Infrastructure Planning & monitoring
Exposed critical infrastructure, Shodra, Albania 2014 (Source: GeoVille)
This service provides information on infrastructure and its surrounding environment by characterising artificial landscape elements. It provides infrastructure information on licence/project scale (up to 1:5000) based on high to very high resolution satellite imagery.
This product includes all physical infrastructures such as buildings (e.g. hospitals, schools and power stations), roads, railways, power cables, pipelines, airports or train stations. Infrastructure mapping is detailed land use mapping with a specific thematic focus.
Infrastructure maps can be created from optical or radar satellite data, but they often require additional reference information to characterise the actual use of a specific building, or the hierarchical level of roads. The precision and detail of infrastructure information is dependent on the input data resolution.
For precise land use information additional in-situ information is mandatory.
For monitoring of infrastructure a satellite data based baseline mapping of infrastructure is conducted. Afterwards, further satellite data is used to monitor infrastructure and infrastructural changes over time.
Satellites enable the creation of precise surface elevation maps as well as the detection of otherwise invisible ground movement on the scale of just a few millimetres, using radar interferometry. Infrastructure at risk of large-scale subsidence, landslides or faulting can be flagged and avoided by e.g. route planners. The result is improved evaluation of costs and planning of site operations.
For planning of network infrastructure such as power cables or road/rail transport connections, information content may also include:
This product delivers PDF maps or raster/vector digital files that delineate and identify:
Known restrictions / limitations
In the inner and outer tropics frequent cloud cover can be an issue for the production of the maps but may be mitigated by combing radar and optical satellite images. However, there are some features which will be close to impossible to be mapped using radar data. The achievable size of mapped objects is depends on the sensor used and its resolution.
Example: Mapping of small roads with a width of 5 m using 5 m RapidEye data (HR1) is extremely challenging, thus VHR2 data with a resolution below 2 m are needed.
Historical ground movement:
Historical analyses can only be performed where SAR data was acquired. Although a good coverage exists over many areas worldwide, some areas do not have large historical SAR data archives. Furthermore, the density of measurement points identified over areas of vegetation decreases (e.g. pipelines under canopy cover).
Lifecycle stage and demand
Development and Decommissioning:
Geographic coverage and demand
Global coverage and demand.
HC:3201 Assessment of infrastructure placement and effects to the surrounding environment
Input data sources
Optical: VHR1, VHR2, HR1
Radar: VHR1, VHR2, HR1
Obligatory supporting data:
Spatial resolution and coverage
Spatial resolution: 0.5 - 10 m pixel size
Minimum Mapping Unit (MMU)
n/a (the product is directly based on the input data; the smallest unit is one pixel)
Accuracy / constraints
Thematic accuracy: 80-90%
Spatial accuracy: The goal would be one 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 mapped infrastructure.
Frequency / timeliness
Observation frequency: The frequency is constrained by satellite revisit and acquisition, but also processing requirements. While the minimum frequency is technically driven by the revisit cycle of the satellite, the maximum frequency is defined be the customer. Depending on the requirements of the customer the best suitable satellite sensor has to be chosen regarding spatial/spectral resolution as well as revisit frequency. Most of the time, long-term changes are detected in 2 years or longer intervals (frequency can be lower depending on demand).
Timeliness of deliverable: Depending on size of the mapped area, resolution, MMU and number of mapped classes.
Freely available or commercially acquired is depending on the sensor selected.
Delivery / output format
|Peer Reviewer:||Hatfield Consultants|
Maria Lemper; Jan Militzer
Infrastructure Planning & monitoring
# of Pages:
Internal – Project consortium and science partners
External – ESA
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