funding from the European Union thought the Geo-INQUIRE project (GA 101058518), within the Research Infrastructures Programme of Horizon Europe.
This dataset presented herein originates from the JAGUARS (The Japanese German Underground Acoustic Emission Research in South Africa) project, which took place from 2007 to 2009 in Mponeng Gold Mine, South Africa. Project partners included Ritsumeikan University, Earthquake Research Institute University of Tokyo and Tohuku University in Japan, the German Research Center for Geosciences Potsdam and Gesellschaft für Materialprüfung und Geophysik GMuG mbH in Germany, as well as the Council for Scientific and Industrial Research in Johannesburg, Seismogen CC in Cartonville, Anglo Gold Ashanti Ltd and the Institute of Mining Seismology in the Republic of South Africa. This publication forms part of the Geo-INQUIRE initiative (HORIZON-INFRA-2021-SERV-01 call, project number 101058518).
It is cross-referenced on the EPISODES Platform (https://episodesplatform.eu/?lang=en#episode:JAGUARS (not yet existing)), which is managed by the EPOS TCS AH (European Plate Observing System Thematic Core Service Anthropogenic Hazards). Within the EPISODES Platform, the datasets are consolidated into an “episode” titled “JAGUARS: Mining induced picoseismicity associated with gold mining”. The EPISODES Platform offers open access to the integrated research infrastructures of the EPOS TCS AH, enabling users to download data and utilize a range of basic online visualization tools to graphically represent and process the datasets directly within their personal workspace.