This week, raster data was provided from USDA Geospatial Gateway. Data was published by US Dept of Agriculture, Natural Resources Conservation Service, National Geospatial Management Center 09-2012. Data was originally created by The PRISM Group at Oregon State University.
I implemented continuous tone by accessing the symbology in the layer properties, selected "precipitation" color ramp. The legend required more work. Choosing a horizontal style, creating an alternate legend with inverted colors, converting the alternate legend to a graphic, ungrouping and moving the labels.
I utilized the spatial analyst extension (after I remembered to active the toolbar). I used the Int Spatial Analyst Tool to convert the raster values from floating (fractional numbers that have decimal places) to integers, to allow crisp contours.
I implemented hypsometric symbology in the layer properties by opting classified with 10 classes with manual break values (per lab instructions). Adjusting the manual breaks to whole numbers. I again chose "precipitation" color ramp, and utilized hillshade relief.
I added contours to the hypsometric tint by utilizing the analyst toolbar this time utilizing the contour list tool. I included required map elements, followed cartographic design principles. I added description of the data to the map (after I remember the draw toolbar and the text in shape).
The fundamental problem in isarithmic map is that data must be interpolated to cover the unknown values between control points, or data collection points. Methods of interpolation the text discussed for true point data were triangulation, Inverse distance, and Kriging, Basic (very basic) explanations of each:
- Triangulation: connects neighboring control points to form triangles, utilizes Delaunay triangles similar to Thiessen polygons forms triangles with all points contained in the triangle are closer to that triangles control point than any other. Once triangles are formed contour lines are created by interpolating along the edges of triangles. Finally the contour lines are smoothed.
- Inverse Distance (gridding): layes a grid on top of the control points, estimates values at each grid node, contour points are weighted as inverse function of the distance from grid points. Consideration is distance only between grid point and control points. Strategies including search radius for grid points for minimum number of points to fall within radius, and maximum number of whole, quadrants or octants of radius without data are set. Interpolated contour lines are placed and finally smoothed.
- Kriging (ordinary kriging): used for data without trend or drift. Similar to inverse distance uses weighted average to compute a value at a grid point. Unlike inverse distance, consideration is not only the distance from control points to grid points, but also the distances between the control points themselves. More complex method of interpolation, it can produce more accurate map (optimal interpolation). ONLY if one has property specified the semivariograms and associated semivariogram models. This model also provides a measure of the error associated with estimate, standard error of the estimate, can be established with a confidence interval.
Symbolization of Isarithmic maps:
- contour lines - lines that mark amounts of a phenomena, can be difficult to visualize
- hypsometric tints - light and dark shades (grey or color) are added between the contour lines to enhance visualization
- continuous-tone - unclassed so color or gray fades and darkens across the entire area to depict different values, can be difficult to get specific data as there are no clear boundaries
- fishnet- gives the effect of a fishnet being draped over the results, can cause blocked information of lower values from higher values.
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