Vegetation Mapping

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PRODUCT DESCRIPTION

Category

• Topographic information
• Impact assessment
• Change detection / continuous monitoring
• Land cover / use
• Near surface geology

• Surface deformation
• Precision ortho-images
• Terrain information
• Water quantity & quality

Uses

• Vegetation mapping
• Vegetation monitoring
• Environmental monitoring – Baseline historic mapping of environment and ecosystems
• Environmental monitoring – Continuous monitoring of changes throughout the lifecycle

Challenges addressed

• Permitting Process – Flora and Fauna
• Closure and Aftercare – Environmental Monitoring

Geo-information needs

• P-9: Characterization of flora and fauna
• CA-2: Characterization of flora and fauna
• CA-6: Demonstrate no impact on special area of conservation; 
• CA-8: Farming activities - confirm a return to baseline conditions for crops/animals 

Description

To understand the environmental impact of mining activities and to get information about rehabilitation criteria, mapping and monitoring of Flora and Fauna in the area of influence of any mining activity is required. Base assessment and monitoring of Flora and Fauna require ground sampling methods. EO can support this activity with vegetation mapping covering land areas as well as underwater areas on a local scale. With various image classification methods, vegetation types can be identified on various scales.

Vegetation Indices (VI) are good indicators used to identify and map different vegetation types. For example, the Normalized Difference Vegetation Index (NDVI) gathers information on the radiances in red- and near-infrared regions. Through the dynamic signals of the NDVI and other indices it is possible to identify particular vegetation groups and dynamic changes. The Enhanced Vegetation Index (EVI) is another example. Compared to the NDVI, it has an improved sensitivity and better responds to structural variations in the canopy.

Vegetation types and changes are detected by using spectral signature, structure or phenology profiles. With the analysis of signatures it is possible to identify various classes, such as different forest, woodland, shrubland, grassland and other vegetation types.

Radar imagery helps to get into depth with mapping forest and land cover. With this data remote sensing is able to map structural attributes such as height, biomass, volume and basal area; monitor changes (deforestation, degradation, reforestation) as well as photosynthetic processes, e.g. growing-season length.

Vegetation stress and changes therein may also be detected with remote sensing through different methodologies, using mainly time series of vegetation indices such as fAPAR (Fraction of Absorbed Photosynthetically Active Radiation), LAI (Leaf Area Index) or the NDVI.

Known restrictions / limitations

Lifecycle stage and demand

Exploration

Environmental Assessment and Permitting

Design, Construction and Operations

Mine Closure and Aftercare

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Exploration:

• Basic information about current flora and fauna that might be affected

Environmental Assessment & Permitting:

• Information to monitor impacts on the environment and highlight good and poor performers

Mine Closure & Aftercare:

• Information about rehabilitation criteria and to monitor the rehabilitation process of environment

Geographic coverage

EARSC Thematic Domain

Domain

PRODUCT SPECIFICATIONS

Input data sources

Commer-cial, on demand

Website

Minimum Mapping Unit (MMU)

Variable, depending on source data resolution. A MMU as small as 0,5 ha is possible using VHR.

Accuracy / constraints

Thematic accuracy:

90 % for vegetation types.

Spatial accuracy:

Sub-pixel accuracy (i.e. <10m for Sentinel products)

Accuracy assessment approach & quality control measures

Accuracy is assessed by comparing class labels in the derived thematic map with ground data from the location. A confusion or error matrix describes the accuracy between derived classes and reference data. Usually, an accuracy of 80–90 % is reached.

Frequency / timeliness

Observation frequency:

Every one or more days, depending on satellite.

Timeliness of delivery:

Within five (working) days of sensing.

Availability

Data from all Sentinel satellites are freely available through the open data policy of the operator ESA (Sentinel-1A since 2014, Sentinel-2A since 2015, Sentinel-1B since 2016, Sentinel-2B since 2017).

Data from Landsat 8 (since 2013) are freely available through the open data policy of the operator USGS.

Delivery / output format

Data type: Vector formats, Raster formats

File format: Geotiff, Shapefile

Further delivery formats: Paper maps, Statistical progress/change report

USE CASE