Lecture 12 Data Standards and Quality & New Developments in GIS
Lecture 12: Outline I. Data Standards and Quality 1. Types of Spatial Data Standards 2. Data Accuracy 3. III. Documenting Spatial Data Accuracy 4. IV. Positional Accuracy 5. Attribute Accuracy II. New Developments/The Future of GIS 1. Future Hardware 2. Future Software 3. Future Research Issues 4. New Developments
Data Standards and Data Quality Spatial Data Standards: Methods for structuring, describing, and delivering spatially-referenced data. Four Areas of Spatial Data Standards: 1. Media Standards: The physical form in which data are transferred. 2. Format Standards: Data file components and structures. 3. Spatial Data Accuracy Standards: Document the quality of positional and attribute values stored in a spatial data set. 4. Documentation Standards: Define how we describe spatial data.
Data Standards and Data Quality Four Areas of Spatial Data Standards: 1. Media Standards: The physical form in which data are transferred. Drive Type Name The drive can: CD-ROM Compact Disk Read Only Memory Read CD-ROM and CD-R CD-ROM multiread --''-- Read CD-ROM, CD-R and CD-E CD-R Compact Disk Recordable Read CD-ROM and CD-R. Write once on special disks named CD R CD-RW Compact Disk ReWritable Read CD-ROMs and CD-R. Write and re-write on special disks (CD-RW). DVD RAM Digital Versatile Disk Random Access Memory Reads all CD formats. Reads DVD ROM. Reads and writes DVD disks
Data Standards and Data Quality Four Areas of Spatial Data Standards: 2. Format Standards: Data file components and structures. USGS: http://nationalmap.gov/gio/standards ESRI: E00, shapefile, geodatabases SDTS: Spatial Data Transfer Standards http://mcmcweb.er.usgs.gov/sdts/
Data Standards and Data Quality Four Areas of Spatial Data Standards: 3. Spatial Data Accuracy Standards: Document the quality of positional and attribute values stored in a spatial data set. Ways to Describe Spatial Accuracy: Positional Accuracy - How close locations of objects represented in a digital data correspond to the true locations. Attribute Accuracy - Summarizes how different the attributes are from the true values. Logical consistency - Reflects the presence, absence, or frequency of inconsistent data. Completeness - Describes how well the data set captures all the features it is intended to represent.
Data Standards and Data Quality Four Areas of Spatial Data Standards: 3. Spatial Data Accuracy Standards: Document the quality of positional and attribute values stored in a spatial data set. Ways to Describe Spatial Accuracy: Positional Accuracy Positional Accuracy Standards 1:1,200 ± 3.33 feet 1:2,400 ± 6.67 feet 1:4,800 ± 13.33 feet 1:10,000 ± 27.78 feet 1:12,000 ± 33.33 feet 1:24,000 ± 40.00 feet 1:63,360 ± 105.60 feet 1:100,000 ± 166.67 feet
Data Standards and Data Quality Four Areas of Spatial Data Standards: 3. Spatial Data Accuracy Standards: Document the quality of positional and attribute values stored in a spatial data set.
Data Standards and Data Quality Four Areas of Spatial Data Standards: 4. Documentation Standards: Define how we describe spatial data. 1. Data documentation describes the source, development and form of spatial data. 2. Metadata!
Data Standards and Data Quality Accuracy: How often or by how much data values are in error. How far is a spatial feature from its true location? Positional Accuracy Precision: How repeatable a process or measurement may be. How far is the set of repeat measurements from the average measurement?
Data Standards and Data Quality Positional Accuracy Federal Geographic Data Committee of the United States (FGDC) FGDC developed the National Standard for Spatial Data Accuracy (NSSDA). Presents a standardized method for presenting positional error. Identify a set of test points from the digital data under scrutiny. Identify a data set or method from which true values will be determined Collect positional measurements from the test points as they are recorded in the test and true data set. Calculate positional error for each test point and summarize the positional accuracy for the test data in a standard accuracy statistic. Record the accuracy statistic in a standardized form that is included in the metadata description of a data set.
Multiply RMSE by 1.7308 to estimate 95% accuracy level. This means that 95% of the time, horizontal accuracy is expected to be less that 12.9 meters.
Data Standards and Data Quality Attribute Accuracy There is no standard for measuring and reporting attribute accuracy. Usually, you will create random test points, assess their true attribute and compare it to your spatial data. This will result in an error table.
New Developments/The Future of GIS Future Hardware: GIS has incorporated advanced database techniques and will most likely continue to do so. The personal computer has allowed GIS to be applied to new fields and has improved GIS education. The mobility of portable GIS and GPS has revolutionized GIS use.
New Developments/The Future of GIS Future Software: Improvements to the user interface End to raster/vector debate Increased programming capability Increase in customized GIS applications Scientific visualization tools (http://www.esri.com/software/arcgis/extensions/3danalyst/index.html ) Spatial analysis tools (e.g. SPlus) Increased ability with computer networks Ability to create animated and interactive maps
New Developments/The Future of GIS Future Research Issues: Privacy will become a critical issue for GIS as use expands to legal applications. Data ownership will remain critical to GIS, with a delicate balance between public and private GIS data. Standardization of GIS education, creation of agreed upon standards for data use, analysis, and general GIS application.
New Developments/The Future of GIS Future Hardware: - GPS Integration
New Developments/The Future of GIS Future Hardware: - Mobility and GPS Integration
New Developments/The Future of GIS Improved Remote Sensing
New Developments/The Future of GIS Internet Mapping Google Earth ESRI s ArcGIS Server
Geovisualization New Developments/The Future of GIS
New Developments/The Future of GIS Open Standards for GIS: Seeks to reduce technical barriers to sharing data and information. OpenGIS Consortium: Developed a framework to ensure interoperability. In the future, expect more emphasis on compliance with OpenGIS standards. Open Source GIS: Free software distributed with the source code. General Purpose GIS: GRASS, FMaps Web-Based GIS: Open Layers, Google Mashups