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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Classified buildings - Dominica, 2025

Authors: Van Westen, Cees;

Classified buildings - Dominica, 2025

Abstract

Science Case Name Multi-hazards in the Caribbean SIDS Dataset Name/Title Classified buildings - Dominica, 2025 Dataset Description Classified buildings using an AI approach for Goodwill, Pichelin and Roseau (partly), this layer includes additional information such as the roof colour and orientation, number of floors and facade colour compared to the building footprint layer in the elements of risk datasets. Key Methodologies Using building footprints from OSM and other sources, merged and classified using an AI approach for Goodwill, Pichelin and Roseau (partly). Temporal Domain Erika: 2015, Maria: 2017, other maps are for the situation in 2025 Spatial Domain Dominica, UTM WGS 84 Zone 20N. Key Variables/Indicators Classified buildings using an AI approach for Goodwill, Pichelin and Roseau (partly) as part of the element of risk datasets. Data Format The data is in Zip format; the zip file contains ESRI Shapefile. Source Data OpenStreetMap, Google OpenBuildings, fieldwork. Accessibility 10.5281/zenodo.13833874 Only freely accessible data is used. Disclaimer – This dataset is provided solely for research purposes. It is based on available data and has not been verified or approved by any local authority. The dataset represents the outcome of the applied methodology and research judgments, and does not reflect the official policies or positions of the authorities of Dominica. Stakeholder Relevance Used for determining which areas are most endangered for floods and landslides, as a basis for early warning and risk-informed planning Limitations/Assumptions Classification of all buildings was difficult, so we used a set of rules, without checking each building individually. Additional Outputs/Information Contact Information C.J. Van Westen (UT-ITC)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average