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What is Remote Sensing?

With the ability to capture data from a distance, remote sensing enables the analysis of large areas, monitoring of changes over time and the extraction of meaningful insights. We can assist you with any projects that would benefit from the extraction of spatio-temporal information from remotely sensed imagery.

Our Expertise

Remotely sensed data such as regional aerial imagery or LiDAR requires complex modelling pathways for data manipulation and transformation. We wrangle the data and produce pipelines that are reproducible, shareable, and supported by documentation.

Big Data

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As data nerds, we love to keep up with the latest research in the field. This means that our solutions are informed by research and designed for success.

Research Informed Problem Solving

We bridge remote sensing with socioeconomic and environmental concerns

We can utilise remote sensing and demographic variables to model future scenarios of development density by integrating climate change related hazards and community risk, using a population health lens.


Explore the below case studies to learn more....

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Extreme Heat Modelling and Vulnerability Assessment


Urban Canopy Carbon Sequestration Modelling

In addition to these we have also completed projects with: the Vancouver Economic Commission, Abbotsford, Surrey, Richmond, Kamloops, Langley (Township), West Vancouver, North Vancouver (District) and more work with the Province of British Columbia.

Case Studies


The Climate Action Secretariat (CAS) at the Province of British Columbia is responsible for supporting the implementation of programs, strategies, policies and legislation related to climate change mitigation.  To support this work greenhouse gas emissions quantification, monitoring and reporting is required. The Province is engaging in a continuous process to improve the granularity and scope of their emissions data, as well as other policy-relevant indicators.


One of the primary emissions data sources used by the Province is Canada’s National Inventory Report (NIR), a federally prepared report with annual emissions for each Province. It offers a standardized approach for Province-wide reporting that is highly aggregated and meets internationally agreed upon GHG accounting standards. The NIR is not disaggregated at the community-level, nor does it provide granular-level information on vehicles or buildings.


Another source of emissions data used in BC is the Community Energy and Emissions Inventory (CEEI), which provides emissions measures for BC local governments. The CEEI is based on different data sources than the NIR due to the requirement that the dataset represents community-level emissions and energy use.


The challenge for CAS in improving data quality is thus to develop reproducible methodologies for updating community-level emissions inventories that contain detailed building and vehicle information, while also remaining consistent with federal and provincial reporting.

Case Study 1

Provincial Energy and Emissions Inventories


At LGeo, we are experts in disaggregation! We use our expertise in GIS, data science and our deep knowledge of the data context to extract spatial, temporal and technology-wise information from top-line numbers. We also have extensive experience in emissions accounting.


In this project, we applied our disaggregation expertise and domain knowledge and experience to develop three reproducible methodologies for creating annual emissions inventories that align with the NIR and the CEEI. The sectors and their disaggregation data included:


  • On-Road Vehicles, using vehicle insurance records, statistical surveys to estimate driving distance and engine characteristics of the vehicles to estimate their fuel (or electric) efficiency.

  • Off-Road Vehicles, for 

    • Agriculture, using the Census to estimate vehicle counts and surveys to estimate their hours of operation and fuel efficiencies.

    • Forestry, using annual reports for volume of wood harvested and research-based factor for assumed fuel consumption per m3.

    • Manufacturing, using mandatory, facility-based provincial reports.

    • Mining, using production data and assumed fuel efficiencies per unit for several different commodities including coal and various metals.

    • Construction, using fuel-sales and the amount of building and road construction.

  • Buildings, using top-line utility consumption values for each local government, along with highly disaggregated building floor area data and building energy archetypes.


The results of our work are not yet public, but for more information on the Province’s emissions reduction initiatives, explore the reports below!

Case Study 2

Metro Vancouver Carbon Neutral Scenario Modelling


Metro Vancouver and its member municipalities have pledged to reduce greenhouse gas emissions by 45% by 2030 and achieve carbon neutrality by 2050.


The challenge presented in this project was to identify, test and evaluate a diverse suite of regional policies to meet a Carbon Neutral Scenario for the region. Policies extended across 10 sectors identified by the Climate 2050 Strategic Framework

Nature and Ecosystems, Industry, Infrastructure, Energy, Human Health and Well-Being, Land-Use and Growth Management, Buildings, Agriculture and Transportation and Waste


We applied our deep experience with energy and emissions modeling, model integration, tool development and climate leadership to model more than 40 potential policies, actions and measures including:

  • Transportation policies that affect vehicle kilometers traveled;

  • Transportation policies that affect vehicle technology adoption;

  • Transportation policies that affect vehicle efficiency;

  • Policies that affect carbon contents of fuels;

  • Policies that affect the use of renewable natural gas and shifts to compressed natural gas;

  • Industrial policies that affect process feed stocks;

  • Industrial policies that affect process efficiencies;

  • Buildings policies that affect retrofit rates for building stock renewal;

  • Buildings policies that affect performance standards for new construction;

  • Land use policies that provide throughput for transportation modeling and buildings modeling; and

  • Liquid and solid waste management policies that affect disposal and diversion rates from numerous emissions sources.

Case Study 3

City of Vancouver Climate Emergency Action Plan - Ongoing Modelling


As a global leader in climate change policy, the City of Vancouver has ambitious sectoral goals and targets. To achieve these, the City has laid out the Climate Emergency Action Plan (CEAP) that bundles interdependent actions and targets into 6 categories called Big Moves:

  • Big Move 1: Complete, Walkable Communities

  • Big Move 2: Active Transportation and Transit

  • Big Move 3: Zero Emissions Vehicles

  • Big Move 4: Zero Emissions Space and Hot Water Heating

  • Big Move 5: Low-Carbon Construction Materials

  • Big Move 6: Carbon Sequestration

The challenge faced by the City of Vancouver, and the purpose of this project, was (and continues to be) to evaluate upcoming and potential CEAP policies based on domain expertise, best practices, and informed modeling and data, in order to:

  1. Understand the direct impacts of policies on GHG reductions;

  2. Monitor progress towards targets; and

  3. Identify key risks, uncertainties and opportunities to accelerate action.


We developed causal computational models to forecast the emissions impacts that result from a variety of policy scenarios. In other words, our models can be explained! They produce a wide variety of interesting information such as projections for: building floor areas, energy use, EV ownership and many more. 


We also developed a reusable software pipeline so that we can quickly test a wide range of assumptions. This means that we can evaluate the impact of each policy in isolation, conduct sensitivity analysis and incorporate new policies, all with limited overhead. For this reason, we are able to provide ongoing policy integration, modelling and analysis for the City.

Our results are displayed for the City in an interactive online dashboard  (an example, populated with placeholder values, is available here).


For more information on our approach, click through on the images in the carousel below! For privacy, the images below are populated with placeholder data and may not be representative of actual results.


For further reading on the CEAP, check out the 2022 CEAP progress report, and the City’s website.