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  • Product Sheet: Linear disturbance features

Linear Disturbance Features

Image credit: Hatfield Consultants



Component products

Land Use



  • Logistics planning and operations - Baseline mapping of terrain and infrastructure
  • Logistics planning and operations - Support to surveying crews for planning surveys and H&S
  • Logistics planning and operations - Facility siting, pipeline routing and roads development
  • Seismic Planning - Identification of adverse terrain for trafficability
  • Seismic Planning - Identification of environmentally sensitive areas
  • Environmental monitoring - Baseline historic mapping of environment and ecosystems
  • Environmental monitoring - Continuous monitoring of changes throughout the lifecycle

Geo-information requirements

  • Distribution and status of infrastructure
  • Detailed land cover information  
  • Detailed land use information 
  • Precision ortho-images


Linear disturbance products are typically delivered for linear features with a width between 1 and 30 m. The most common linear disturbance in oil and gas development areas is from seismic lines and roads, but can also include pipeline and transmission line corridors associated with a project.

Maps of existing linear infrastructure routes and corridors that may be abandoned or may belong to other operators are important for exploration and development planning and assessment of cumulative environmental effects. Existing linear corridors could be repurposed or shared rather than clearing new routes, both to reduce costs and minimise impacts.

EO data can help to identify existing linear features. Very high resolution EO products can deliver information about the extent and magnitude of disturbance along narrow linear corridors. If the contrast (in spectral response) between these features and the surrounding area is significant, then the centrelines of features smaller than the sensor spatial resolution can still be estimated. Multi-temporal EO data can be used to identify older disturbances and the extent of re-growth.

Linear feature extraction can be optimised using object-based classification methods, and  pre‑existing vector data can be incorporated into the process. Conflation control is required to make corrections where data from multiple sources conflict. Extracted features require topology control and manual verification with editing.

The linear disturbances product delivers centrelines and standardized widths of linear features, and includes coding for feature themes, such as single or double track, surface type, seismic line, etc.

Known restrictions / limitations

  • Cloud cover which affects optical images. Radar data can complement optical data, depending on topography and viewing geometry.
  • Difficulties detecting very narrow linear features such as past seismic lines. Image resolution and canopy closure can limit outputs.
  • Canopy obscured or partially obscured roads, or washed out road segments require manual interpretation which is subject to judgement error.
  • Conflation control can be time-consuming and challenging.
  • LiDAR remains superior to EO methods for detecting very narrow features, or for penetrating vegetation canopy, although costs can be very high.

Lifecycle stage and demand











Pre-license: Knowledge of pre-existing access corridors will facilitate geological and geophysical assessment.

Exploration: Knowledge of pre-existing access corridors will facilitate seismic and site surveys, and appraisals.

Development: Re-development or expansion of existing access corridors will reduce development costs. Wildlife populations are sensitive to linear disturbance density, which may need to be addressed in the environmental impact assessment (and for cumulative effects).

Production: Site security can be enhanced by accounting for pre-existing potential access points.

Decommissioning: Useful for monitoring of re-vegetation along decommissioned access corridors.

Geographic coverage and demand

Demand is global, especially in developing or remote areas where infrastructure maps may not be comprehensive. The mapping and management of cumulative linear disturbance is an important issue in North America.

Challenges Addressed

OTM:013  Flagging environmentally sensitive areas prior to seismic surveys

OTM:037  Identification of road or track for logistics planning

OTM:049  Identifying unregulated overhead power cables

OTM:062  Monitoring revegetation

OTM:070  Understanding security situations

HC:1211  Planning bridging through a tropical forest

HC:1303  Planning heliports, camps, and drop zones in forested areas

HC:4101  Assess fragmentation of natural habitat and cumulative disturbance

HC:4201  Remediation and reclamation monitoring

HC:5305  Identify existing linear routes for co-location of pipelines in wilderness areas


Input data sources

Optical: VHR1, VHR2, HR1, HR2

Radar: VHR2, HR1, HR2

Supporting data: Aerial imagery, LiDAR

Spatial resolution and coverage

Spatial resolution: 0.5-15 m.

Varies depending on input imagery used and client needs. Very high resolution imagery is needed for very narrow feature detection (e.g., seismic lines).

Minimum Mapping Unit (MMU)

Variable, depending on source data resolution. The MMU could be very small (i.e., when derived from very high resolution optical data). Four metres is a typical single-track road width, although minimum feature width (MFW) could be less than two metres (e.g., narrow single-track roads or seismic lines).

Accuracy / constraints

Thematic accuracy: Accurate area estimates for features requires VHR optical data, e.g., within ± 10% of the actual area. Thematic accuracy is dependent on the number of classes being discriminated (road versus single track, multi-track, sealed, gravel, etc.), but recent linear disturbance can be extracted with >90% accuracy if using VHR optical data.

Spatial accuracy: Centrelines of features can be determined within 1-2 pixels.

Accuracy assessment approach & quality control measures

Topology of output vectors to be checked and cleaning to be performed. Automatic centreline correction for features of known width, and visual assessment with manual corrections for all linear features. Limited ground survey and comparison to ancillary vector data. Vegetation type and/or structural information would require field vegetation assessment survey.

Frequency / timeliness

Observation frequency: One baseline feature collection is needed. An additional yearly snapshot during the reclamation process supports monitoring activities.

Timeliness of delivery: Imagery and elevation can be acquired quickly. Data processing can be completed in near real time (< 24 hours) for detection of most easily visible linear disturbances (e.g., roads).  The processing of data for more challenging areas (e.g., very narrow historic seismic lines) requires professional/expert interpretation and is typically a consulting assignment of weeks to months.


On-demand availability from commercial suppliers.

New acquisitions can be requested globally.

Delivery / output format

Data type:

  • Vector linear features as centrelines and polygon or double-line polylines.

File format:

  • Shapefile or client-specified common spatial formats.

Download product sheet.



Lead author:

Hatfield Consultants/SRC

Peer reviewer:



Barry Pierce

Document Title:

Linear Disturbance Features

# of Pages:



Internal – Project consortium and science partners


External – ESA

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