Brian G. Buchanan
GEOG 483: Problem Solving with GIS
Project 7: Introduction to Raster GIS Analysis
California is world famous as a wine-producing region in terms of both production and quality (King 2008). In order to create a top quality wine, certain conditions in the location of the vineyard must be met. Using a GIS can aid the winemaker in picking a suitable location for the planting of grape vines. The conditions that a winemaker looks for before planting a vineyard include: the land is outside of a floodplain and more than 100 meters from a stream, the land is located within agricultural or undeveloped land, the land is situated on a slope between 112 to 337 degrees or on flat land, and the land is located on a landform containing medium to highly drained soils (values of 1.5-3) in soil depths between 31 and 72 inches (King 2008). In addition, certain climatic conditions are needed to produce excellent wine including a maximum wind speed of 25 miles per hour (mph), and an average minimum temperature greater than 35 degrees Fahrenheit (King 2008). The above conditions “represent important environmental characteristics that must be considered when identifying suitable sites for grape cultivation” (King 2008). A GIS can take data on all of the above conditions and create a map that shows the suitable sites for the location of a vineyard within a small portion of Napa County.
The goal of this project was to combine all of the environmental data into one map to graphically show what areas within the study area were suitable for planting a vineyard. All of the data layers, therefore, had to be within the same format. I converted the vector layers I had been supplied with into raster data by using the spatial analyst convert command (landuse, hydro, and floodplain). I then took the elevation raster data I had been supplied with and using the spatial analyst toolbar, I calculated the hill shade. The hill shade represents an illumination of the ground surface, giving the appearance of the topography within the portion of Napa County (Figure 1). Using the spatial analyst toolbar, I then calculated the aspect of the elevation data. Aspect refers to the orientation of the slope. The results of the hill shade and aspect commands are overlain and shown in Figure 2. Together, these two commands graphically show the 3-dimensional appearance that aids in visualization as well as helps to determine the slope of the landforms within the study area.
Figure 1: Hill shade of the elevation raster data of the study area. The hill shade is labeled topography in the table of contents. This map was created using ArcView 9.2 on February 26, 2008.
Figure 2: Map of the study area showing the aspect raster data overlaying the hill shade data. This map was created using ArcView 9.2 on February 26, 2008.
The next step was to interpolate grids from the climate and soils data. Both the soil and climate layers were sets of sample points. A continuous raster layer was created of the soil and climate layers using Inverse Distance Weighted (IDW) interpolation. Using this command created layers that were color ramped raster grids showing the depth of the soils, the minimum temperatures, and the maximum wind speeds throughout the study area. The next step was to create buffers around the hydro layer in order to determine the land within the study area at least 100 meters from water. I used the spatial analyst distance straight line command to create the Dist_hydro grid. This raster grid showed the distance within the study area from the hydro layers (Figure 3).
Figure 3: Map of the study area with the soil drainage, maximum wind, minimum temperatures, soil depth, flood grid, hydro grid, and landuse grid layers overlaying the hill shade layer. This map was produced using Inverse Distance Weighted command that interpolated values based upon the soil and climate sample points. This map was created using ArcView 9.2 on February 24, 2008.
Using spatial analyst, I reclassified the maximum wind, minimum temperature, soil depth, soil drainage, land use, aspect, and the distance to hydro layers into two categories: desirable and undesirable. Reclassifying all of this data created seven new layers that I overlaid on the hill shade grid (Figure 4). Now that all of my data was broken down into desirable and undesirable classifications, I could use the raster calculator to combine multiple grid layers into a single layer that could be made into a layout showing the suitable sites for the location of a vineyard. I combined the floodplain grid and the hydro buffer with the raster calculator to create the Flood_hydro layer. This new layer showed a buffer around the streams, rivers, and floodplains.
Figure 4: Map of the study area showing seven reclassified layers overlaying the hill shade layer. This map was created using ArcView 9.2 on February 24, 2008.
Now that all of my data was broken down into desirable and undesirable classifications, I could use the raster calculator to combine multiple grid layers into a single layer that could be made into a layout showing the suitable sites for the location of a vineyard. Using the raster calculator, I created an expression that multiplied all of the reclassified layers and the Flood_hydro layer to create a suitable sites layer. I displayed this on a layout along with the hydro vector layer, the Flood_hydro grid layer, and the hill shade layer (Figure 5). The available acreage within the study area that was suitable for the location of a vineyard was 1,295 acres.
Figure 5: Layout of the study area showing the suitable sites for a vineyard, the streams and rivers, and the buffer around the floodplains and streams and rivers. The acreage suitable for a vineyard numberd 1,295 acres, with the majority located in the western portion of the study area. This map was created using ArcView 9.2 on February 24, 2008.
After I had completed this layout and determined the available acreage, I was given data on the ownership within the study area. Only portions of the study area that were privately owned could be used as sites for vineyards, because the publicly owned land was not available for purchase. I took the ownership data, and reclassified it according to desirable (private) and undesirable (public). I then used the raster calculator and multiplied all of the reclassified data to create another map of suitable sites. The suitable sites, after factoring in the ownership data, were obviously much smaller. Only 739 acres were now suitable as locations for vineyards within the study area (Figure 6).
Figure 6: Layout of the study area showing the reduced suitable areas for the location of a vineyard after the ownership data was calculated along with the other conditions. The same layout was used as Figure 7 to avoid confusion. The acreage within the study area suitable for a vineyard now numbered 739 acres. This map was created using ArcView 9.2 on February 24, 2008.
The final layout I made was an overlay of the suitable sites for the locations of a vineyard before the ownership data was added and after the ownership data was added (Figure 7).
Figure 7: Layout of the study area showing the suitable sites before and after the ownership data was calculated with the other conditions. This map clearly shows how much land that was suitable for vineyards is located in public land (the area in yellow). This map was created using ArcView 9.2 on February 24, 2008.
I was pleased with how my layouts turned out. I think that they graphically show the areas that were suitable for the location of a vineyard. Higher resolution data could improve the analysis of the study area. For example, better resolution of the elevation grid or floodplain grid could drastically change the results because higher resolution data would change the reclassification and buffers according to the change in dimensions of the floodplain and/or better resolution of the elevation changes across the study area. This project shows that a GIS has applicable business uses for vintners. Using data from a variety of sources and the criteria of a winemaker, a GIS was made that narrowed down the study area into areas that were desirable or undesirable for the location of a vineyard.
Source
King, Beth (2008) Problem Solving with GIS, Lesson 1. The Pennsylvania State University World Campus Certificate Program in GIS. Accessed February 22, 2008.
This document is published in fulfillment of an assignment by a student enrolled in an educational program of The Pennsylvania State