Land Monitoring from Hatfield

Big Earth observation data analytics for environmental assessment and monitoring

Big Earth observation data analytics for environmental assessment and monitoring

Multi-sector expertise and cutting-edge analytics to deliver products and strategic insights​

Inputs

  • Optical satellites
  • Radar satellites
  • LiDAR
  • Remotely Piloted Aircraft Systems

Analytics

  • Data fusion
  • Machine learning
  • Data mining
  • Time series analytics
  • Cloud native, scalable processing

Take your land monitoring to the next level! Maxar’s™ SecureWatch® platform enables users to access high quality imagery. Connect with one of our experts to learn more.

Sector Insights

Providing cutting edge analytics to fulfill the environmental assessment and monitoring requirements of our clients.

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Forestry

  • Forest extent and type
  • Biomass and carbon stock estimation
  • Leaf area index (LAI) modeling
  • Landscape disturbance detection and recovery assessment
  • Fire mapping (perimeter and burn severity)
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Wetlands

  • Wetland class and form classification
  • Wetland permanence assessment
  • Wetland change monitoring
  • Watershed characterization
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Coastal Management

  • Mangrove assessment and monitoring
  • Aquaculture inventory
  • Habitat assessment and monitoring
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Climate change & nature-based solutions

  • Historical baseline assessment
  • Habitat degradation and disturbance monitoring
  • Restoration and rehabilitation planning and monitoring
  • Measurement, reporting, and verification (MRV) for REDD+
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Energy

  • Energy corridor monitoring
  • Incident response and assessment
  • Habitat disturbance and reclamation monitoring
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Hazards

  • Wildfire – rapid burned area mapping (R-BAM)
  • Flood – rapid mapping and historical assessment
  • Natural disturbances (e.g., insects)

Analytic Service Examples

Forest Disturbance & Recovery

Forest ecosystems are affected by natural disturbances such as wildfires and insect attack as well as forestry operations and natural resources development. Understanding of the cumulative disturbance of the forest landscape and the effectiveness of forest recovery and restoration efforts are important for biodiversity, timber supply, water resources, and wildfire management. We provide strategic information on disturbance and recovery over large areas by analyzing long time series of satellite EO data, including detecting and assessing narrow linear features, for example assessing several caribou ranges and timber supply areas in Northeast British Columbia.

Leaf Area Index

LAI is an measure of the amount of leaf area relative to the ground area, and is an important vegetation parameter driving net primary production, water and nutrient use, and carbon balance. We developed a machine learning LAI model, calibrated by in-situ measurements, based on optical and radar satellite EO data to estimate LAI of boreal forest ecosystems in Northern Alberta. Using the scalable computing power of our cloud platform, we applied the model over 16 million hectares, monthly between May and October in 2020. This enabled researchers to visualize LAI dynamics in coniferous and deciduous treed areas for water balance studies.

Wetland Classification

Obtaining and integrating environmental information to identify, classify and monitor wetlands is challenging. We developed object-based and machine learning classification methods that integrate multi-source and multi-temporal remote sensing data, including airborne lidar and satellite EO optical and radar data. We have mapped wetlands following the Alberta Wetland Classification System over large areas in boreal and prairie landscapes.

Mangrove Monitoring

Mangroves ecosystems are distributed across the tropical and subtropical regions of the world and provide important ecosystem goods and services to nature and society. Mangrove forests are under threat from both natural and anthropogenic forces. We use multi-spectral, radar, and lidar data with machine learning methods to classify and map change in mangrove ecosystems over large areas. Our mangrove experience includes Tanzania, Madagascar, and Indonesia. Our services complement global monitoring initiatives providing more details and calibrated local information.

Desert Locust Impacts

In early 2020, several countries in east Africa reported an outbreak of desert locust, causing widespread infestation of cropland and pastures. As part of the European Space Agency’s Earth Observation for Sustainable Development (EO4SD) – Fragility, Conflict, Security (FCS) cluster, Hatfield investigated the use of satellite EO time series data to provide additional insights into the locust infestation on croplands in Ethiopia, Kenya, and Somalia. Read more in our EO4SD articles:

Lake Ice Classification

We developed an efficient computational technique for identifying bottom-fast ice across lakes in the Northwest Territories using multi-temporal SAR backscatter images. We used dynamic time warping (DTW), which provides a shape-based similarity metric for time series data. We used backscatter profiles from surveyed lakes with known bottom-fast ice to generate a DTW similarity metric on a pixel by pixel basis for a set of lakes. Our model categorized ice status across large areas with > 89% accuracy. Read more in our Canadian Journal of Remote Sensing article.

Rapid Burned Area Mapping (R-BAM)

Using our big data cloud-platform, R-BAM analytics enable rapid and scalable processing of multispectral EO data for wildfire mapping and assessment. Our R-BAM system uses cloud-free pre-fire composite images as the basis for rapid mapping of fire perimeters and burn severity. R-BAM has been used to support wildfire response and impact assessment. Read more in Hatfield’s featured project story.

Oil Spill Response

If an accidental release occurs, pipeline operators want to quickly assess the incident. Hatfield developed a rapid onshore oil spill assessment tool in a project International Oil and Gas Producers Association and the European Space Agency. The tool is an algorithm deployed in a cloud platform, which automatically accesses and analyzes satellite EO data for a location submitted by a user, for example to investigate potential impacts on vegetation health.

Land Monitoring Engine

The Land Monitoring Engine is a cloud native, open platform for Big Data geoscience that can be customized and deployed in your own cloud or HPC infrastructure.

We’re on a mission to advance satellite EO analytics and enable stakeholders to embrace this new era using cloud and high-performance computing environments.

Learn more at www.geoanalytics.ca

Connect with one of our experts

    We are trusted advisors to government, private sector, and non-government clients on the use of remote sensing technology for environmental monitoring and management around the world. We regularly support international space agencies, international finance institutions, and major energy and mining companies with scientific and strategic consulting and data analytics.

    Our head office is located in Vancouver, British Columbia, Canada. We also have offices in Indonesia and Botswana. We have experience in more than 40 countries and a network of local experts around the world.

    #200 - 850 Harbourside Drive
    North Vancouver, BC V7P 0A3

    Tel: +1-604-926-3261
    Toll-Free: 1-866-926-3261
    Fax: +1-604-926-5389
    Email: hcp@hatfieldgroup.com

    Plaza Harmoni Unit B5 - B7
    Jl. Siliwangi No.46
    Bogor 16131, Indonesia

    Tel: +62 251 832 4487; 833 2602
    Fax: +62 251 834 0414
    Email: hatfindo@hatfieldgroup.com

    PO Box 3415 Main Mall,
    Gaborone, Botswana

    Tel: +267 397 2661
    Fax: +267 397 2668
    Email: hca@hatfieldgroup.com

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