GIS Data Capture: Getting the Map into the Computer Chapter 9, Longley et al.

1. GIS Data Capture:Getting the Map into the ComputerChapter 9, Longley et al.

2. Overview • Introduction • Primary data capture • Secondary data capture • Data transfer • Capturing attribute data • Managing a data capture project • Error and accuracy

3. Data Collection • One of most expensive GIS activities • Many diverse sources (source integration, data fusion, interoperability) • Two broad types of collection • Data capture (direct collection) • Data transfer • Two broad capture methods • Primary (direct measurement) • Secondary (indirect derivation)

4. Preparation Evaluation Planning Digitizing / Transfer Editing / Improvement Stages in Data Collection Projects

5. Data collection purposes:

6. Data Collection Techniques

7. Primary Data Capture • Capture specifically for GIS use • Raster – remote sensing • e.g. SPOT and IKONOS satellites and aerial photography • Passive and active sensors • Resolution is key consideration • Spatial • Spectral • Temporal

9. www.spot.ucsb.edu

10. Imagery for GIS

11. Vector Primary Data Capture • Surveying • Locations of objects determines by angle and distance measurements from known locations • Uses expensive field equipment and crews • Most accurate method for large scale, small areas • GPS • Collection of satellites used to fix locations on Earth’s surface • Differential GPS used to improve accuracy

12. Total Station

13. Pen/Portable PC and GPS

14. Secondary Geographic Data Capture • Data collected for other purposes can be converted for use in GIS • Raster conversion • Scanning of maps, aerial photographs, documents, etc • Important scanning parameters are spatial and spectral (bit depth) resolution

15. Scanner

16. Raster to vector conversion

17. Vector Secondary Data Capture • Collection of vector objects from maps, photographs, plans, etc. • Digitizing • Manual (table) • Heads-up and vectorization • Photogrammetry – the science and technology of making measurements from photographs, etc.

18. Digitizer

19. GEOCODING • spatial information ---> digital form • capturing the map (digitizing, scanning) • sometimes also capturing the attributes • “mapematical” calculation, e.g., • address matching WSW

20. The Role of Error • Map and attribute data errors are the data producer's responsibility, • GIS user must understand error. • Accuracy and precision of map and attribute data in a GIS affect all other operations, especially when maps are compared across scales.

21. Accuracy • closeness to TRUE values • results, computations, or estimates • compromise on “infinite complexity” • generalization of the real world • difficult to identify a TRUE value • e.g., accuracy of a contour • Does not exist in real world • Compare to other sources

22. Accuracy (cont.) • accuracy of the database = accuracy of the products computed from database • e.g., accuracy of a slope, aspect, or watershed computed from a DEM

23. Positional Accuracy • typical UTM coordinate pair might be: • Easting 579124.349 m • Northing 5194732.247 m • If the database was digitized from a 1:24,000 map sheet, the last four digits in each coordinate (units, tenths, hundredths, thousandths) would be questionable

24. Map scale Ground distance corresponding to 0.5 mm map distance 1:1250 62.5 cm 1:2500 1.25 m 1:5000 2.5 m 1:10,000 5 m 1:24,000 12 m 1:50,000 25 m 1:100,000 50 m 1:250,000 125 m 1:1,000,000 500 m 1:10,000,000 5 km Positional Accuracy A useful rule of thumb is that positions measured from maps are accurate to about 0.5 mm on the map. Multiplying this by the scale of the map gives the corresponding distance on the ground.

25. Testing Positional Accuracy • Use an independent source of higher accuracy: • find a larger scale map (cartographically speaking) • use GPS • Use internal evidence: • digitized polygons that are unclosed, lines that overshoot or undershoot nodes, etc. are indications of inaccuracy • sizes of gaps, overshoots, etc. may be a measure of positional accuracy

26. Precision • not the same as accuracy! • repeatability vs. “truth” • not closeness of results, but number of decimal placesor significant digits in a measurement • A GIS works at high precision, usually much higher than the accuracy of the data themselves

27. Accuracy vs. Precision

28. Accuracy vs. Precision

29. Components of Data Quality • positional accuracy • attribute accuracy • logical consistency • completeness • lineage

30. Data Transfer • Buy vs. build is an important question • Many widely distributed sources of GI • Includes geocoding • Key catalogs include • Geodata.gov • Geography Network • Access technologies • Translation • Direct read

31. GPS “Handhelds” text geographic coordinates photos video audio Bluetooth, WiFi

32. cell towers +/- 500 m Google db of tower locations Wi-Fi +/- 30 m Skyhook servers and db GPS +/- 10 m iPhone uses reference network Graphic courtesy of Wired, Feb. 2009

33. “Power to the People:”VGI & PPGIS • “Volunteered Geographic Information” • Wikimapia.org • Openstreetmap.org • Aka “crowdsourcing” • “Public Participation GIS” • GEO 599, Fall 2007 • Papers still online at dusk.geo.orst.edu/virtual/

34. Example: A Boon for International Development Agencies Kinshasa, Democratic Republic of Congo Robert Soden, www.developmentseed.org

35. International Development, Humanitarian Relief Mogadishu, Somalia Robert Soden, www.developmentseed.org

36. Haiti Disaster, MapAction.org

37. “Citizen Sensors” UCLA Center for Embedded Networked Sensing, http://peir.cens.ucla.edu

38. Google Maps Mania Blog Societal Issues(privacy, surveillance, ethics)e.g., Google StreetView Early and late May 2008

39. More surveillance (electronic, video, biological, chemical) integrated into national system From Chris Peterson, Foresight Institute As presented at OSCON 2008, Portland

40. From Chris Peterson, Foresight Institute As presented at OSCON 2008, Portland Graphic: Gina Miller

41. Sewer monitoring has begun “The test doesn’t screen people directly but instead seeks out evidence of illicit drug abuse in drug residues and metabolites excreted in urine and flushed toward municipal sewage treatment plants.” From Chris Peterson, Foresight Institute As presented at OSCON 2008, Portland