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  • Product Sheet: Tree Height

Tree Height

Global map shows forest canopy height in shades of green from 0 to 70 meters (Source: NASA)



Component products

Land Cover


  • N/A



  • Seismic Planning – Identification of adverse terrain for trafficability
  • Environmental monitoring – Baseline historic mapping of environment and ecosystems
  • Environmental monitoring – Continuous monitoring of changes throughout the lifecycle
  • Environmental monitoring – Natural hazard risk analysis

Geo-information requirements

  • Detailed land cover information
  • Topographic information (optional, although this is the DTM surface)


This product provides information on tree heights in tropical and boreal forests. The EO techniques use stereo data to produce a digital surface model (DSM) and digital terrain model (DTM), which are then combined to derive a normalised digital surface model (nDSM), which shows the height of all features above the Earth's surface. Land cover classification techniques are used to distinguish forest from other elevated land cover/use classes (e.g. shrubs or build-up) and the height of various landscape features (trees, shrubs, etc.) is calculated.

Tree height information can be used as a component to determine forest above-ground biomass. Furthermore, tree heights can be plugged into models that predict the spread and behavior of fires, as well as ecological models that help to understand the suitability of species to specific forests.

Known restrictions / limitations

Tree height or canopy height information is a standard forestry parameters. Input data sources are optical stereo data or a combination of optical (single image) and radar (stereo image). In tropical rain forest areas, frequent cloud cover can be an issue for deriving the forest cover information. If optical stereo data for generation of DSM, DTM and nDSM are used, the effects of clouds, cloud shadows as well as shadow areas caused by terrain, can lead to missing elevation information and this must be considered.  LiDAR is the standard approach to derive this information as it delivers more accurate height information.

Lifecycle stage and demand











Pre-Licensing, Exploration & Development:

  • Information on forests effects the planning of a seismic survey and may also factor as a consideration as part of a licence area’s feasibility assessment e.g. is it practical to develop a densely forested or jungle area? And also as part of an environmental baseline exercise.
  • Vegetation clearance demands time, finance and increases health and safety exposure. Forest roads/trails can be impassable in different seasons and be in poor condition. Knowing access limitations and potential ground conditions is therefore an important factor in planning effective seismic and logistics operations. Efficiently moving both equipment and people around is critical to completing a project in good speed. In addition, from a safety perspective, being able to map emergency response times and how (and what type of transport/vehicle) to get from a particular point to any point within the working area may prove critical in a safety of life situation.


  • Following decommissioning, tree height can provide an indication of ecosystem recovery and therefore the rate at which this occurring.

Geographic coverage and demand

Demand is global, in regions with dense forest cover.


OTM:029 Prelicensing site selection
OTM:030 Ecosystem valuation of potential site
OTM:032 Detecting ecosystem damages
OTM:033 Mapping of environmental degradation (change)

HC:1204 Assess forest characteristics to plan access and assess hazards


Input data sources

Optical: VHR1, VHR2, HR1

Radar: VHR1, VHR2, HR1

Supporting data:

  • In-situ information for calibration and validation

Spatial resolution and coverage

Spatial resolution: 2 - 30 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

The geometric accuracy is less than 1 pixel which in the case of tree cover density is on the order of 2-30 m.

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 and producer’s accuracy as well as kappa statistics for tree height.

Frequency / timeliness

Observation frequency: The frequency is constrained by satellite revisit and acquisition timeframes, but also processing requirements. Depending on the requirements of the customer, the most suitable satellite sensor has to be selected considering spatial / spectral resolution as well as revisit frequency.  Typically, long-term changes are detected on a 3 to 5 year basis.

Timeliness of delivery: Depending on size of the mapped area, resolution, MMU.


VHR1, VHR2 and HR1 data must be commercially acquired.

Delivery / output format

Data type:

  • Raster formats

File format:

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

Download product sheet.


Lead Author:


Peer Reviewer:

Hatfield Consultants


Maria Lemper; Jan Militzer

Document Title:

Tree height

# of Pages:



Internal – Project consortium and science partners


External – ESA


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