Child pages
  • Product Sheet: Urban Settlement

Urban & settlement map


Land use and building structure, Prey Veng, Cambodia 2011 (GeoVille/ESA/SOS Children Village)



Component products

Land Use


  • N/A



  • Environmental monitoring – Baseline historic mapping of environment and ecosystems
  • Environmental monitoring – Continuous monitoring of changes throughout the lifecycle
  • Logistics planning and operations – Monitoring of assets
  • Logistics planning and operations – Facility siting, pipeline routing and roads development

Geo-information requirements

  • Detailed land use information
  • Distribution and status of assets
  • Distribution and status of infrastructure


The product provides mapping of urban areas in terms of land cover and land use, as well as the associated temporal changes based on high to very high resolution optical or radar satellite data.

Based on this, the product can provide various urban indicators, as well as infrastructure and building inventories based on construction classes. Typical artificial surface land cover/use classes used in the classification follow the established nomenclatures (CORINE, MOLAND, FAO LCCS, etc.).

Mapping can include:

  • Building inventory on building or block level. Besides building footprints, general uses as e.g. residential housing, industrial, public services can be assigned to urban structures as for example building heights derived from ancillary geospatial data (e.g. LIDAR surface height data).
  • Infrastructure mapping including all anthropogenic structures such as roads, railways, gas pipelines or overhead power cables (depending on data resolution)
  • Vegetation cover and water areas including its use within the urban context (recreation areas, parks, adjacent forests, dredging lakes, ponds, etc.)
  • Sealing/imperviousness degree map, which indicates the housing density of urban settlements and permeability of urban surfaces.

In the case of building inventories, only part of the building information can be captured, depending on the sensors used for data acquisition. Very high resolution optical sensor imagery makes it possible to estimate building footprints, building location, distance from building to building, building height classes (using stereo image pairs). Other features, such as building height as number of storeys, building material, structure type, load bearing structure system, construction technique, floor area, are more difficult to capture or must be inferred from other contextual information.

Using multi-temporal image information, the product is particularly relevant for monitoring urban expansion. Furthermore, the products serve as a starting point for a range of urban indicators for soil protection and management as well as the monitoring of crucial water supply systems, urban structures, and flood risk control.

While the EO products rarely achieve the accuracy of cadastral data, their accuracies are sufficiently high to form an objective basis for decision-making and enable continuous monitoring over time.

Known restrictions / limitations

A potential limitation of urban and settlement mapping is a high presence of cloud coverage within the analysis region, as optical satellite data is not capable of penetrating clouds. Potential approaches mitigating this issue could be:

1)     combining optical and VHR SAR data as they are able to penetrate cloud coverage;

2)     using VHR SAR stereo data to produce a nDSM (normalized Digital Surface Model) to support optical classification.

Urban and settlement mapping is also limited by the resolution of the input data used. Structures smaller than double the resolution of the input data cannot be mapped.

Lifecycle stage and demand











Pre-licensing & Exploration:

  • Selecting an appropriate development site for an onshore facility is a complex task.  The site needs to be accessible, safe, connect to local O&G infrastructure (if any) and have limited impact on the environment.
  • New developments can require relocation of communities and existing infrastructure. The value of the occupied land for compensation / purchase needs to be made at a particular time and day, and needs to be supported by documentary evidence relating to the status of the area at the given time and date.
  • Being aware of the location or patterns of tribes in remote areas allows to more sensitively plan exploration activities.

Development, Production & Decommissioning

  • Monitoring the social implications of O&G development during development and production phase, e.g. changes in land use or impacts caused by construction activity, allow highlighting areas of success and improvement.

Geographic coverage and demand

In general, the products are independent and up-to-date, available practically around the globe. The demand is global, focusing on urban or densely populated areas.

Challenges Addressed

OTM:024 Urban encroachment on O&G assets

OTM:028 Land use mapping to detect the social impact of O&G developments

OTM:035 Assessing the social impact of construction work

OTM:036 Geohazard exposure analysis

OTM:039 Selection of development sites

OTM:063 Resettlement assessment

OTM:065 Floodplain mapping

OTM:072 Monitoring flash floods

OTM:075 Creating basemaps in politically challenging regions


HC:1201 Identify up-to-date general land use patterns to plan access and apply safe setback distances

HC:1208 Identify optimal seasonal land use to reduce permitting costs - in particular commercial and subsistence farming practices

HC:1209 Identify land parcel boundaries for impact compensation

HC:2401 Identify geohazards and landscape change rates

HC: 4103 Social baseline information to support compensation and/or resettlement


Input data sources

Optical: VHR1, VHR2, HR1

Supporting data:

  • Digital elevation models (DEM) – optical VHR1 or radar based VHR2 nDSM or LiDAR nDSM
  • Existing  GIS data such as infrastructure and assets
  • Local knowledge

Spatial resolution and coverage

The spatial resolution of most products can reach a few meters depending on the input imagery resolution.

Spatial resolution: < 10 m, but urban mapping can also be performed over extensive areas with 20 m, 30 m or even 100 m resolution.

Minimum Mapping Unit (MMU)

The MMU is depending on the input data resolution, the mapped objects and the accuracy required.

For optical satellite data with 0.5m spatial resolution this can be, for example, a MMU of 9 m².

Accuracy / constraints

The geometric accuracy is usually comparable to the spatial resolution of the input satellite data, i.e. typically a few metres. The thematic (classification) accuracy is in the range of 80–90% depending on the quality of the EO data.

Limits for mapping are always given by great off-nadir look angles and sun shadows.

Thematic accuracy: 80-90% in areas of low vegetation cover and density. Higher accuracies can be reached with manual extraction of features.

Spatial accuracy: The goal would be 1 pixel, but depends on reference data.

Accuracy assessment approach & quality control measures

Stratified random points sampling approach utilizing VHR reference or other geospatial in-situ data. Statistical confusion matrix with user’s, producer’s accuracy and kappa statistics for urban areas.

Frequency / timeliness

Observation frequency: The frequency is constrained by satellite revisit and acquisition, but also processing requirements. Depending on the requirements of the customer the most suitable satellite sensor has to be chosen considering spatial / spectral resolution as well as revisit frequency.

Timeliness of delivery: Depends on size of the mapped area, resolution, MMU and number of mapped classes.  Automatic procedures may extract urban areas fast but more advanced analysis will require more time. Some analysis using stereo images are time consuming and may require dedicated operators to perform manual work.


Freely available or commercially acquired is depending on the sensor selected.

Delivery / output format

Data type:

  • Raster or vector (depending on customer needs),

For detailed land use information the use of vector data would be superior to raster data, as multiple raster files would be necessary to convey the same information. Furthermore vector data are capable of keeping more complex information as raster data.

File format:

  • Geotiff or shapefile (standard - any other OGC standard file formats)

Download product sheet.

Lead Author:GeoVille
Peer Reviewer:Hatfield Consultants


Maria Lemper, Jan Militzer

Document Title:

Urban & settlement map

# of Pages:



Internal – Project consortium and science partners


External – ESA



This page has no comments.