Always a pleasure to catch the beautiful Canada Warbler and today we’ve caught 4! Unfortunately this species is listed as Threatened on the Species at Risk Act as it has declined by 62% between 1970 and 2014. This hatch year male is about to embark on a 3,000 mile journey south! pic.twitter.com/n156ZmS8sq Retweeted by Fiera Biological

#fieldworkfriday Understanding the #impact of a proposed #development on #naturalfeatures often means getting your feet wet. Here, Dr. Shari Clare is sporting her favourite #fieldfashion, while assessing a #wetland in Central #Alberta. #ecology #assessment #conservation pic.twitter.com/wj2Vpfy06i

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.