Fine-resolution land use/land cover classification of Leipzig in 2012

The dataset contains a land use/land cover classification of Leipzig, Germany, for 2012. It is based on Banzhaf, Ellen; Kollai, Helen (2018): Land use / Land cover for Leipzig, Germany, for 2012 by an object-based image analysis (OBIA) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.895391, with an improved classification of individual trees. Find a class assignment and a QGIS-ready colormap file attached .

Simple

Date (Publication)
2020-10-13
Citation identifier
urn:uuid/68b88e09-8562-4f77-ae77-47d23baa861a

Title

Internal Identifier

Cited responsible party
Role Organisation Electronic mail address
Author

Helmholtz-Centre for Environmental Research UFZ
Status
Completed
Topic category
  • Environment
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)

Extent

N
S
E
W




Temporal extent

Time period
2012-01-01 2012-12-31

Associated resource

Title

Banzhaf, Ellen; Kollai, Helen (2018): Land use / Land cover for Leipzig, Germany, for 2012 by an object-based image analysis (OBIA) [dataset]. PANGAEA

Citation identifier
https://doi.org/10.1594/PANGAEA.895391

Website

https://doi.org/10.1594/PANGAEA.895391

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 incorporates digital orthophotos (DOP), LiDAR data and vital statistics. We used remote sensing techniques to create an Object-based Image Analysis (OBIA) that differentiates grey and green structures with high precision and at a refined scale. This spatial information is linked with allocated population and health-related indicators to identify building types with the highest population densities and local districts lacking in different green structures. Our results show the share of built-up structures and the contribution of green structures to urban ecosystem services, human health and well-being at the local district level.

Association Type
Larger work citation

Digital transfer options

OnLine resource

Dataset Download

Reference system identifier
EPSG/EPSG:25833

Title

EPSG Geodetic Parameter Registry

Website

https://www.epsg-registry.org/

Metadata

Metadata identifier
urn:uuid/68b88e09-8562-4f77-ae77-47d23baa861a

Language
English
Character encoding
UTF8
Contact
Role Organisation Electronic mail address
Point of contact

Helmholtz-Centre for Environmental Research UFZ

Type of resource

Resource type
Dataset
Date info (Revision)
2026-05-18

Metadata standard

Title

ISO 19115-1 Geographic Information - Metadata

Edition

ISO 19115-1:2014 / Amd 1:2018

 
 

Overviews

Spatial extent



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