UM Geospatial Digital Special Collections

Citation: Univeristy of Miami GDSC (2017). 2015 Miami-Dade County DEM 30ft [gis dataset]. University of Miami GDSC. last updated: 2024-10-28 (update frequency: Never). Abstract: This dataset is derived from the 2015 Miami-Dade County DEM 10ft layer found at https://gis-mdc.opendata.arcgis.com/documents/MDC::2015-miami-dade-county-dem-10ft/about. The original source data was resampled to a resolution of 30ft per pixel using the gdalwarp utility. This source from Miami-Dade County a Digital Elevation Model (DEM) as a raster mosaic in ESRI float format 32bit representation on a 10ft grid created from the LiDAR collected for the 2015 ITD LiDAR project. Bare-earth 10-foot DEM as 32-bit floating point raster format in ArcGIS GRID Raster format in compliance with USGS LIDAR Base Specifications: georeferencing information, delivered without overlap and with no edge artifacts or mismatched, “NODATA” value for void areas, bridges removed from the surface, etc. Key words: Florida, Miami-Dade County, MDC, Environment, Elevation, DEM 30ft, Vulnerability, Flood, Flood Hazard, Public-Safety Open Geospatial Consortium Standards: raster tiles | raster tile url: https://gdsc.idsc.miami.edu/rastertiles/mdc_2015_dem_30ft/{z}/{x}/{y}.png | WMS (coming soon) | WFS (coming soon) Analytical Functions: gdsc_zonal_statistics(table=mdc_2015_dem_30ft,lat=25.718,lng=-80.279,radius=500) ETL documentation

ETL for mdc_2015_dem_30ft

######### # GDSC ETL is performed in two steps: shell script to ETL data into postgres # and then additional transformations with SQL in postGIS (if needed). #### ######### # Step 1 - bash script (pseudo code) #### # create directory structure and move into it mkdir -p /data/mdc_2015_dem_30ft/{download,etl} && cd /data/mdc_2015_dem_30ft # set update flag based on last update and update frequency do_update=0 if date() < last_update + update_frequency else do_update = 1 # load mdc_2015_dem_10ft as dependency (see mdc_2015_dem_10ft for details). # resample raster with: gdalwarp -tr 30 30 /data/mdc_2015_dem_10ft/download/dem_10ft/w001000.adf download/mdc_2015_dem_30ft.tif ######### # Step 2 - SQL script (pseudo code): #### # load raster into postGIS with: raster2pgsql -s 2236 -d -C -I mdc_2015_dem_30ft.tif -F -t 256x256 mdc_2015_dem_30ft > load_raster.sql psql < load_raster.sql rm load_raster.sql # render raster tiles mkdir -p /tiles/raster/mdc_2015_dem_30ft cd /data/mdc_2015_dem_30ft/ cat > mdc_2015_dem_30ft_color_ramp.txt <<_EOF -0.91 159 207 251 255 -0.30 221 226 183 255 2.867 210 231 171 255 6.684 250 247 187 255 10.501 219 200 161 255 14.318 208 179 124 255 18.136 219 178 142 255 22.324 255 255 255 255 nv 0 0 0 0 _EOF gdaldem color-relief download/mdc_2015_dem_30ft.tif mdc_2015_dem_30ft_color_ramp.txt download/mdc_2015_dem_30ft_color.tif -alpha gdal2tiles.py -ex --xyz -z 8-16 download/mdc_2015_dem_30ft_color.tif /tiles/raster/mdc_2015_dem_30ft/ cd /data/mdc_2015_dem_30ft/ mkdir -p derived # Create pg_dump and downloadable zip of table in derivate directory pg_dump -d $POSTGRES_DB -U $POSTGRES_USER -p $POSTGRES_PORT -h postgis-vtc29jryy1rbxz07 -t mdc_2015_dem_30ft > derived/mdc_2015_dem_30ft.sql tar -czf derived/mdc_2015_dem_30ft.sql.tar.gz meta_dcat_mdc_2015_dem_30ft.json -C derived mdc_2015_dem_30ft.sql