Fraser River - BCSRIF Landslide Mapping – 2022 – Hakai Airborne Coastal Observatory

Airborne Lidar and Imagery data continued to be collected by the ACO in 2022, in partnership with Dr. Jeremy Venditti (SFU) and Dr. Brian Menounos (UNBC, Hakai Institute). The goal of this data is to inventory and characterize the terrain throughout the Fraser River system to look at contemporary and historical landslide impact on flow dynamics, fish migration, and genetics of Fraser River Salmon. This work was underscored on November 1st, 2018 by the Big Bar Landslide, which partly blocked the Fraser River, creating a hydraulic barrier to salmon passage at moderate to high flows and significantly impeded salmon migration to the upper Fraser Basin.

Below is a brief overview of the Airborne Coastal Observatory (ACO) and the type of data collected. For more detailed information about data processing, data quality assurance, software used please contact data@hakai.org The Airborne Coastal Observatory (ACO) is a collaborative program led by the Hakai Institute with partners the University of Northern British Columbia and Kisik Aerial Surveying. The program offers rapid and accurate aerial observations of coastal ecosystems, from Icefields to Oceans. A Kisik Aerial Piper Navajo aircraft is packed with an array of integrated Earth imaging sensors and technology to provide highly visual and highly accurate data. Hakai’s Airborne Coastal Observatory was developed to map and monitor icefields to oceans by using a combination of airborne Lidar (Light Detection and Ranging), high-resolution imagery, and hyperspectral imagery. Combined, the ACO sensors provide data to quantify changes in seasonal snow cover and glacier mass loss. The ACO is an aerial remote sensing platform used by the Hakai Institute to survey landscapes in detail. A Piper Navajo aircraft carries an array of integrated airborne mapping sensors installed to collect data in concert. The aircraft is operated and maintained by Kisik Aerial Surveys (Delta, BC). For more information on post processing, data quality assurance, software used, and summary of results please contact data@hakai.org