{"id":2434,"date":"2016-11-03T20:59:37","date_gmt":"2016-11-04T03:59:37","guid":{"rendered":"http:\/\/blog.light42.com\/wordpress\/?page_id=2434"},"modified":"2021-11-05T19:29:52","modified_gmt":"2021-11-06T02:29:52","slug":"archive3","status":"publish","type":"page","link":"http:\/\/blog.light42.com\/wordpress\/?page_id=2434","title":{"rendered":"archive3"},"content":{"rendered":"

Assessment of Spatial Asset Contents – basics:
\nWhat classifications are used in the Multi-Family CoStar sample ?<\/em><\/p>\n

\r\ngeo_datamine_f2=# select count(*) from costar_mf_pts0;\r\ncount =>  12333\r\n\r\ngeo_datamine_f2=# select distinct(property_type,secondary_type) from costar_mf_pts0;\r\n                        row                        \r\n---------------------------------------------------\r\n (Multi-Family,Apartments)\r\n (Multi-Family,Dormitory)\r\n (\"Multi-Family (Community Center)\",Apartments)\r\n (\"Multi-Family (Lifestyle Center)\",Apartments)\r\n (\"Multi-Family (Neighborhood Center)\",Apartments)\r\n (\"Multi-Family (Power Center)\",Apartments)\r\n (\"Multi-Family (Regional Mall)\",Apartments)\r\n (\"Multi-Family (Strip Center)\",Apartments)\r\n (\"Multi-Family (Super Regional Mall)\",Apartments)\r\n(9 rows)\r\n<\/pre>\n
 
