One of the many strengths of a GIS is that you can stack several data layers on top of each other for visualization or analysis. For example, if you

Transcription

1 One of the many strengths of a GIS is that you can stack several data layers on top of each other for visualization or analysis. For example, if you overlay a map of the habitat for an endangered species and a land stewardship layer you can find out who is managing the land where the species exists. The concept of overlay analysis is easy, however it can get complicated because real world objects in a GIS can be represented by different features such as points, polygons, lines and pixels. Each type of overlay requires a unique analysis procedure in a GIS. For example point over polygon overlay is different from point over pixel overlay etc. 1

2 Remember the three types of vector data: points, polygons and lines? 2

3 .and then there is raster data where the real world features are represented by pixels (cells). 3

4 This map illustrates a point over polygon overlay. The polygons here represent different vegetation types created via aerial photo interpretation. The points are GPS coordinates for vegetation plots characterizing the vegetation in the area. The GPS points will be used to estimate how accurate the photo interpreted map is. 4

5 This is a similar map where the vegetation layer was created via image analysis of a satellite image resulting in a raster dataset (grid) where all green pixels represent vegetation type 1, the brown pixels vegetation type 2 etc. Again, the orange points are GPS locations for ground control points. 5

6 Two overlay analysis principles will be described here: 1 the piercing needle approach 2 the cookie cutter approach. Both methods involves extracting data from multiple GIS data layers at locations of interest. In the piercing needle approach information from one or more data layers are extracted at one single point (point polygon overlay). For example, you may want to know the habitat type and canopy cover at bird nest locations. In this case the bird nests are represented by a point layer and the habitat type, elevation and canopy cover is represented by individual polygon data layers. The result of such an analysis will be a table that contains the habitat type and canopy cover for each bird nest location in your dataset. 6

7 This table gives you information on what tool in ArcGIS (or ArcView 3.x or ArcInfo) you can use to create a point to polygon or point to grid overlay. For example in a point/polygon overlay, to find the polygon characteristics of the locations where the points are located, use the Join and Relates features. In Exercise 2 which is part of this lesson you will perform these different kinds of overlay analyses. 7

8 Sometimes we want to overlay a polygon layer over another polygon layer or a raster. In the map above the polygons outlined in black represent fire perimeters and the raster map represents different cover types. An overlay analysis can here tell you the cover types within the fire perimeters. 8

9 The other overlay approach is the cookie cutter approach. This is an example of a polygon to polygon overlay analysis. Going back to the bird nest example, rather than extracting data from the exact bird nest location it might be interesting to analyze the conditions within a 100 meter buffer around the bird nest. The first step in such an analysis would be to create a 100 m buffer around the points (nests). The buffers will be represented in a new polygon layer in GIS. Next you would clip or intersect the habitat and canopy cover layers with the buffer layer and finally summarize the hbi habitat types and canopy cover classes within ihi the buffers. If your habitat and canopy cover layers are represented by raster data you would use the raster tools masking, zonal statistics or combine rather than the vector tools clip and intersect. 9

10 The table above guides you as to what tool to use when performing a polygon to polygon overlay (vector overlay) or a poly to grid or grid to grid overlay. We will work with these tools in the lab exercise for this lesson. 10

11 This map shows the vegetation cover types of Idaho overlayed with the fire start locations for fires larger than 640 acres during the time period What cover types do you think has the most fire starts (> 640 acres)? When you estimate the relative abundance of fire in different cover type you must consider how much of each cover type there is in the state. If the entire state was in the sagebrush cover type we would expect all fires to start in sagebrush. If half the state was sagebrush and hlf half was forest you would expect hlfh half the fires to start in sagebrush and half in forest if the start of fires was a random event. Is it? 11

12 This graph shows data extracted from an overlay analysis of the two layers in the previous map (cover types and fire start locations). First, the black bars here show the distribution of vegetative cover types in Idaho. For example ~14% is in agriculture, 8% in native grasses, 3% in exotic grasses etc. Second, the red bars show the proportion of fires (> 640 acre) that started in these cover types. If the red and the black bar are the same height, the number of fires started are in proportion to the land area covered by that vegetation type, ie. random. If the red bars are taller than the black bars there are more fires than expected started in that cover type (more than random). What cover types have a higher proportion of large fires than you would expect if the distribution was random? Answer: (Native grasses, exotic grasses, other shrub, sagebrush) 12

13 In this graph the start locations of large fires in Idaho ( ) are compared to aspect. On what aspects do large fires occur more often than would be expected if the distribution was random? Answer: south, southwest, west 13

14 This map displays the potential vegetation types in the Selway Bitterroot Wilderness. What is a potential vegetation type? Answer: A potential vegetation type is a habitat type, i.e. represents the climax vegetation in an area. How is cover type different from potential vegetation type (habitat type)? Answer: The potential vegetation type (PVT) always represents the climax vegetation while the cover type is the vegetative cover currently occurring in an area. The cover type on a Douglas fir PVT may be grasses or shrubs a few years after a fire, however, given time Douglas fir will dominate the site. 14

15 Zonal statistics is a tool that is used for overlay analysis in GIS. This tool is part of the Spatial Analyst extension. You can here find out what the mean elevation is for forest stands. 15

16 The Zone layer is in this case the forest stands while the Value layer is the elevation layer. The output table will show the mean, max, min etc elevation within each forest stand. 16

