SPATIAL ANALYSIS OF WINERY CONTAMINATION

Transcription

1 SPATIAL ANALYSIS OF WINERY CONTAMINATION The Spatial Analysis of Winery Contamination project used a previously created MS Access database to create a personal geodatabase within ArcGIS in order to perform a spatial analysis. The database held winery location and attribute information for twelve wineries in Niagara-on-the-Lake. Buffers were performed on the wineries depending on the type of wine they produced, either red, white, or rose. Buffers were also performed on the hydrology in the area and then an overlay analysis determined where the wine buffers and the hydrology buffer intersected. These points of intersection, deemed the contamination zones, show areas within the Niagara region where watershed contamination is very likely to occur from the wineries. It was found that in Niagara-on-the-Lake, there is a heavy contamination of the local hydrology from these twelve surrounding wineries. GISC9301 ArcGIS Applications By; John Bull

2 Table of Contents 1. Introduction Background Data Creation Geodatabase Purpose Datasets Used Goal Methodology Objective # Objective # Objective # Objective # Objective # Objective # Objective # Objective # Objective # Objective # Findings Conclusion Bibliography... 12

3 Table of Figures Figure 1: Metadata for SID imagery showing spatial reference... 3 Figure 2: Results of inverting the colour ramp... 3 Figure 3: Create feature class dialog box showing the selection of columns for XY data... 4 Figure 4: Completed metadata for personal geodatabase... 5 Figure 5: Join data dialog box indicating the join to tblwinery using WineryID... 6 Figure 6: Initial buffer analysis... 8 Figure 7: Results of 1200m hydrology buffer... 9 Figure 8: Result of overlay analysis intersecting hydrology buffer with winery buffer... 10

4 1. Introduction The Spatial Analysis of Winery Contamination project serves to use a previously constructed Microsoft Access database to create a personal geodatabase within ESRI s ArcGIS software. The MS Access database that we will be using contains information on twelve different wineries located within Niagara-on-the-Lake including attributes such as their name, address, location, and what wine types they produce. Out of the twelve wineries we are using, four wineries produce red wine, four produce white wine, and four produce rose wine. For each wine type that a winery is producing there is a different amount of distance that chemicals used in the winemaking process can travel in order to contaminate a waterway. For a white wine producer the distance is 500m, for a red wine producer it is 1600m, and for a rose wine producer it is 2500m. The hydrology used in this project has an area of up to 1200m from the centreline of each stream or river that can potentially be contaminated. Two separate analysis techniques will be performed upon these datasets; a buffer analysis indicating the contamination zones around each winery as well as around each waterway, and an overlay analysis indicating which parts of the wine buffer intersect with parts of the hydrology buffer. This project will provide insight into if there is contamination occurring in the Niagara Region s waterways, and if so, which wineries this contamination is coming from. It will also provide information as to what impacts could occur from these contaminations. 2. Background 2.1. Data Creation The winery data used in this project was manually inputted into a Microsoft Access database via a database management project at Niagara College. The winery information was provided to students by Dr. James Jiang at Niagara College while the location information was gathered from students and inputted into the database. The location data was collected using a Trimble GeoXT GeoExplorer 3000 Series GPS unit. All other GIS data used within the project was obtained from the X: drive at Niagara College via the ArcGIS Applications folder Geodatabase Purpose To perform the array of spatial analyses required to complete this project a geodatabase is much more convenient to create to store the spatial data that you have chosen to use. The creation of a personal geodatabase allows simple importing of data simply by importing them as feature classes and then altering their projections while it also keeps all of your data in one location when performing multiple analyses on datasets such as the multiple buffers we will perform in this project. With the data inside of a personal geodatabase it is also much easier to manipulate like creating joins between two attribute tables or layers. In all, the personal geodatabase is the JB Industries 1

5 common data storage and management framework for ArcGIS offering the ability to store a rich collection of spatial data in a centralized location, apply rules and relationships to the data, and maintain integrity of spatial data with a consistent, accurate database (ESRI, 2005) Datasets Used This project involved using an array of different datasets as opposed to simply ESRI shapefiles. The road datasets, labelled 30M03 and 30M06, were probably created from a topographic map series and were the only ESRI shapefiles that we worked with. These files were however in a different coordinate system so conversions were necessary before they were used. The hydrology dataset was made up of an old ArcInfo Version 7.X coverage file comprised of an arc feature class and a tic feature class. The municipal boundary dataset was in the.dwg file format which is a CAD drawing composed of point, line, and polygon features. All of these file formats were easily imported into the personal geodatabase as feature classes. 3. Goal The Niagara Region, and Niagara-on-the-Lake in particular, is a booming area for the wine industry with many wine producing farms clustered together over a relatively small area. With this many wineries the potential for the contamination of local waterways is greatly increased due to the amount of chemical additives used in the winemaking process. The major goal of the Spatial Analysis of Winery Contaminants project is to identify if there is possible contamination of local hydrology from the wineries nearby and if so what is the impact of this contamination. 4. Methodology 4.1. Objective #1 Objective one involved using DOI raster imagery in order to create a base map for the project. This task was fairly simple as the raster imagery was already spatially referenced to NAD 83 UTM Zone 17N as we can see in Figure 1. JB Industries 2

