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Geographic Information Systems Applications in Natural Resource Management. Chapter 3 Acquiring, Creating, and Editing GIS Databases. Michael G. Wing & Pete Bettinger. Chapter 3 Objectives. Methods to acquire GIS databases, particularly via the Internet
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Geographic Information SystemsApplications in Natural Resource Management Chapter 3 Acquiring, Creating, and Editing GIS Databases Michael G. Wing & Pete Bettinger
Chapter 3 Objectives • Methods to acquire GIS databases, particularly via the Internet • Methods to create new GIS databases • Processes to edit existing GIS databases • Types and sources of error potentially associated with GIS databases
Four general cases of GIS databases at most organizations • The data necessary for project work • Don’t exist • Do exist but were created for other general uses and may not be completely suitable for your project • Do exist but were created for other specific uses and may not be completely suitable for your project • The data are in place and in good order for your project!
Typically, you’ll have to acquire data • Hire a contractor to create or edit GIS data • Use a GPS or other device to capture data • Modifying an existing database • Create a new GIS database • Digitizing • Using/buying data from another organization • Downloading data from the Internet
Internet acquisition • Now a standard method of making data available • Many federal and state organizations make spatial data available • The U.S. Government is the largest producer of spatial data in the world • Manual of Federal Geographic Data Products • Freedom of information act allows the public some access to data created by public agencies • Use these data to save time
Oregon Data Sources • Oregon Geospatial Data Clearinghouse (OGDC) • Formerly the SSCGIS • Demonstration • OSU College of Forestry • Bureau of Land Management (BLM)* • National Forest Offices (SNF) • StreamNet* • Oregon Department of Fish and Wildlife (ODFW)* • Environmental Protection Agency (EPA)*
National Data Sources • US Geological Survey (USGS)* • Bureau of Land Management (BLM)* • National Park Service (NPS)*
Acquisition processes • Using an Internet browser to select and download • FTP- File Transfer Protocol • Transfer on hardware • Tape • External harddrive • CD or DVD • USB key • Floppy
Creating GIS databases • We’ve covered techniques in Chapter 1 • Digitizing • Remote Sensing • Satellite imagery • LIDAR • Laser range finder • Total station • Scanning • GPS
Roads Stands Reference points (with associated X and Y coordinates) Figure 3.1. Measurement reference points for the Daniel Pickett forest to enable digitizing of additional landscape features or the creation of new GIS databases.
Figure 3.2. A landslide drawn on a map with a regular sharpened pencil (upper left), a marker (upper right), a sharpened pencil, yet in a sloppy manner – the landslide area is not closed (lower left), a marker, yet in a sloppy manner - the landslide area is barely closed (lower right).
(a) (b) (c) Figure 3.3. A timber stand (a) in vector format, from the Brown Tract, scanned (b) or converted to a raster format using 25 m grid cells, then converted back to vector format (c) by connecting lines to the center of each grid cell.
Editing GIS databases • Reasons for editing • Changing a spatial projection • Edge matching GIS databases to other databases • Generalization and transformation processes necessary to convert a GIS database to a specific format or resolution • In natural resources, updates may occur annually to keep pace with timber inventory • Growth, disturbance, harvesting
Updating processes • Can be laborious and error-prone • Verification protocols can help • Assures that data variables are reasonable or meet some standard • Should be in place for spatial and attribute characteristics • Should involve multiple people
Inventory forester Information systems analysts maps, data files Delineate changes to be made to inventory Check data for mistakes and omissions maps, data files Verification process #1 maps, data files Digitize changes to spatial data, encode inventory maps, data files GIS databases Check data for mistakes and omissions Verification process #2 maps, data files Integrate into GIS database GIS databases Check data for mistakes and omissions Check data for mistakes and omissions Verification process #4 Verification process #3 Figure 3.4. A generalized process for updating a forest inventory GIS database.
Editing attributes • Attributes are the values used to describe landscape features in a GIS database • Fields, variables, columns, data, etc. • Attributes may need to be updated overtime • Vegetation type, basal area, age, volume (mbf) • Easy to make mistakes, particularly with major updates • Verification processes can check whether values are in the appropriate range
Editing spatial position • As the locations or shapes of spatial features change, their coordinates will need to be changed within the GIS database • Editing procedures for this purpose vary widely among software products • Typically, a database is first made “editable” • The user then makes edits • Points, lines, and/or polygons moved, copied, created, or deleted • The edits are saved • Often, a time-consuming procedure
Consistency in spatial position • When updating or creating new data, inconsistencies may result as the data are incorporated into existing databases
Inconsistency Roads Timber stands Figure 3.5. A timber stand drawn more precisely (top) and less precisely (bottom). Note that the lines on the south and eastern portion of the figures are different. Figure 3.6. Spatial inconsistency between a timber stand GIS database and a roads GIS database.
Error in GIS databases • Errors arise from many sources: • Editing, encoding, hardware, and others • Three primary sources of error in GIS data • Systematic • Human • Random
Systematic errors • Caused by problems in the processes and/or tools used to measure spatial locations or attribute data • Sometimes called cumulative errors since they add up during data collection • Sometimes called instrumental • Can be removed if identified and quantified
Human errors • Sometimes called gross errors or blunders • As the name suggests, these are introduced through carelessness or other inattention • Verification processes can be used to control human errors • Data collection and editing protocols can also assist in limiting human errors
Random errors • An almost unavoidable by-product of measuring and describing landscape data • No matter how careful we are in data collection procedures, there will almost always be some slight variance from the true measurement • Random errors are the errors that remain after systematic and human errors have been removed
Managing random errors • We assume that random errors follow a normal (Gaussian) distribution • They cluster around a mean value or center • Least squares adjustments can distribute and minimize the error among all measurements in a feature • More frequently, and especially in forestry, we assume that random errors will cancel each other out • For this reason, random errors are sometimes called compensating errors
Types of errors in GIS databases • Positional errors occur when things are in the wrong place • Can result from poor registration or inaccurate coordinate input during the digitizing process • Are sometimes handled with accuracy statements: “90 percent of landscape features are within 150 meters of their true position” • A root mean square error (RMSE) is sometimes used to set or describe an accuracy standard • A RMSE assesses the error between a mapped point and its on-the-ground (true) equivalent
Digitized road segment Real-world representation #1 Real-world representation #2 Real-world representation #3 Figure 3.7. Uncertainty of the local shape of a road segment (after Schneider 2001).
Other types of errors • Attribute errors • Incorrect values assigned to features • Can result from keyboard entry • Verification processes can help alleviate these • Computational errors • Can be introduced during procedures • Generalization • Vector-to-raster transformations • Interpolations • Results should be carefully considered to judge appropriateness of procedures