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Internal Infrastructure Tour

On-site computing, reference data sets, operating system support and development environs

    demo & tour

Project Overview: Collect available digital vector assets of building footprints statewide (data), QA/QC that data, and build derived products from that data, deploying project internal infrastructure as needed. see process snapshots :


WMS Identify -- LA Bldgs Raw

WMS Identify — LA Bldgs

  • WMS Layer assets are typically viewed via Web Mapping Services. styled WMS layers are intelligently sampled on the server-side to send only necessary information across data links. Selected WMS layers also support feature identification. -wikipedia-
  • Server Assets are delivered upon request by Web Services including Geoserver, in a plurality of formats and under a security framework based on Spring Security.
  • Source Code Ingestion, processing and reporting are driven by code, be it SQL, python, shell script or other. Code, snippets and certain intermediate assets are stored in Git source control.
  • Contents
    Blockgroup ID

    Blockgroup IDs

    • Buildings — e.g. retrieved from City of Bakersfield as shapefile (SHP)
    • California, other North America — NAIP imagery stored locally
    • ca_county_shp — US Census TIGER reference shapefiles
    • worldcities_ca_min — City name as POINT with population count and dynamic styling
    • osm_roads — from Openstreetmap California data snapshot, extracted and styled for visualization (viz)
    • LA_Bldgs_raw — full dataset from LA County, 1st ed. 2008
    • LA_Bldgs_pt — buildings with attributes, stored as POINT for summary spatial statistics
    • costar_mf_pts0 — Costar Multifamily units, supplied by CEC
    • census_2016_uac — urban areas layer; US Census TIGER reference shapefiles
    • ca_bg_dark — blockgroups ; US Census TIGER reference shapefiles with labeling
    • ne_10m_urban_areas — NaturalEarth dataset; simplified urban area boundaries
  • Orthophotos Aerial imagery with the camera oriented straight-down is sometimes called the Bombardier’s View and is a typical method to create orthophotos. Tracing vector assets over orthophotos is common. Every one of the major imagery providers does have alignment issues in various local geographical areas. In the JOSM Openstreetmap editing environment, there are provisions for storing offsets, per local area, per imagery provider (e.g. MapBox Satellite versus BING in Central Europe). However, given current mapping feature density, it is possible for an OSM editor to simply copy the offsets of other features around them, somewhat analogous to driving a car in traffic at the same speed as the other cars, irregardless of the posted speed limit. Imagery alignment does matter and poor alignment can be the source of errors, but modern image analysis benefits from a crowd effect of multiple, stable reference sets in most all areas. These benefits are most quickly exploited by a human operator; using reference data to stabilize offsets in a machine learning environment is TBD.


naip_08_bkrsfld_align_test1 sangis_nonresidential_base newport_beach_sample_15sep16 osm_bldgs_bing_align0

osm_bldgs_mapbox_misalign0 align_labldgs_raw_naip_2009


MapViewer osmb / NAIP 2014 Detail


NAIP 2016 Image Data for California

  example   Source Ortho Imagery Attributes
Data axis to CRS axis mapping: 1,2
Origin = (577188.000000000000000,4150908.000000000000000)
Pixel Size = (0.600000000000000,-0.600000000000000)
    TIFFTAG_SOFTWARE=Trimble Germany GmbH
Image Structure Metadata:
Corner Coordinates:
Upper Left  (  577188.000, 4150908.000) (122d 7'36.20"W, 37d30' 6.77"N)
Lower Left  (  577188.000, 4143612.000) (122d 7'38.95"W, 37d26'10.04"N)
Upper Right (  583086.000, 4150908.000) (122d 3'36.01"W, 37d30' 4.92"N)
Lower Right (  583086.000, 4143612.000) (122d 3'38.97"W, 37d26' 8.20"N)
Center      (  580137.000, 4147260.000) (122d 5'37.53"W, 37d28' 7.50"N)

  Band   1  Block=9830x1 Type=Byte, ColorInterp=Red
  Band   2  Block=9830x1 Type=Byte, ColorInterp=Green
  Band   3  Block=9830x1 Type=Byte, ColorInterp=Blue
  Band   4  Block=9830x1 Type=Byte, ColorInterp=Undefined

NAIP 2016 Image Processing Onsite @ MAPLABS Berkeley

## production run image processing scripts
##  re-sample, color model, compression to output format(s)



DOQQ coverage as of 13Feb17

DOQQ Infrared (IR) areas processed as of 13Feb17

Calibrating the placement and overlap of DOQQs

Masking Trouble in Paradise, California.

digital ortho quarter quad tiles (DOQQs) * Native Resolution

digital ortho quarter quad tiles (DOQQs) * 3x Resolution

digital ortho quarter quad tiles (DOQQs) * ex0

digital ortho quarter quad tiles (DOQQs) * Infrared Band

An Infrared (IR) View of Tree-filled Downtown Arcata, Calif.