UM Geospatial Digital Special Collections

Citation: Department of Housing and Urban Development (2016). Miami-Dade Public Housing Developments [gis dataset]. Office of Policy Development and Research. https://hudgis-hud.opendata.arcgis.com/datasets/HUD::public-housing-buildings/about. last updated: 2024-05-01 (update frequency: 3 months). Abstract: Denotes the general position of Public Housing Developments by providing the location of the building with the largest number of units in a Development’s community. HUD furnishes technical and professional assistance in planning, developing and managing these developments. Public Housing Developments are depicted as a distinct address chosen to represent the general location of an entire Public Housing Development, which may be comprised of several buildings scattered across a community. The building with the largest number of units is selected to represent the location of the development. Key words: Florida, Miami-Dade County, MDC, HUD, Property, Housing, Public Housing, Public Housing Development, Development, Infrastructure Open Geospatial Consortium Standards: vector tiles | WMS (coming soon) | WFS (coming soon) ESRI Standards: ArcGIS MapServer | ArcGIS FeatureServer | Open in ArcGIS Portal for GDSC Analytical Functions: gdsc_get_attributes(tablename=mdc_public_housing,lat=25.718,lng=-80.279,identifier=project_name,attrs=[participant_code,formal_participant_name,development_code,project_name,scattered_site_ind,pd_status_type_code,total_units,total_dwelling_units,acc_units,total_occupied,regular_vacant,pha_total_units,pct_occupied,number_reported,pct_reported,months_since_report,pct_movein,people_per_unit,people_total,rent_per_month,spending_per_month,hh_income,person_income,pct_lt5k,pct_5k_lt10k,pct_10k_lt15k,pct_15k_lt20k,pct_ge20k,pct_wage_major,pct_welfare_major,pct_other_major,pct_median,pct_lt50_median,pct_lt30_median,pct_2adults,pct_1adult,pct_female_head,pct_female_head_child,pct_disabled_lt62,pct_disabled_ge62,pct_disabled_all,pct_lt24_head,pct_age25_50,pct_age51_61,pct_age62plus,pct_age85plus,pct_minority,pct_black,pct_native_american,pct_asian,pct_hispanic,months_waiting,months_from_movein,pct_utility_allow,ave_util_allow,pct_bed1,pct_bed2,pct_bed3,pct_overhoused,tminority,tpoverty,tpct_ownsfd,state2kx,cnty_nm2kx,cnty2kx,tract2kx,bg2kx,block2kx,dpvact,dpvnost,curcnty_nm,curcnty,curcosub,curcosub_nm,place2kx,place_nm2kx,place_cc2kx,place_inc2kx,msa,msa_nm,cbsa,cbsa_nm,necta,necta_nm,metro,micro,fcd_fips91,hlc,dpv,dpvrc,std_addr,urb_out,std_city,std_st,std_zip5,std_zip9,zip_class,zcta2kx,dpbc,dpbc_cksum,std_zip11,addr_type,apt_no,apt_type,c1pgrc,c1pprb,c1pdrc,c1psrc,c1parc,c1pzrc,msgusps,lat,lon,rc2kx,stm2kx,lvl2kx,ur,msg2kx,county_level,place_level,tract_level,blkgrp_level,spending_per_month_prev_yr,chldrn_mbr_cnt,eldly_prcnt,pct_disabled_lt62_all,pct_lt80_median,median_inc_amnt,last_updt_dttm,annl_expns_amnt,annl_expns_amnt_prev_yr,ha_phn_num,ha_fax_num,ha_email_addr_text,exec_dir_phone,exec_dir_fax,exec_dir_email],normal='') ETL documentation

ETL for mdc_public_housing

######### # 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_public_housing/{download,etl} && cd /data/mdc_public_housing # set update flag based on last update and update frequency do_update=0 if date() < last_update + update_frequency else do_update = 1 # download if update flag is set: if do_update == 1 then wget -O download/mdc_public_housing.json 'https://services.arcgis.com/VTyQ9soqVukalItT/arcgis/rest/services/Public_Housing_Developments/FeatureServer/11/query?outFields=*&where=1%3D1&outSR=4326&f=geojson' # replace column names Shape__Length and Shape__Area to avoid conflict when # providing as service on ArcServer. sed -i 's/Shape__Length/shape_length/gI; s/Shape__Area/shape_area/gI' download/mdc_public_housing.json # load into postGIS with: ogr2ogr -lco GEOMETRY_NAME=geom -f PostgreSQL PG:"" download/mdc_public_housing.json -nlt point -nln mdc_public_housing ######### # Step 2 - SQL script (pseudo code): #### # remove duplicate points and make geometries valid: UPDATE mdc_public_housing SET geom=ST_MakeValid(ST_RemoveRepeatedPoints(geom));" # add local geometry column and reproject existing geometries into local EPSG: SELECT AddGeometryColumn ( 'mdc_public_housing', 'geom_local',2236,'point',2 ); UPDATE mdc_public_housing SET geom_local=ST_Transform(geom,2236); CREATE INDEX mdc_public_housing_geom_local_idx ON mdc_public_housing USING GIST (geom_local); NOTIFY pgrst, 'reload schema';"