MASL has signed a contribution agreement with the Canadian Space Agency for a 2-year project under the Satellite Mobilization for Biodiversity (SaMBA) opportunity, part of the smartEarth funding initiative.
ASL is in works to develop the DeCAF Rapid Response Tool (RRT) to support near-real-time monitoring of salmon habitats. It builds on ASL’s wide-area-monitoring solution DeCAF, and uses advanced deep learning techniques to process open-access or commercial satellite data and find immediate landscape changes, including human disturbances and natural phenomena (i.e. landslide detections as seen in figure).
ASL is developing this in collaboration with a variety of stakeholders:
Classified change detection results for 2021 around Victoria, BC, Canada, produced using an ensemble of deep learning and statistical models developed during the project.
ASL and Canadian Space Agency co-funded this R&D project under smartEarth initiative – Bridging the Information Gap with Space-Based Analytics.
The project aimed to develop foundational components of a system capable of monitoring landscape change across large regions using free and open-access satellite image time series
State-of-the-art deep learning techniques were used to prototype frameworks for detecting and classifying change. Multiple study areas supported model development across diverse landscapes and change processes, including wildfires, placer mining, forest health degradation, timber harvesting, and urban development.
Land cover classification over Slave Lake, AB, from integrated optical and RADAR image data.
The MARA project, funded by the Canadian Space Agency (CSA) under Earth Observation Applications Development Program (EOADP), focused on development of improved Earth Observation (EO) products for the assessment of reclaimed industrial disturbances in Canada’s natural areas.
Earth Observation data from Synthetic Aperture Radar (SAR) and optical sensors were integrated to improve land cover classification in the boreal forest, by combining the spectral information from optical sensors with the backscatter information from RADARSAT-2. Study areas included sites in Ontario, Alberta, BC and Yukon.
The project resulted in the following advancements:
1985-2009 trend in vegetation greenness.
The Whitefish Wetlands is a 467 km2 proposed Habitat Protection Area in north-central Yukon. In 2015 ASL was contracted by Environment Yukon to establish a baseline of vegetation information and to assess change in the study area.
Using Landsat 5 data from 2009, we created an 8-class land cover map that included four classes of wetland or aquatic vegetation and three classes of upland vegetation. Landsat 5 and 7 data were then used to construct a time-series of imagery back to 1985. From this time-series, long-term trend information was extracted.
Services provided included:
Aerial Survey using a Saltspring Air de Havilland Beaver.
2013 vegetation assessment.
Highland Valley Copper (HVC) near Kamloops, British Columbia has had a major mine reclamation program underway since 1983, in which the establishment and development of self-sustaining vegetative cover are important elements.
Airborne multispectral surveys to supplement the ground surveys were initiated by Borstad Associates in 2001 and were repeated annually until 2011, when high resolution satellite imagery became a feasible alternative. These remote sensing surveys provided synoptic, quantitative thematic maps of the vegetation on the mine site and were used to extrapolate from and between the more detailed observations at ground sampling sites.
Services provided:
