This lesson will focus on analysis tools for vector data. Be aware that there are two completely different suites of tools in ArcGIS; one that works

Transcription

1 This lesson will focus on analysis tools for vector data. Be aware that there are two completely different suites of tools in ArcGIS; one that works for vector data and one that works for raster data. You cannot use the vector data tools on raster data and vise versa. It is therefore very important to always be aware of what data type you are working with. In Lesson 1 you learned that there are three representations of real world objects when working with vector data in GIS: points, lines and polygons. Raster data is composed of cells (pixels, squares) of a certain size. 1

2 GIS is a tool where you can explore two or more data layers together to reveal relationships that were previously unknown. In Lab 2 you will use the ArcToolbox analysis tools to perform an overlay analysis and a proximity analysis on vector data. Vector data analysis commonly result in tabular data. These tables can be further analyzed in the GIS software or exported to other database programs such as Microsoft Excel or Access. 2

3 ArcToolbox is launched directly from ArcMap the icon looks like a red toolbox. In exercise 2 you will be using tools located under the Analysis Tools tab in ArcToolbox. In Exercise 2 you will be using the clip, intersect, and buffer tools. 3

4 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 id 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. 4

5 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 habitat types and canopy cover classes within 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. 5

6 Do you have a question that could be answered using GIS overlay or proximity analysis? 6

7 Different overlay analysis tools are used in ArcGIS depending on what type of overlay analysis you want to do. Different tools are used for vector and raster data and the tool used also depends on the vector data type, point, line or polygon. The instructions on this slide helps you find the correct tool for the overlay analysis you want to do. 7

8 Different overlay analysis tools are used in ArcGIS depending on what type of overlay analysis you want to do. The Analysis Tools in ArcToolbox are useful for overlay analysis between two polygon data layers while the Spatial Analysis Tools in ArcToolbox are specific to raster data. In the lab exercises we will use many of these tools. 8

9 During an overlay analysis, new polygons are often created. For example, if the shapefile to the left is clipped with the boundary shown in the right figure, new polygons will be created and the area for these new polygons must be updated. 9

10 The area of all polygons in a polygon shapefile can be updated in a few simple steps: 1) Open the attribute table for the shapefile you would like to update the area for 2) Right click on the Area column heading 3) Select Calculate Geometry 4) On the following screen (lower right dialog box on this slide), make sure to select Area for the property and the correct units depending on the coordinate system you are working in. In this class we will work mostly in metric units (UTM coordinates) and you should therefore select meters for the units. 10

11 A polygon attribute table in ArcGIS contains one row for each polygon in the dataset. You are here looking at a polygon layer of land managers on Craig Mountain in Idaho. Commonly a land manager manages more than one polygon on the map. For example the Bureau of Land Management (BLM) manages all the yellow areas (polygons) on the map and hence the attribute table contains many rows where the land manager is BLM. In the summary table all areas managed by the BLM are summarized (expressed in hectares in this example) and the table contains only one line per land manager. A summary table is sometimes called a frequency table. 11

12 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 tdplateaus lt with steep, dissected tdtopography. 12

13 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. 13

14 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. 14

15 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). 15

16 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. 16

17 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. 17

18 Yellow star thistle (Centaurea solstitialis), an invasive exotic, has largely out-competed 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. 18

19 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. 19

20 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. 20

21 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. 21

22 This is a close-up of the Craig Mountain area before and after the Maloney Creek fire. 22

23 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 groundreferenced. 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.. 23

24 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. 24

25 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. 25