Successful reclamation relies on the ability to create consistent and repeatable maps of disturbances and how they change over time. The COSIA As-Built Footprint Dataset (project code: LE0002) exists to quantify and characterize the footprint of oil and gas-related activities throughout the Oil Sands Region. It is built from other datasets, including the fundamental Alberta Biodiversity Monitoring Institute (ABMI) Human Footprint Map. 

The resulting map provides spatially accurate industry-specific data including footprint feature, disposition number, owner/creator, unique well identifier, approval number, status, product type, well type, road class, and reclamation status. This makes it an essential planning tool underlying all COSIA restoration initiatives. 

For more information on the (ABMI) Human Footprint Map:

• https://abmi.ca/abmi-home/what-we-do/land-cover-and-land-use-mapping/human-footprint-mapping.html
• https://abmi.ca/data-portal/82.html
• https://www.cclmportal.ca/resource/blog-canadian-scientists-collaborate-map-biodiversity-and-human-footprint

ABMI’s field and geospatial monitoring programs have also produced other datasets including their Digital Integrated Dispositions Application (disposition types and ownership information), Alberta Energy Regulator well sites, pipelines, and wildlife and biodiversity monitoring. 

(Other ABMI project codes include: LE0039, LJ0189, LE0008, LE0088).

A database and modelling tool known as the Landscape Ecological Assessment and Planning (LEAP) Framework (project code: LJ0070) is helping COSIA member companies better understand how reforestation and reclamation work undertaken today will impact the health of tomorrow’s boreal forest. LEAP uses location data of oil and gas leases, forest types, lakes, watercourses, and other landscape features to target where and how conservation and reclamation efforts can have the greatest impact. It also allows planners to visually project what current reclamation and reforestation areas will look like 10, 20 and even 50 years down the road. 

Spanning across 3.7 million hectares of Alberta’s boreal forest, this tool is helping address widespread reclamation challenges. LEAP can help indicate which disturbed areas will benefit the most from revegetation efforts which is critical when resources are limited, and impacts must be maximized. Although the amount of land disturbed by oil and gas operations is a relatively small percentage of the total area, linear disturbances like seismic lines and pipeline corridors can have a high cumulative impact because of forest fragmentation — affecting wildlife habitat, particularly for woodland caribou. LEAP is helping to turn fragmented landscapes into restored, functioning ecosystems where wildlife and industry coexist. 

Other LEAP projects include: LL0094, LL0096, LL0103, and LJ0234

Read more about LEAP: https://www.silvacom.com/news/assessing-linear-restoration-ecosystem-service-benefits

Managing environmental footprints requires up-to-date inventories and landscape classifications. Traditional field-based landscape mapping is labour intensive, expensive, and time consuming. Light detection and ranging (LiDAR) and remote sensing technologies are fundamentally improving how practitioners inventory, monitor, and manage environmental footprints. These tools reduce labor-intensive field surveys, replacing them with efficient, high-resolution data collection techniques that enable landscape-scale decision-making.

LiDAR-based workflows have been successfully implemented in a variety of projects including: 

• The Surface Water Assessment and Mapping Project (SWAMP) (project code: LL0016) that was developed to address gaps in provincial water data. The project uses LiDAR, digital elevation models, and high-resolution imagery to accurately predict the location of small, previously unmapped streams. The model enables managers to reduce the hydrological impacts of stream crossings through optimized access routes. These mitigations help reduce regulatory delays and bring down maintenance and liability costs. Inquire internally to access Cenovus’s GIS technical manual for SWAMP.
• Similarly, a LiDAR-based Wet Areas Mapping (WAM) tool (project code: LL0053), originally developed for forestry applications, has been successfully adapted to support a broader range of operations, including oil sands, through a partnership between Devon and the University of New Brunswick. Implementation of the WAM process using LiDAR digital elevation models (DEMs) produces consistent, high-resolution maps of soil drainage, vegetation type, and hydrological connectivity, enabling “surprise-free” field operations. This tool helps optimize land-use decisions, minimize infrastructure impacts, and improve environmental planning under changing climatic and hydrological conditions.
• Beyond hydrology, LiDAR can also map disturbances and vegetation regrowth (project code: LJ0268). This workflow uses vegetation field data and remotely sensed map data to produce vegetation height and cover metrics. This height and cover data can in turn be used for reclamation planning on a range of disturbance types and ecological site conditions. These maps can be used to describe access and line of sight conditions, determine which habitats regenerate best naturally, and determine where restoration efforts should be prioritized for caribou recovery.

Partnerships through BERA (Boreal Ecosystem Recovery and Assessment) are also advancing remote sensing techniques (project codes: LJ0220, LJ0331, LE0081). Dozens of peer-reviewed papers explore new tools and techniques that help inform landscape-level decision making. Some examples include mapping trails and tracks and detecting trees with remote sensing.

Due to the widespread environmental impact of seismic lines, challenges and workshops aimed at finding ways to reduce seismic line creation have been a priority. The Eco-Seis methodology emerged at the Exploration Tools Pitch Competition (project code: LE0076). This methodology, developed by OptiSeis Solutions Ltd., reduces the total amount of line clearing needed within a seismic program by up to 50%. It also reduces greenhouse gas emissions by an estimated 55% and cuts costs by 10-25%. These savings are accomplished by using irregular, alternative geometries for seismic arrays that minimize line clearing while maintaining subsurface data quality. This methodology has been successfully developed (project code: LJ0340). Now, ongoing work is demonstrating it can provide equal or superior subsurface information while reducing environmental footprints and meeting industry safety standards (project code: LJ0344). Work continues to advance this methodology towards commercial acceptance. 

Learn more about Eco-Seis: 

https://www.youtube.com/watch?v=fjz5NAtdPAM

Eco-Sies is not the only new methodology or technology to emerge from this work. Others that have been making progress include the eVibe “storm”, the PinPoint Pilot from Explor, and the combination of low-impact seismic sources and fiberoptic sensing technologies prop

A landscape with both industry and caribou is possible, but significant work is required to make this future a reality. A variety of planning tools applicable to various scales in space and time are necessary to restore key habitats and plan future developments that minimize impacts to caribou. Some key tools and workflows supporting caribou include:  

• Prioritizing and optimizing restoration schedules for seismic lines and other semi-permanent human footprint types (project codes: LE0039, LE0049). Prioritization is based on the potential increase of undisturbed caribou habitat that could be achieved through linear feature restoration, accounting for both the restoration cost and the potential for future resource development.

• The use of UAVs and remote sensing tools to map and quantify terrestrial lichens (project code: LE0045), which are important winter food sources for caribou. This work is also relating disturbance history patterns (especially fires of varying ages) to lichen recovery rates.

The LiDAR-Based Footprint Mapping and Vegetation Succession Assessment for Caribou Habitat Management in the Cold Lake Range (project code: LJ0156). This project uses LiDAR, colour infrared imagery, and ground truth data to map disturbances and vegetation succession. This work is helping inform habitat management and land-use planning by evaluating vegetation structure in relation to caribou habitat requirements, predator use of linear features, and the effectiveness of passive and active reclamation strategies. It allows managers to tailor restoration strategies to site-specific ecological conditions.