ENGRG Introduction to GIS

Transcription

1 ENGRG Introduction to GIS Michael Piasecki April 3, 2014 Lecture 11: Raster Analysis GIS Related? 4/3/2014 ENGRG Intro to GIS 2 1

2 Why we use Raster GIS In our previous discussion of data models, we indicated that Raster GIS is often used because: Raster is better suited for spatially continuous data like elevations Raster is better for creating visualizations and modeling environmental phenomena Other continuous data may include: air pressure, temperature, salinity, etc.. Raster data is a simplified realization of the world, and allows for fast and efficient processing A raster GIS performs geoprocessing tasks on a grid based realization of the world 4/3/2014 ENGRG Intro to GIS 3 Outline Today Map Algebra Concept Typical Local Operation Typical Neighbor Operation Moving Window (size, shape and margin erosion) Common operations Typical Global Operation Cost Distance Operations in ArcGIS Spatial Analysis Environmental Setting Toolbox 4/3/2014 ENGRG Intro to GIS 4 2

3 Map Algebra Map algebra and raster GIS is quite simple to visualize in a spread sheet. An example of multiplication and addition The use of arrays make map algebra and raster GIS very computationally efficient But, be careful of: Layers that are not coincident Different cell sizes 4/3/2014 ENGRG Intro to GIS 5 Map Algebra Map algebra is a cell by cell combination of raster layers using mathematical operations Basic Mathematical Operations Addition, subtraction, division, max, min, virtually any mathematical operation you would find in an Excel spreadsheet Strong analytical functions Some Map Algebra Commands in ARC/INFO Outgrid = grid1 + grid2 Outgrid = grid1 * 2 Outgrid = sin(grid1) Outgrid = costallocation(sourcegrid, costgrid, accumgrid, backgrid) Outgrid = con(>5 (ingrid1),0,ingrid1) Outgrid = select(grid1, VALUE = 10 ) 4/3/2014 ENGRG Intro to GIS 6 3

4 Map Algebra It is a simple syntax similar to any algebra Spatial Analysis language Developed by C. Dana Tomlin (1990) Implemented in many grid analysis packages, including ArcGIS, Idrisi, ArcView Spatial Analyst; The implementation in ArcGIS is Raster Calculator Four classes of operations: Local, Focal, Zonal and Global 4/3/2014 ENGRG Intro to GIS 7 Raster Calculator 4/3/2014 ENGRG Intro to GIS 8 4

5 Raster Operations 4/3/2014 ENGRG Intro to GIS 9 Local Operations Work on single cells, one after another, value assigned to a cell depends on this cell only Examples: arithmetic operations with a constant, or with another grid also logical operations, comparisons (min, max, majority, minority, variety, etc.) same location but different layers Reclassification 4/3/2014 ENGRG Intro to GIS 10 5

6 Local Operations 4/3/2014 ENGRG Intro to GIS 11 Focal Operations Assign data value to a cell based on its neighborhood (variously defined) Neighborhood: a set of locations each of which bears a specified distance and/or directional relationship to a particular location called the neighborhood focus (D. Tomlin) distance and directional neighbors immediate and extended neighbors metric and topological neighbors neighbors of points, lines, areas

7 Define Neighborhoods: Shapes /3/2014 ENGRG Intro to GIS 13 Neighborhood Statistics in Spatial Analyst shape of neighborhood: Circle Rectangle Doughnut Wedge Star size of neighborhood: radius (circle), inner and outer radius (doughnut), radius, start and end angles (wedge), width and height (rectangle) Operation: Minimum Maximum Mean Median Sum Range Standard Dev. Majority Minority Variety 4/3/2014 ENGRG Intro to GIS 14 7

8 Define Neighborhood: Moving Window Moving Window: A window : cells used to specify the input values for an operation. 4/3/2014 ENGRG Intro to GIS 15 Focal Operations 4/3/2014 ENGRG Intro to GIS 16 8

9 GIS Solution to Margin Erosion Example of mean kernel 4/3/2014 ENGRG Intro to GIS 17 Neighborhood Operations 4/3/2014 ENGRG Intro to GIS 18 9

