Data underlying the PhD thesis of Wen Zhou: Deep Learning Methods for Multiple Building Use and Urban Livability Evaluation from Multimodal Geospatial Data

DOI

This dataset includes data and codes underlying the PhD thesis of Wen Zhou: Deep Learning Methods for Multiple Building Use and Urban Livability Evaluation from Multimodal Geospatial Data. This data set contains four research works. Research one is building use and mixed use classification. Research two is hierarchical building use classification considering mixed-use. Research three is impact of building spatial and functional information on Urban Livability. Research four is Urban livability evaluation based upon multimodal deep learning.

Identifier
DOI https://doi.org/10.17026/PT/VFTW9X
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/PT/VFTW9X
Provenance
Creator W. Zhou ORCID logo
Publisher DANS Data Station Physical and Technical Sciences
Contributor A. Stein; C. Persello
Publication Year 2025
Rights CC-BY-NC-ND-4.0; info:eu-repo/semantics/restrictedAccess; http://creativecommons.org/licenses/by-nc-nd/4.0
OpenAccess false
Representation
Resource Type Dataset
Format application/zip
Size 1621779854; 5494723541; 3430733630; 22226466198
Version 1.1
Discipline Earth and Environmental Science; Environmental Research; Geosciences; Natural Sciences