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A key piece of the puzzle with many current opportunities and some challenges. Important for understanding historic impacts, restoration site planning, effectiveness monitoring and communications
Opportunities include (among many others of course) quantification and visualization of historic changes in stream morphology resulting in loss of quantity and quality of water and fish habitat while highlighting areas of historic dredging, realignment, and floodplain disconnections due to infrastructure, to guide future restoration efforts.
We can link to URLs of Digital Elevation Models (DEM) stored in the cloud and served out by LiDar BC as Cloud Optimized Geotiffs (COGs) without actually downloading any data however many of these files are very large (ex. 1:20,000 mapsheets) so rendering these in QGIS can be very slow. We may need to link to and/or develop workflows to potentially trim lidar to our areas of interest (some sort of buffered representation of floodplains perhaps), optimize the resulting files for reading through https connections and re-store in the cloud. Many of these steps can potentially be combined and scripted (see beginning of discussion here https://chat.openai.com/share/7d5edb68-fc36-442a-94c8-6b96467b5990
There is much discussion of collaboration with and within the provincial government and open-source community occurring with some of those discussions and current workflows discussed here:
A key piece of the puzzle with many current opportunities and some challenges. Important for understanding historic impacts, restoration site planning, effectiveness monitoring and communications
Opportunities include (among many others of course) quantification and visualization of historic changes in stream morphology resulting in loss of quantity and quality of water and fish habitat while highlighting areas of historic dredging, realignment, and floodplain disconnections due to infrastructure, to guide future restoration efforts.
https://lidar.gov.bc.ca/pages/download-discovery
We can link to URLs of Digital Elevation Models (DEM) stored in the cloud and served out by LiDar BC as Cloud Optimized Geotiffs (COGs) without actually downloading any data however many of these files are very large (ex. 1:20,000 mapsheets) so rendering these in QGIS can be very slow. We may need to link to and/or develop workflows to potentially trim lidar to our areas of interest (some sort of buffered representation of floodplains perhaps), optimize the resulting files for reading through https connections and re-store in the cloud. Many of these steps can potentially be combined and scripted (see beginning of discussion here https://chat.openai.com/share/7d5edb68-fc36-442a-94c8-6b96467b5990
There is much discussion of collaboration with and within the provincial government and open-source community occurring with some of those discussions and current workflows discussed here:
bcgov/bcmaps#99
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