Comments (6)
Potential metrics:
Metric | Source |
---|---|
Total area (sqkm) | |
Average distance from shore (km) | CDFW coastline layer (distance from centroid) |
Average depth (m) | CDFW bathymetry layer |
Total length of sandy beach (km) | CA ROMS model layer |
Park area (sqkm) within 500 m | CA Parks parks shapefile |
Number of people within 50 km | US Census data |
Number of public beaches | Coastal Commission public beach layer |
Proximity to Public Beach access points | Beach access points |
Other datasets State Parks:
- Campgrounds
- Parking
- Entry
from ca-mpa.
sf::st_distance()
and raster::DistanceFromPoints()
could be options to compute the distances metrics
from ca-mpa.
The following metrics (raster layers) were processed:
Metric | Source |
---|---|
Total area (sqkm) | MPA shapefile |
Average distance from shore (m) | Global Watch Fisheries |
Average depth (m) | CDFW bathymetry layer |
Total length of sandy beach (m) | CA ROMS model layer <--- not processed yet waiting for the new dataset |
Distance from closest park entry point | CA Parks parks entry points |
Number of park entry points within 600m | CA Parks parks entry points |
Number of people within 50 km | US Census data |
Distance from closest public beaches | Coastal Commission public beach layer |
Number of public beaches | Beach access points |
Distance from closest Public Beach access points | Beach access points |
The Script processing those metrics is here: https://github.com/NCEAS/ca-mpa/blob/main/data/counterfactuals_rasters/counterfactuals_raster_processing.R
from ca-mpa.
Statistics processing script: https://github.com/NCEAS/ca-mpa/blob/main/analyses/3performance_human/code/counterfactuals_mpa_stats.R
This script creates a raster cube with all the tiff layers processed above and computes statistics for the MPA and transforms this raster cube into a large data frame.
Outputs:
mpas_counterfactuals_stats_epsg3309.geojson
data frame with the stats for the MPAscounterfactual_layers_epsg3309.Rds
raster cube transformed into a data framecounterfactual_layers_shallow_epsg3309.Rds
is the same but filtered for depth above the deepest pixel found in an MPA (aka smaller file)
All of those data files have been saved on the team's Google Drive: data/sync-data/counterfactuals
from ca-mpa.
Also added rasterization rasters of the MPAs matching the bathy grid:
- binary file (1 == MPA):
mpa_200m_epsg3309.tif
- ID file (grid value matches MPA ID):
mpa_200m_id_epsg3309.tif
updated the RDS files accordingly: f70949
from ca-mpa.
Chris and Cori have conducted the counterfactual analysis. Closing the issue
from ca-mpa.
Related Issues (5)
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from ca-mpa.