Remote Sensing Indicators: Land Surface Albedo

DOI

Monthly prediction of Land Surface Albedo in a spatial resolution of 1 km x 1 km based on MODIS and AVHRR datasets. for the prediction of the retrospective albedo values the STARFM algorithm was utilized within a Python environment. All available months are packed into one .zip file which can be (i) downloaded and (ii) extraced using free and open standard software (e.g. 7-zip).

Identifier
DOI https://doi.org/10.58160/gVFecIBpNdRbDiZk
Related Identifier IsSupplementTo https://doi.org/10.58160/gGzexcbDikobkyvK
Metadata Access https://www.radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=datacite&identifier=10.58160/gVFecIBpNdRbDiZk
Provenance
Creator Otte, Insa ORCID logo
Publisher University of Würzburg
Contributor RADAR
Publication Year 2024
Funding Reference Federal Ministry of Education and Research https://ror.org/04pz7b180 ROR 01LG2080A https://foerderportal.bund.de/foekat/jsp/SucheAction.do?actionMode=view&fkz=01LG2080A Verbundprojekt WASCAL WRAP 2.0
Rights Open Access; Creative Commons Attribution 4.0 International; info:eu-repo/semantics/openAccess; https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Representation
Language English
Resource Type Dataset
Format application/x-tar
Discipline Geography; Geosciences; Geospheric Sciences; Natural Sciences
Temporal Coverage 2021-2024