E.G. please always turn off your cell phone or put it on vibrate mode for class

1. A kind reminder on distractions such as phone use, noise (see syllabus). Please allow fellow students to focus. E.G. please always turn off your cell phone or put it on vibrate mode for class GIS for environmental management Dr. William James Smith, Jr. Assistant Professor of Environmental Studies, UNLV Adjunct Assistant Professor in Geography, The University of Iowa

2. Development and population animations http://www.nrel.colostate.edu/~davet/animations.html

3. MAPS AS NUMBERS: Data structures, basic statistics and queries, and topology Geographic Information Legend Mixed conifer Maps as numbers Douglas fir Oak savannah Theme Time Space Grassland Using Arcview software Points Lines Areas Volumes Nominal Raster representation. Each color represents a different value of a nominal-scale field denoting land cover class. Ordinal Interval Ratio

4. But that is not the main topic of discussion for this type of class We will focus on data structures again and then connect them to topology Topology The property that describes adjacency and connectivity of features. A topological data structure encodes topology with geocoded features.

5. We require a mental model of how the physical data represent a geographic figure. Traditionally there have been two types of data model for map data. 1. Raster format 2. Vector format Standards. Attributes. Formats. Topology. Key terms

6. Raster model Uses a grid, like coordinate systems we discussed do, to hold the data. Each grid cell in the grid is one map unit, often selected so that each cell shows on the GIS map as one screen display point or pixel, or on the ground as a whole number increment in the coordinate system. 5

7. When we capture a map into the raster model we have to assign a value to every cell in the grid. The value we assign can be an actual number such as terrain elevation in a DEM, or an index value standing for an attribute stored in a database.

8. The cell size determines the resolution of the data and the cell size has both a ground and map expression. On a map we may use several pixels to display the grid cell, or on paper we may use a dot of a certain size in a given color.

9. Resolution • Resolution increases as the size of the cell decreases; however, coding, database storage, and processing speed for analysis are more costly.

10. Composition of a Raster data set • Raster is made up of cells • Cells have coordinates • Cells have attributes • Integers: categorical or nominal values • Floating point

11. Composition of a Raster data set • Each cell is assigned a specific value to identify or describe the class, category, or group the cell belongs to (categorical data). • Examples of categorical data include soil type, soil texture, landuse class, water body type, road class, and housing type.

12. Data dictionary: The part of a database containing information about the files, records, and attributes rather than just the data. Attributes have a database dictionary of sorts, this lists of attributes and their characteristics. Sometimes its is a separate file(s) and other times it is written in to the top or header of the file before the data begin. Digital Chart of the World hard copy data dictionary E.G. DEM hack if time

13. We often speak of Landsat imagery being 30 meter. This means that each cell in the data is 30 meters by 30 meters on the ground. YOU CAN ZOOM IN ALL YOU WANT BUT IT DOES NOT IMPROVE BEYOND THAT! E.G. people do not show up. Foreshadow - FSM 30, 4, 1 at same spot different things show up. Zoom in on volcano tiff from last class to look for trash

14. Composition of a Raster data set • Raster organized in rows and columns • Upper left corner defines origin • Spatial extent by origin and cell size • Again, resolution is a matter of cell size

15. Discrete Continuous Discrete v Continuous Models

16. Representing features in a raster dataset - areas • The accuracy of the raster representation is dependent on the scale of the data and the size of the cell. The finer the cell resolution and the greater the number of cells that represent small areas, the more accurate the representation.

17. Earth at night

18. There must be a link between the raster or vector and the flat file. -For a raster grid we could store index numbers in the grid and any number of attributes for the index numbers of attributes in the flat file. LAND USE MAP 1=FOREST 2=FARMLAND 3=URBAN See DCW -- if raster data O.K. there

19. Raster data structures Each pixel or grid cell contains either a data value (e.g. “brightness”) for an attribute, or an index number that points to a reference in the attribute database. Again, pixel =s 2 and then 2 always = oak forest anywhere on the map, then that pixel is oak -- and patterns manifest. To write numbers to a file start with writing attribute codes, the number of rows and columns and maximum size of value possible, then convert to binary in all rows and columns.