\nNext, classification of the la_bldgs_pt<\/code> table. -query-<\/p>\n
\r\ngeo_datamine_f2=# select distinct (generaluse,specificus,specific_1)\r\nfrom la_bldgs_pt order by (generaluse,specificus,specific_1);\r\n\r\n-\r\n (Commercial,\"Animal Kennel\",)\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Auto Body Repair Shop\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Auto Service Centers (No Gasoline)\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Car Wash Only\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Car Wash Only, Self-service Type\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Farm and Construction Equipment Sales and Service\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"New Car Sales and Service\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Recreation Equipment Sales and Service (Campers, Motor Homes and Boats)\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Used Car Sales\")\r\n (Commercial,\"Auto, Recreation Equipment, Construction Equipment Sales and Service\",\"Wireless Communication Tower\")\r\n (Commercial,\"Bank, Savings and Loan\",\"Wireless Communication Tower\")\r\n (Commercial,\"Bank, Savings and Loan\",)\r\n (Commercial,Commercial,\"Artist in Residence\")\r\n (Commercial,Commercial,\"Miscellaneous Commercial\")\r\n (Commercial,Commercial,\"Wireless Communication Tower\")\r\n (Commercial,Commercial,)\r\n (Commercial,\"Department Store\",\"Building Supplies (Home Depot, etc.)\")\r\n...\r\n\r\ngeo_datamine_f2=# select * from la_bldgs_pt where \r\ngeneraluse = 'Residential' ;\r\n\r\n (Residential,\"Double, Duplex, or Two Units\")\r\n (Residential,\"Five or More Units or Apartments (Any Combination)\")\r\n (Residential,\"Four Units  (Any Combination)\")\r\n (Residential,\"Manufactured Home\")\r\n (Residential,\"Manufactured Home Park\")\r\n (Residential,\"Rooming\/Boarding House\")\r\n (Residential,\"Single Family Residence\")\r\n (Residential,\"Three Units (Any Combination)\")\r\n (Residential,)\r\n\r\n--\r\ngeo_datamine_f2=# select * from la_bldgs_pt where \r\ngeneraluse = 'Residential' AND  specificus ~ '^Five';\r\n\r\n...\r\n-[ RECORD 143121 ]---------------------------------------------\r\ngid        | 3120182\r\nobjectid_1 | 3120182\r\nobjectid   | 0\r\ncode       | Building\r\nbld_id     | 517655867139\r\nheight     | 23.64000000000\r\nelev       | 761.32000000000\r\narea       | 0\r\nlariac_sou | \r\nlariac_dat | \r\nain        | 5324018017\r\nstatus     | \r\ncode_num   | 0\r\nsource     | LARIAC2\r\ndate_      | 2008\r\ngeneraluse | Residential\r\nspecificus | Five or More Units or Apartments (Any Combination)\r\nyearbuilt  | 1960\r\nspecific_1 | 4 Stories or Less\r\nunits      | 13\r\ngeom       | 0101000020E61000001760CC5D4D895DC0D98768F3BB0F4140\r\n\r\n--\r\n\r\n-- count buildings per subdivision\r\n\r\n        cousub name           | count  \r\n ...\r\n Inglewood                    | 100623\r\n Agoura Hills-Malibu          |  27751\r\n Los Angeles                  | 706297\r\n San Fernando Valley          | 577742\r\n ...\r\n(20 rows)\r\n\r\n--\r\ngeo_datamine_f2=# select cs.\"name\", count(b.*) \r\nfrom tl_2016_06_cousub cs,  la_bldgs_pt b\r\nwhere\r\n  cs.countyfp = '037'  AND\r\n  st_intersects( cs.geom, b.geom)\r\ngroup by\r\n  cs.\"name\";\r\n\r\n-- Use Inglewood as an LA Example ...\r\n<\/pre>\n
 <\/p>\n
Focus on Inglewood, Los Angeles<\/strong><\/p>\n
Inglewood is a US Census County subdivision -wikipedia-<\/a>, and is a good sample area to use to become more familiar with the contents of 3.1 million building records in the LA Import resource. We shall pay particular attention to correlation, or lack, with the CoStar sample supplied by CEC.<\/p>\n
* Use a spatial SQL analytics environment to select all RESIDENTIAL buildings in the Inglewood County Subdivision  <\/p>\n
\"map\"<\/a><\/p>\n
This image shows aprox 90,000 residential buildings (gray), 6956 “Residential - Five or more units<\/code>” buildings (blue), and 86 CoStar listings in the CEC-supplied data sample.  (any combination of attributes and spatial relationship can be used to generate these views<\/em>)<\/p>\n
* Use Openstreetmap for a cartographic impression of the area, landmarks, and structural composition
\n –
\n\"\"<\/a><\/p>\n
* Use a desktop GIS client to show asset details — the area near the large freeways intersection is easy to identify, and has buildings in the class we are interested in ..
\n\"\"<\/a><\/p>\n
In this layout, CoStar MF buildings are marked with a large green dot; “Residential - Five or more units<\/code>” buildings are shown as black dots with labels indicating the supplied units count. County Blockgroups are identified as large IDs with light green backing. A single record is selected, with attributes shown. The record is notable because at that location there appears to be a very large residential complex, there is one CoStar marker there, yet there are two LA Buildings records shown.<\/p>\n
Using SQL and converting the “units” field to an integer, generate a database table of Residential Units 17 or greater<\/code>; display
\n\"\"<\/a><\/p>\n
Notice that for each of the six visible CoStar points, there are LA_Bldgs points, but for four of the six CoStar points, there are clearly two LA_Bldgs points corresponding to one CoStar point.  A closer look at one of those occurrences, West of the highway intersection <\/p>\n
 <\/p>\n
Bakersfield MultiFamily Units over NAIP — Test Four
\n<\/strong><\/p>\n
In order to define and scope the task of Machine Learning (ML<\/strong>) for this project in a job description, describe and execute a very short series of steps similar to the ML methods; examine and document test elements.<\/p>\n
The following screen shots consist of:
\n* NAIP  California_20090801
\n* Bakersfield City Building Footprints
\n* TIGER 2016 Block Groups, Kern County<\/p>\n
Hint:<\/em> Click on thumbnails to get full view; use your browser scaling to magnify<\/p>\n
Inquiry:<\/em> “given four CoStar-sourced multifamily dwelling units (MF) in a given BlockGroup in Bakersfield, what can be learned from examining aerial imagery”<\/p>\n
\"mf_costar_bakersfield_b1\"<\/a><\/p>\n
\"Bakersfield<\/a>
Bakersfield Test Case<\/p><\/div>\n
Observations<\/em><\/p>\n