TEACHING GEOG 385.02/GTECH 785.02  GIS APPLICATIONS IN SOCIAL GEOGRAPHY Back to MP home page

### MASTERY EXERCISE 3. DISTANCE AND CONTEXT OPERATORS

 Start: 3/31 Due: 4/14 Data: Please read and follow the instructions in Downloading mastery exercise data on how to create a new project environment file to store your settings for each mastery exercise and to download your data. Turn In: 1. A print out of the map produced in Stage 1 of the exercise. Annotate the map after doing Stage 2 of the exercise. 2. A complete annotated cartographic model (either handwritten or from the macro-modeler of the steps you used (use the conventions discussed on pp. 53-54 and Tutorial exercise 2-2 of Idrisi32 Tutorial) in Stage 1 and Stage 2 of the exercise.

The Exercise:

This is the third mastery exercise and it focuses on the tools for raster analysis covered in class. This mastery exercise is in the form of a single problem that can be solved in two stages. To solve the problem you will have to use distance and context operators as well as tools for database query to complete this exercise. You are encouraged to keep a lab journal where you can record each step you take toward the solution. Also, make use of cartographic models at all stages of your problem solving.

The problem to solve in this exercise is to find areas that are suitable for maple syrup harvesting in the area of Paxton, Massachusetts.

STAGE 1:

Maple syrup is produced from liquids that are "tapped" or drained from maple trees in early spring. The liquid that is harvested flows best while temperatures are above freezing. For this reason, trees on south facing slopes will yield more liquid earlier in the season than trees on north facing slopes. In this problem, south facing slopes are those between 90 and 270 degrees from North (rotating clockwise).

However, transporting the heavy buckets of liquid through forests that are likely to still be covered in snow is difficult. Stands of maple trees that are close to roads are, therefore, more suitable than those far from roads. In this problem, trees within 650m of a road will be considered suitable.

The first part of the problem, then, is to find all locations that are suitable for maple syrup harvesting. These are locations that

·  contain maple trees and

·  are within 650m of a road and

·  are on south facing slopes (90-270 degrees from North).

The method we have used in class and in the exercises is to produce an image for each of the criteria important to solving some problem. In most of the examples we’ve looked at so far, criteria correspond to a single attribute query that results in a Boolean image. In this problem you will perform three single attribute queries resulting in three Boolean images. However, before you can perform the two queries corresponding to the second and third criteria above, you have to first produce the images (database) to query. For example, to create a Boolean image of all locations within 650m of a road you must first produce an image where all cells contain values representing their distance from a road ("roads" are the feature from which distance is measured). Similarly, to find all locations that face south, you will first need an image where each cell contains a value representing the direction of its slope. These steps will involve both distance and context operations.

Once each Boolean image is produced, you should be able to then combine them in the form of a multiple attribute query where the result is an image showing all areas considered suitable for maple syrup harvesting. The data for this stage of the exercise includes the following:

·  PAXLU, a raster image of landuse/landcover in Paxton, MA. Display this image with the PAXLU palette and the legend.

·  PAXDEM, a raster image of elevation in meters for Paxton, MA. Display this image with the Idrisi256 palette.

·  ROADS, a vector file of roads in Paxton, MA. You can display this file as an added layer while viewing PAXLU or you can display it alone. Use the default symbol file for display. Note: to use a vector file for analysis (in a raster based analytical software such as Idrisi) it must first be converted into a raster image. Use the module INITIAL to create a "blank" image with the same parameters as PAXLU and then update that blank image using one of the vector to raster conversion tools in Idrisi (look under REFORMAT in the menu and Help system).

Question 1: Using the information above, the data provided, and the tools for raster analysis covered in class, produce an image showing all locations suitable for maple syrup harvesting. Create a map composition that includes title, legend and meaningful legend captions and your name. Add a textbox that briefly (1-3 sentences) clarifies the content of your map of and print this map composition. Also, produce a complete cartographic model showing how you produced this image.

STAGE 2:

Your result in stage 1 included many locations that are suitable. However, small stands of maple trees (where "stands" are contiguous groups of cells, diagonally connected) do not yield enough liquid to make them economically practical for harvesting. Only relatively large stands of maple trees are suitable. Therefore, we will add a new criteria: only stands (in the result from stage 1) greater than 10 hectares are suitable.

Question 2: What is the total number of maple stands in your image?

Question 3: How many stands of suitable maple trees are greater than 10 hectares in area? Add the steps you took to figure this out to your cartographic model. On your image of suitable areas produced in stage 1, simply circle the stands that are greater than 10 hectares.

Extra credit (1 pt): Print an image showing only suitable stands greater than 10 hectares. Provide a cartographic model showing how you did it. [hint: Explore the other output formats available in the module AREA].