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Vegetation/Forest Type

 

Forest type, Turkey 2012 (Source: GeoVille/EEA)

 

PRODUCT DESCRIPTION

Category

Component products

Land Cover

 

  • N/A

 

Uses

  • 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
  • Terrain information
  • Critical habitat identification

Description

This product provides the classification of different types of vegetation (e.g. grassland, shrubs, peat land, forest, steppe and savannah) based on optical satellite imagery. This product can also focus on the classification of different types of bushes and forest, as well as the quantification of any changes that may have occurred between the acquisitions of at least two satellite images, as forest monitoring has become more and more important in applications such as REDD+ monitoring.

Forest type maps:  

Forest type maps are in-depth examinations of the forest categorizing the forest into deciduous/broadleaved, coniferous forests and mixed forest. Besides this generic classification, individual tree species such as pine, bamboo, or palm trees can be mapped. Base / surficial geology and elevation are important additional determinants of forest type.

Known restrictions / limitations

In tropical rain forest areas frequent cloud cover can be an issue for the production of the maps, but can be mitigated by combing radar and optical satellite images.

Level of detail in forest type class often demanded by foresters/ecologists requires significant ground data collection.

Volume classes typically quite broad. It is challenging to determine forest biomass/volume for tropical forests.

Lifecycle stage and demand

Pre-licensing

Exploration

Development

Production

Decommissioning

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Pre-licensing & Exploration:

  • Information on vegetation and forest type affects the planning of a seismic survey. Vegetation clearance demands time and resources, and increases health and safety exposure. Forest roads/trails can be impassable in different seasons and/or be in poor condition. Knowing access limitations and potential ground conditions is therefore an important factor in planning effective seismic operations. Efficiently moving both equipment and people around is critical to completing a project on schedule. 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.

Development, Production & Decommissioning:

  • Identify and assess vegetation and forest structure and quality is an important input to mapping habitat and managing potential environmental impacts. Mapping forest quality in a consistent manner is challenging, e.g. pristine vs. degraded forests. This increases the uncertainties and risks that all important habitats have been identified and characterized.

Geographic coverage and demand

Demand and coverage is global.

CHALLENGES ADDRESSED

OTM:029 Pre-licensing site selection

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

PRODUCT SPECIFICATIONS

Input data sources

Optical: VHR1, VHR2, HR1, HR2

Radar data supporting optical: VHR1, VHR2, HR1, HR2 (radar)

Supporting data:

  • Geology
  • Elevation
  • Existing land cover information for calibration and validation (ground surveys, hydrographic features, road infrastructure, etc.)

Spatial resolution and coverage

Spatial resolution: 1 - 30 m pixel size

Minimum Mapping Unit (MMU)

The MMU is dependent on the input data resolution, the mapped objects and the accuracy to be achieved. Monitoring forest stands, typically hectares to km² at a time.

For optical satellite data with 4 m spatial resolution a MMU of 256 m² can be achieved for example.

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 vegetation/forest type.

Frequency / timeliness

Observation frequency: Produced locally or regionally, normally on a 3 to 5 year basis (frequency can be lower or higher depending on demand)

Timeliness of deliverable: Dependent on size of the mapped area, resolution, MMU, and number of mapped classes.

Availability

Freely available or commercially acquired depending on the sensor selected.

Delivery / output format

Data type:

  • Vector formats
  • Raster formats (depending on customer needs)

File format:

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

 


 Download product sheet.

 

Lead Author:GeoVille
Peer Reviewer:Hatfield Consultants

Author(s):

Maria Lemper; Jan Militzer

Document Title:

Vegetation/ForesT Type

# of Pages:

4

Circulation:

Internal – Project consortium and science partners

 

External – ESA

 

 

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