Fine-resolution land use/land cover classification of Leipzig in 2023

The dataset contains a land use/land cover (LULC) classification of Leipzig, Germany, for 2023. It is a follow-up on the dataset for 2012 https://doi.org/10.25870/1fv3-6e91 and 2018 https://doi.org/10.25870/chba-j214 using the identical LULC classes. Find a class assignment and a QGIS-ready colormap file attached .

Date (Publication): 2026-06-19

Citation identifier

urn:uuid/6996aaed-0555-460a-8a96-45ef9c951935

Title: Internal Identifier

Citation identifier

doi/https://doi.org/10.25870/7w6z-jf52

Title: DataCite

Website

https://datacite.org

Cited responsible party

Role	Organisation	Electronic mail address
Author	Helmholtz-Centre for Environmental Research UFZ

Status: Completed

Topic category

Environment

Extent

Temporal extent

Time period: 2023-01-01 2023-12-31

Keywords

Leipzig
LULC
remote sensing
land use
land cover
OBIA
object based
Urban
ALKIS

Resource constraints

Access constraints: License

Other constraints: Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

Associated resource

Title: Elze, Sebastian (2026): Fine-resolution land use/land cover classification of Leipzig in 2018

Citation identifier: https://doi.org/10.25870/chba-j214

Website

https://doi.org/10.25870/chba-j214

Mapping urban structures is a vital prerequisite for urban planners to enhance their databases for liveable cities dedicated to sustainable development. Therefore, it is important to measure urban grey and green structures at the scale of local districts to understand the urban structure and residential needs for urban ecosystem services. Our detailed analysis is a follow-up on the 2012 dataset (https://doi.org/10.25870/1fv3-6e91) and 2018 dataset https://doi.org/10.25870/chba-j214 and distinguishes between the same LULC classes. For a comparison between 2012 and 2018 and further analysis, see the publication Elze, S. & Banzhaf, E. (2022): High-precision monitoring of urban structures to understand changes in multiple ecosystem services, https://doi.org/10.1016/j.ufug.2022.127616.