10 Neighborhood Operations smoothing moving averaging edge detection Grade (slope) Orient (aspect) Profile High pass filter assessing variety, etc. 4/3/2014 ENGRG Intro to GIS 19 Noise Highlight (high pass filter) 4/3/2014 ENGRG Intro to GIS 20 10

11 Noise Reduction (low pass) 4/3/2014 ENGRG Intro to GIS 21 Spatial Filtering Low and High Frequency Detail and Edges 543 Composite Result of ENVI 15x15 High Pass Filter Edge Finding High Pass filters emphasize high texture, low pass filters suppress, or minimize texture 4/3/2014 ENGRG Intro to GIS 22 11

12 Directional Edge Detection 4/3/2014 ENGRG Intro to GIS 23 Overlay in Raster Map Algebra Overlay functions in map algebra may be performed through addition and multiplication. Union operations with layer addition, clip operations through multiplication. Union by addition: Where cells don t overlap (value + no data ), new map unambiguous. With overlap, attribute values are added, so be aware of consequences. 4/3/2014 ENGRG Intro to GIS 24 12

13 Layer A values multiplied by 10 No ambiguous products (LayerA * 10) + LayerB 4/3/2014 ENGRG Intro to GIS 25 Raster Clip Make a new map of the area of interest with cell value = 1, others cell value = 0 or NODATA Multiply by existing map 4/3/2014 ENGRG Intro to GIS 26 13

14 Common Raster Command: CON Con: Condition, a command in ArcGIS If (layer1>5) then Output = 1 else Output = 0 End if Nested Con operation: Con(layer1>5, Con(Layer1>10,2,1), 0) If (layer1>5) then if (layer1>10) then output = 2 else output =1 end if Else output = 0 End if Con(layer1>5, 1, 0) /3/2014 ENGRG Intro to GIS 27 CON is used for reclassfication 4/3/2014 ENGRG Intro to GIS 28 14

15 Cost Surfaces Global Operation Contain the minimum cost of reaching cells in a layer from one or more source cells. The cost may be expressed in different units: $ money, time, or other units of merit. Cost = distance * cost per unit of distance (frication surface) The distance from a source cell is combined with a cost per unit of distance (variable or fixed) to calculate a travel cost. Think simple: Distances in cell dimension units are measured to/from cell centers and calculated using RMS formulae that keep values positive. 4/3/2014 ENGRG Intro to GIS 29 Friction Surface: Cost per unit Distance Another way to calculate travel costs Cell values of a friction surface represent the (variable) cost per unit travel distance for crossing each cell. Define cell friction on elevation, land cover, etc. (or even friction: icy slopes!) 4/3/2014 ENGRG Intro to GIS 30 15

16 Cost Surface: varied cost 4/3/2014 ENGRG Intro to GIS 31 Cost of a new power line Land Use Friction or Cost Explanation Agriculture 1 Base Cost Deciduous Forest 4 Cut trees, removed and sold Coniferous Forest 5 Cut trees, less return Urban 1200 Conversion very expensive Pavement 1 Base Cost Suburban 1000 See Urban Barren/Gravel 1 Base Cost 4/3/2014 ENGRG Intro to GIS 32 16

17 Cost Surface Existing Trunk Power line 4/3/2014 ENGRG Intro to GIS 33 Types of Raster Analysis Math Distance Surface analysis Extraction Water based analysis Change cell values Statistical Analysis Conditional Weighted overlay 4/3/2014 ENGRG Intro to GIS 34 17

18 Comparing Two Maps Map comparison is easily facilitated using the Tabulate Area function in ArcGIS (or any decent raster based GIS) Determines the cross tabulation between two grid themes on a cell by cell basis Once the tabulations are made, the data is displayed in a simple matrix Map one is the X axis and Map two is the Y axis 4/3/2014 ENGRG Intro to GIS 35 Cross Tabulation A B B B B C B A C Cross Tabulate A A B B C C A A B Cross Tabulated Grid Assume we have a 9 cell land cover map from 1990 with three categories: A, B, and C. We also have another map from AA BA BB BB BC CC BA AA CB A B C A B C You can see that the resulting cross tabulation provides a pixel by pixel comparison of the interpreted land cover types with the reference land cover. So, for the upper right hand cell, the 1990 data was B, and the 2000 data was also B. Therefore, this is a match between the two data sets. However, in the lower right cell you can see that the 1990 data indicated a value of C and the 2000 data set had a value of B We can now quantify the results into a matrix as shown below. 4/3/2014 ENGRG Intro to GIS 36 18

