Introduction to Raster Data RESM 440 Lecture 13

1. Introduction to Raster DataRESM 440Lecture 13

2. Today • Return tests at end of class today • Topic: • Intro to raster data • This week in lab: • Raster spatial analysis • Exercise 6, part B is due this week at start of lab • Next week in lab: Final exam review, help with final projects • Extra reading: Bolstad, Chapter 2

3. Review • Review: Raster data model • Data made up of cells • Cells are square, arranged in a grid of rows, columns • Forms of raster data: • Images • GRIDs Column Row Cells are square, but entire grids may or may not be square

4. From Lesson 3: Spatial Data Review: Comparing raster and vector

5. From Lesson 3: Spatial Data Review: Which should you use? • Depends on purpose and type of map or analysis! • Modeling/analysis: Generally raster (quicker) • Representation/feature precision: Generally vector • Depends on scale / level of detail needed • Can convert data between the two formats Cheat Lake Vector Cheat Lake Raster

6. Cells and raster datasets • Smallest unit is the cell • Cell size can vary, depending on the dataset • Affects precision and file size Cell size: 100m # Cells: 4 Cell size: 50m # Cells: 16 Cell size: 25m # Cells: 64

7. Cell values • Cells store numeric values • Categorical data: cell values represent types of something (such as land use) • Continuous data: cell values represent actual physical values (such as elevation)

8. Categorical data in GRID format • Numeric values in raster cells represent features or different classes of data • Examples: • Feature datasets converted to raster (streams, roads, watersheds) • Land cover • Soils • Other

9. Continuous data in GRID format • Continuous data • Cell values represent value in a range • May be integer or floating point (decimal values) • Examples: Elevation, Precipitation, Slope Value = 896 m

10. Raster cell values • Cell values represent geographic features • Types of cell values: Binary (0,1) Presence/absence Integers Coded values or whole numbers Floating point Values with decimal places Vector data converted to raster Land use, Elevation (if rounded off) Slope, precipitation

11. Assigning raster cell values • Real-world features are not usually square! • Raster datasets cannot be as “exact” as vector • Some method of generalization required to represent real world in raster cells: • Value at center of cell • Majority value within cell

12. Attribute tables for GRIDs • Categorical (and some small continuous) raster layers will have attribute tables • Table includes Value and Count fields • Value = actual cell value • Count = number of cells (in entire grid) with that value • To find total area: Multiply Count * (Cell Size)2 NLCD Land Use Attribute table

13. Finding area using GRID datasets • Area of one cell = (cell length) x (cell width) • 30m cell size: Area = 900m2 for one cell • Multiply (area of cell) X (count of cell type) to get total area for that type • Example: • 30m cell size • 4 cells of type 11 (open water) • What is total area of open water in m2? Example: Land Use Grid Values are codes for land use types

14. Legends for GRID datasets • GRID data values can be symbolized using various methods in ArcGIS: Unique values Classified Stretched *

15. GRID data examples: Digital Elevation Models (DEMs) • Very useful raster dataset • Cell values are elevations, may be measured in ft or meters (check metadata) • Common DEMs: • 90m cell size • 30m cell size • 10m cell size • 3m cell size * new for West Virginia • Elevations are also known as “Z” values • May have own accuracy statistics associated with “Z” value • Download DEMs from WVGIS Tech Center or USGS National Atlas download site (see previous lecture or class links page)

16. DEM comparison: 3m cell size vs. 30m • Hillshaded relief maps, derived from DEM

17. GRID data examples: Land use/land cover • Many different land use/land cover grid datasets are available: • National Land Cover Dataset (NLCD) 1992, 2001, 2006 • Chesapeake Bay Program land use/land cover (2000) • WV GAP land cover (mid 1990s) • Cell values are land use types • Created from classified satellite imagery • 30m cell size • Download NLCD from WVGIS Tech Center or USGS National Atlas viewer download site (see previous lecture or class links page)

18. Land cover grid example

19. NLCD Land Cover • Available nationwide for 1992, 2001, 2006 • Includes • Land cover (~15 classes) • Percent impervious • Percent canopy cover* * Data poorly edge-matched between regions, use with caution

20. USGS National Map Viewer • ArcGIS toolbar to access data through ArcMap • Website for viewing, downloading data directly • Raster data available: • NLCD land cover, impervious • DEM (elevation) • Orthoimagery • Many other datasets as well

21. National Map Viewer website http://viewer.nationalmap.gov

22. GRID data example: Forest fragmentation Edge Perforated Interior forest Patch forest Transitional Non forest Water Data Source: Classification of Forest Fragmentation, by USGS Available from National Atlas website

23. Summary and key points • Raster data model: Cell based data • Cells: • Cell values (continuous vs. categorical) • Cell size can be different • Attribute tables and GRID datasets • Value and count fields • Finding area using GRIDs • Examples of GRID datasets: DEM, Land use, others • Be sure to review comparison of raster vs. vector data from earlier lesson

24. Coming up… • Spatial Analyst extension (for working with GRID data) • Analysis with GRIDs: • Resampling • Reclassifying • Distance surfaces • Map algebra • Terrain analysis: Slope, aspect, contours, hillshade

25. Midterm exam • Highest grade: 100 • Average grade: 82.6 • See me for specific questions (not your TA) • See grade summary for any assignments you still need to turn in • Exercises count for 30% of class grade!