Adversarial validation for quantifying dissimilarity in geospatial machine learning prediction

Dataset

DOI

This data includes all datasets and codes for adversarial validation in geospatial machine learning prediction and corresponding experiments. Except for datasets (Brazil Amazon basion AGB dataset and synthetic species abundance dataset) and code, Reademe.txt explains each file's meaning.

Identifier
DOI	https://doi.org/10.17026/PT/OPPCTP
Metadata Access	https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/PT/OPPCTP

Provenance
Creator	Wang, Yanwen.
Publisher	DANS Data Station Physical and Technical Sciences
Contributor	Wang, Yanwen.; Mahdi Khodadadzadeh; Raul Zurita-Milla
Publication Year	2024
Funding Reference	China Scholarship Council 201804910723
Rights	CC0-1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess	true
Contact	Wang, Yanwen. (University of Twente)

Representation
Resource Type	Dataset
Format	application/x-rar-compressed; application/vnd.openxmlformats-officedocument.wordprocessingml.document; text/plain
Size	505156777; 428448; 6305; 657508458
Version	2.0
Discipline	Earth and Environmental Science; Environmental Research; Geosciences; Natural Sciences