## GEOG5222 Lesson 7

### John Taber

Figure 1: This is a manipulation of the initial data available for the task at hand, finding suitable areas vineyards in a part of Napa County, California. Elevation is shown in the background, with the overlaying colors showing areas known to be unsuitable: gray is urban development, green forest, and blue floodplain. In addition, light blue lines indicate streams, and white shows stations for which climate data is available.

The next steps involve converting this vector data to raster data. Using a common frame of reference (10-meter squares) new grid files showing elevation (and from it, hillshading), land use, distance from water, floodplain, and soil and weather characteristics were created. These were then reclassified to directly show acceptable and unacceptable locations.
Figure 2: This shows three reclassified grids. Red represents unacceptable slope aspect (toward north and east); green, an average maximum wind speed greater than twenty-five miles per hour; and blue, average minimum temperature less than thirty-five degrees Fahrenheit.

Figure 3: This shows, overlain (and there is significant overlap between them), the grids for the floodplain buffer (blue) and the stream buffer (green), and the reclassified grids for soil depth (orange meaning less than thirty inches) and soil drainage (purple being a "Low" classification as opposed to "Medium" or "High".) There was a grid showing acceptable or unacceptable land use.

Figure 4:This, then, is the completed product. Green areas are those that are acceptable for vineyards. This was derived by multiplying the values in the reclassified grids - if any one of them had a zero in a particular cell, that cell would have a zero in the final grid and would not be considered suitable. Note also that elevation in this image reflects hillshading.

While this might be a sufficient study for a general overview of suitable land, higher resolution for elevation (the slope seems to be exclusively where countour lines were on the original map, and this affects the final suitability data) and more climate stations would produce a much more accurate result.

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