19 The matrix on the right shows the comparison of two hypothetical data sets. The 1990 data set represents the land use in 1990, while the 2000 data set represents the land use in 2000 As an example, geographic features that were A in 2000, and were A in 1990, represent the upper left hand matrix with the value 2 (there were two pixels that met this criteria). This means that 2 units in the overall map that was A in 1990, was also A in Similarly, the same exists for B and C. The diagonal represents areas that have not changed. But, there may have been times where in 1990 the value was A but in 2000, the value was B. In this case, the 2 represented in the top row of the matrix says that there are 2 units of something we said was A in 1990 but is B in 2000 We can begin to add these number up, by adding an additional row and column. But what do these numbers tell us? 2000 Data 2000 Data 1990 Data A B C A B C A B C 1990 Data A B C /3/2014 ENGRG Intro to GIS 37 The bottom row tells us that there were two cells that were A in both 1990 and 2000, five cells that were B, and two cells that were C. The rightmost column tells us that there were four cells that were A in 2000, three cells as B, and 2 cells as C. Adding up the Diagonal cells says there were 5 cells where we actually got it right A B C 1990 A B C So, the similarities is really a function of: Total cells on the diagonal / total number of cells. ( ) / ( ) = 5/9 =.55% agreement The change is 45%. We can also dig deeper and look at A. In 1990 there were 2 A s. But, by the time 2000 came around there were 4 A s. The A s doubled. But, at what cost: Well, A grew by replacing 2 B s. Therefore, we can see that B lost some ground to A. Imagine a real world example of being able to say that as Developed land grew, it actually grew by replacing Forested land: that s the power of evaluating a cross tabulation. 4/3/2014 ENGRG Intro to GIS 38 19

20 Spatial Analysis Extent Define Extent in ArcGIS Default is the intersection of your input data Could be the union of input data x, y coordinates for the bottom left and the top right corners. Could use bookmark or data frame extent 4/3/2014 ENGRG Intro to GIS 39 Define Analysis Extent in ArcGIS 4/3/2014 ENGRG Intro to GIS 40 20

21 Incompatible Cell Sizes Solution: Resample one map (or both?), so layers have same cell size and are aligned 4/3/2014 ENGRG Intro to GIS 41 Analysis Mask You can specify a processing mask (either a raster or vector layer) to identify cells that will be set to NoData in the output. Input Raster Analysis Mask Output Raster 4/3/2014 ENGRG Intro to GIS 42 21

22 A tour of raster functions in ArcGIS 4/3/2014 ENGRG Intro to GIS 43 ArcGIS Spatial Analyst Extension Raster processing extension to ArcGIS It has tools for performing a broad variety of spatial analyses, and is especially well suited to surface analysis. Used to Create Data Identify Spatial Relationships Locate Suitable Sites Execute sophisticated Path finding Comprehensive modeling and raster analysis capabilities Requires separate license from ESRI than ArcGIS 4/3/2014 ENGRG Intro to GIS 44 22

23 Spatial Analyst capabilities Convert vector features (point, line, or polygon) to grids Calculate distance from every cell to objects of interest (similar to buffers) Generate density maps from point features Create continuous surfaces from scattered point features Derive contour, slope, aspect maps, and hillshades for these features Perform cell based map and discrete cell by cell analyses Simultaneously execute Boolean queries and algebraic calculations on multiple raster layers Perform neighborhood and zone analysis Perform raster classification and display Use data from different image formats 4/3/2014 ENGRG Intro to GIS 45 Spatial Analyst Toolbar 4/3/2014 ENGRG Intro to GIS 46 23

24 Quick Check Spatial Analyst ArcGIS Desktop Help (local computer) ArcGIS Desktop Resource Center (ESRI website) 4/3/2014 ENGRG Intro to GIS 47 Remember Next week NO lecture > Spring Break Keep working on your Project! After Spring Break no more Assigned Labs! > instead, work even harder on your project 4/3/2014 ENGRG Intro to GIS 48 24