Wetlands are known to provide excellent waterfowl habitat but #DYK they are also home to many mammals? Let's celebrate #wetland mammals this #MammalWeek such as boreal caribou, moose, and of course, beavers! pic.twitter.com/RMHEJniH4I Retweeted by Fiera Biological

This is a first-time situation for me. #Coyote roaming about outside our @UofAALES building. We do a lot of work with conservation biology & wildlife issues but this is a bit surprising. #yeg pic.twitter.com/nOUroZe2j6 Retweeted by Fiera Biological

Remote Sensing & GIS

We are leaders in applying aerial and satellite multi-spectral imagery to remotely derive ecological information at the scale of a single site or at the landscape-level, using Remote Sensing & GIS technologies.

Remote sensing uses drone, airborne, or satellite sensors to collect information about the earth’s surface without disturbing the area that is being observed. This method provides us with detailed information and measurements that can be used to inventory, map, and assess the condition of natural habitats. Because information is automatically collected and can be processed quickly using machine learning, remote sensing is ideally suited to assess and monitor large areas that would otherwise be too costly to assess on the ground.

At Fiera, we frequently use and combine remote sensing information with other data products in a Geographic Information System (GIS). This allows us to undertake complex spatial analysis to assess how land use decisions may impact the distribution of habitat, and the occurrence or movement of wildlife. We also combine remote sensing and GIS technologies with traditional on the ground field techniques, enabling us to quickly monitor and assess large areas over multiple time periods. This allows us to record and explore how phenomena change over both space and time, expanding the reach of field-based studies.

Our geospatial scientists have experience working with and processing data from a wide range of remote sensing platforms and sensors, including visible, multispectral, and hyperspectral imagery, and full feature LiDAR data. We routinely use these types of data to create land cover and wetland inventories, which can then be used for a wide range of monitoring and assessment applications.

Remote sensing, GIS, land cover classification, wetland inventory, habitat modeling, machine learning, random forest classifier

Our team routinely creates land cover classifications and wetland inventories that can be used to map important areas for management, or to model change in habitats through time.