Remote sensing indicators: plant functional types

Abstract: Monthly prediction of 14 Plant Funtional Types (PFTs) in a spatial resolution of 1 x 1 km based on MODIS, AVHRR and GLC FCS30D datasets. For predicting the retrospective PFT values the STARFM algorithm was utilized in a Python environment. All available months are packed into one .zip file which can be (i) downloaded and (ii) extracted using free and open standard software (e.g. 7-zip).

Cite this as

Otte, Insa (2024). Dataset: Remote sensing indicators: plant functional types. https://doi.org/10.58160/dbplhSwMgPrKwjCM

DOI retrieved: 2024

Additional Info

Field Value
Imported on November 28, 2024
Last update November 28, 2024
License CC BY 4.0 Attribution
Source https://doi.org/10.58160/dbplhSwMgPrKwjCM
Author Otte, Insa
Given Name Insa
Family Name Otte
Source Creation 2024
Publishers
University of Würzburg
Production Year 2021-2024
Publication Year 2024
Subject Areas
Name: Other
Additional: Geography

Name: Other
Additional: Remote Sensing

Name: Other
Additional: Climate Modelling

Related Identifiers
Identifier: 10.58160/gGzexcbDikobkyvK
Type: DOI
Relation: IsSupplementTo