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18 Another useful overlay analysis tool is Tabulate Areas in the Spatial Analyst Tools in ArcToolbox. You can here create a cross tabulation based on two data layers. Let s say that you would like to know how much there is of each landcover type in the watersheds within a study area. You must input the two data layers (watersheds and landcover) in this case, but you must also tell the tool what field in the attribute table that you want to tabulate. 18

19 The output table describes how much area there is of each land cover type in each watershed. The results are in square meter (the numbers above are just an example these watersheds would be extremely small!) 19

20 Your first task in todays lab will be to make a map. A proper map should include the following components: Main map, Legend, Title, Scalebar, North arrow, Data source, Locator map. 20

21 Pay some attention to color composition. Colors should be easy to understand, for example it is recommended that you make water blue, forest green, etc. on your maps to make it easier for the map reader to make the connection between the map and the real world. DON T USE DEFAULT COLORS! If possible, avoid mixing red and green on the same map, many individuals have problems distinguishing between these two colors ( red green color blindness ). 21

22 In the following lab you will set up a study area project for the Craig Mountain Wildlife Management Area. The vegetation cover type data layer already exists. In lab 2 you will add roads, streams, land ownership and county boundaries to the map. Many of the layers exist as state wide datasets and you will use the analysis tools in ArcToolbox to clip the layers to the Craig Mountain boundary. In a later lab you will also add a digital elevation model to the Craig Mountain project. In the second part of lab 2 you will practice using a few of the analysis tools in ArcToolbox and also use Xtools. 22

23 Before starting your next lab I have a few general TIPS to share. If you follow these rules you are more likely to be able to complete the laboratory exercises. 1. Do NOT use spaces in the folder names that contain GIS data. Also avoid using spaces in file names or anything that has to do with GIS. 2. Use ArcCatalog for all data management such as copying, deleting, or moving data sets. If you use Windows Explorer or My Computer for data management you may corrupt files. 3. Manage your data well, i.e. keep data in project related folders. This will enable you to easily transfer entire projects to a CD. 23

24 In Exercise 2 and in many of the following exercises in CNR402 you will be working with data from the Craig Mountain Wildlife Management Area. The Craig Mountain Wildlife Management Area is located north of the confluence of the Snake River and the Salmon River in western Idaho. Size: >65,000 ha (About 250 mi 2, 162,000 ac) Elevation ranges from m ( ft), from the Snake and Salmon Rivers to the forested plateaus with steep, dissected topography. 24

25 Many of the datasets we will be working on through this course originates from the Craig Mountain GIS database. The following slides introduce the vegetation and topography of the Craig Mountain Wildlife Management Area. Mixed conifer forests (background) and mountain meadows dominate on the rolling plateaus at the higher elevations. This is stiff sage (Artemisia rigida) in the foreground. Other meadows support grasses and forbs, some are wet. On this flatter ground at higher elevation, many (but not all) of the forests have been logged, and many (but not all) of the meadows have been grazed by cattle. There is less logging and grazing now than in the past. 25

26 This view is from the top of Corral Creek down toward the Snake River. Forests are more and more interspersed with canyon grasslands as you approach middle elevations. 26

27 You are looking at a north facing slope at middle elevation is Corral Creek. Douglas fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosa) trees grow with diverse shrubs, including ninebark (Physocarpus malvaceous ), oceanspray (Holodiscus discolor), snowberry (Symphoricarpus albus) and rocky mountain maple (Acer glabrum). 27

28 Here is the south facing slope from the same point as the last slide, at middle elevation is Corral Creek. Much of the same vegetation occurs, but the forests are more open and interspersed with grasslands. Topography (both elevation and aspect) have a tremendous influence on the vegetation composition. 28

29 Weeds predominate on the flatter benches, including those far above the river like this one, and those adjacent to the river. All but the smallest, most remote benches were farmed and heavily grazed in the past. 29

30 Yellow star thistle (Centaurea solstitialis), an invasive exotic, has largely outcompeted and replaced the native perennial grasses here. Weed management is a very challenging issue for the managers of both public and private land in the Craig Mountains. The proportion of native species increases, in general, with elevation. More weeds are found near the roads, areas that were once cultivated and heavily grazed, and at low elevations. 30

31 Continuing downhill to the benches at the lowest elevation, we find even more weeds. The gray vegetation in the background is yellow star thistle. The large plants in the foreground are Scotch thistle (Onopordum acanthium). Both are invasive exotic plants. Most of the grasses in the foreground are also exotic. Here Japanese brome (Bromus japonicus) and cheatgrass (Bromus tectorum) predominate; both are annual grasses that are favored by any disturbance. 31

32 This Landsat image is displayed in false color infrared color combination, that is why the forested areas look red. The green areas are canyon grasslands and the white areas are harvested agricultural fields. There are also some clouds in the lower right of the image. 32

33 In mid August in year 2000 the southern half of Craig Mountain burned in the Maloney Creek wildfire. You can still see the smoke from the Maloney Creek fire and also from other fires burning to the south of the Salmon River. 33

34 This is a close up of the Craig Mountain area before and after the Maloney Creek fire. 34

35 This vegetation data was produced by the Idaho Gap Analysis Project ( It was interpreted from Landsat satellite imagery and has a resolution of 30 m and has been locally ground referenced. The thematic accuracy of the data layer is approximately 70% meaning that if you go to any single pixel on the map the chance is 70% that the cover type is actually what is says it is in the map key.. 35

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