20. Advantages - An operation such as comparing a grid cell with its neighbors can be performed by looking at the values in the next and preceding row and column of the grid cells in question. - TIN structure in vector fit easily in raster. - Remote sensing or scanning. Disadvantages - Not good at representing lines or points since each become a whole cell in the grid -- making lines disconnected or fat if they cross the grid at a shallow angle. - Mixed pixels are a problem page 76 CLARKE, as sometimes more than one type of attribute occupies a cell, and then if there are two classes an edge pixel is assigned, but when lots of types exist in the cell we need to assign computational rules, such as the majority attribute takes the whole cell

22. Composition of a Raster data set • Raster data can be organized into zones of cells with similar values. • Each group of connected cells in a zone is considered a region.

23. Legend Mixed conifer Douglas fir Oak savannah Grassland Raster representation. Each color represents a different value of a nominal-scale field denoting land cover class.

24. We need to decide what patterns are legal, e.g. diagonal vs. cardinal. Each grid cell can usually only be owned by one feature, that is, the one whose attribute it holds. But that is not the real world! Soils for example, are often listed by percent of sand, silt and clay. And the grid may be 49 percent water and 51 percent land, but the cell must be one. DEMO Lat/long over counties to make grid of land water See why lots of cells at high resolution is best? Each cell must be able to hold maximum data possible, so as the rows X columns space is eaten up fast.

25. Representing features in a raster dataset - points • Point data • Point data have area depending on resolution or cell size (centroid)

26. Representing features in a raster dataset - lines • As with point data, linear features will become the width of the cell. DEMO CENTROIDS FOR BASINS AND TAX PARCELS & LINE TO RASTER ELE exts in topology pjr

27. Last word, you can convert from vector to raster easily, but the other way makes is more complicated. Either way you need to avoid problems like lines overlapping (e.g. streams).

28. Typical sources of local data you might use. Digital Orthophoto Quad

29. Digital Raster Graphic

30. Surfaces -- some examples

31. What are TINs? TIN: A vector topological data structure designed to store the attributes, usually geographic surfaces. Uses contiguous non-overlapping triangle facets. Not as efficient as grids, but good for detailed large scale apps and better for position of roads, etc. (as triangle edges) than grids. But needs relatively better data to be worth using (e.g. not for DEMs at U.S. scale). See Using AV 3D pp 24-25 figs

32. Digital Elevation Models grid elevation sources Definitions More TINs and other models later in the semester -- not on your midterm. DEMO ELE TO GRID TO TIN

33. Volumes (surfaces) are structured with the TIN model, including edge or triangle topology. TINs use an optimal Delaunay triangulation of a set of irregularly distributed points. TINs are popular in CAD and surveying packages. Chuuk Demo in topology vector only view with DEM

34. Disadvantages include high costs and processing power / time More on using such data to drape, for flow, aspect, slope, visibility/view-sheds, watersheds, etc. later And more on querying and exploring their relationships and making calculations to produce maps later

36. Concentration Diffusion Continuous Surface Models

37. Satellite Imagery

39. Satellite Imagery

40. Online rastser only GISgrid outputs with cells user defined • http://www.ngdc.noaa.gov/mgg/gdas/gd_designagrid.html

46. http://www.nrel.colostate.edu/~davet/animations.html

47. Positive aspects -They are easy to understand. -Capable of rapid retrieval and analysis -Easy to draw on a screen and devices that display pixels. Chuuk or NV topo

48. Ways around the raster data hog problem Run-length encoding It looks at CHANGES between attributes and the numbers of them stored. If a whole row is a class, then it is stored as such, and not lots of cells individually. Not much help if the raster image is quite varied!

49. Quad tree can help too Divides the grid into 4 quadrants, saving a reference to a given quadrant only if it hosts the data desired. And that quadrant is also divided, and so on till one quadrant has all of the same pixels desired.

50. Less resource intensive technique utilizing vector topology, rather than raster topology, to get at a very similar environmental issue Interpolation