6 Figure 1: Metadata for SID imagery showing spatial reference Considering the raster image already has an appropriate spatial reference we can simply drag the file from the catalog onto our map surface. At this time it was chosen to invert the colour ramp used in the symbology of the raster imagery in order to switch the colour from outside the image to white from black (Figure 2) for aesthetic purposes. Figure 2: Results of inverting the colour ramp JB Industries 3

7 4.2. Objective #2 Objective two involved bringing in our previously created Microsoft Access database into ArcMap to create our new personal geodatabase. This task was performed by navigating to our MS Access database within the Catalog of ArcMap and creating a feature class from tblwinerylocation. The winery location table includes previously obtained geographic coordinates for twelve different wineries in which we can use as latitude and longitude data in creating our new feature class. We can see below in Figure 3 the dialog box showing the creation of the feature class using the easting Figure 3: Create feature class dialog box showing the selection of columns for XY data and northing columns within our table. After specifying the output of the feature class to fall within our newly created geodatabase, we now have a point feature class to represent the twelve different wineries on our map. JB Industries 4

8 4.3. Objective #3 Objective three was simply to create metadata for our newly created geodatabase. The best way to go about doing this is to open ArcCatalog and navigate to the geodatabase. Once selected, the metadata is shown under the Description tab and can be edited simply by pressing the Edit button. Once in the editor mode, a photo was added as well as information such as a title, summary, description, tags, and credits (Figure 4). Figure 4: Completed metadata for personal geodatabase JB Industries 5

9 4.4. Objective #4 Objective four involved creating joins between two tables in order to perform the spatial analysis in the future. The winery location table contained geographic coordinates but did not include any information describing the wineries themselves, this information is held in the winery table. Creating a join between these two tables will allow us to buffer select wineries depending on which wine type they produce. In order to do this we first need to project our point data onto the map surface using the Project tool in the Data Management section of the ArcToolbox. After filling out our input and output locations and specifying that we would like the wineries to be projected in NAD 83 UTM Zone 17N, our wineries are now projected as a layer on the map. With the data now projected as a layer we can use the join data function to join attributes from a separate table. The wine location data was joined with the winery information data in the winery table using the common field WineryID (Figure 5). Figure 5: Join data dialog box indicating the join to tblwinery using WineryID 4.5. Objective #5 The next step in the project is to bring in the road network datasets. Some conversion was necessary for these files as they were originally spatially referenced in NAD 27. This was done by assigning and then projecting-on-the-fly the road shapefiles into NAD 83; during the project phase we can also convert the shapefile to a feature class and import it into our personal geodatabase. Once properly projected the road network lined up with our underlying SID imagery as can be seen JB Industries 6

10 in the map in Appendix A Objective #6 Objective six simply involves bringing in the municipal boundaries data into the geodatabase and project them onto the map. This dataset is in the.dwg file format which represents a CAD drawing and therefore it also needs to be projected into the NAD 83 coordinate system. Following similar procedures to objective five the municipal boundaries were added to the map that can be seen in Appendix A Objective #7 Objective seven once again involved bringing in data to our personal geodatabase that is of a different file format. This particular file was the hydrology for the Niagara Region and it was in the ArcInfo Version 7.X coverage file format. In order to complete this task the arc coverage file was imported into my personal geodatabase and then I simply projected it to NAD 83. The projected hydrology can be seen on the map located in Appendix A Objective #8 Once the geodatabase had been populated with correctly projected feature classes we were able to being our spatial analysis. The first step in this process was to complete a buffering of each winery depending on which type of wine they produced. Out of the twelve wineries there were an equal number producing each type of wine and the buffer zones were set at 500m, 1600m, and 2500m, for white, red, and rose wines respectively. The wineries were split into three separate feature classes and were buffered accordingly giving us the map we see in Appendix B Objective #9 The next step in the spatial analysis is to buffer the hydrology layer so that we can find the intersection of these buffers. It was provided to us that the streams in this area can be impacted by contaminants from up to 1200m away so that is the distance that we used for our buffer. We once again used the buffer tool and received the result we see in Appendix C Objective #10 Objective ten was the final step in completing the GIS portion of the project as it involved completing the intersection analysis. Before beginning the intersection analysis the three different winery buffers were combined together using the union tool, dissolving any boundaries they had. The intersect tool was then used to find the intersecting areas of the hydrology buffer and the winery buffers. This intersection analysis results can be seen on the map in Appendix D. JB Industries 7

11 5. Findings The initial analysis performed was simply a buffer analysis of each winery depending on the type of wine they produced; 500m for white wine, 1600m for red wine, and 2500m for rose wine. This initial buffer analysis provided us with the image that we see below in Figure 6. Figure 6: Initial buffer analysis We can immediately see from this image how much larger an impact the rose wine producing wineries will have on contaminants than the other wine type producers. The total amount of area affected by the initial buffers is approximately 75km 2 which is a massive portion of the northeastern Niagara peninsula. We can also see in Figure 6 the large amount of streams that fall within these buffer zones, particularly ones along the south shores of Lake Ontario. The second analysis performed was a buffering of the hydrology in the Niagara Region. All streams within this analysis could be affected from contaminants up to 1200m away so therefore we buffered 1200m from the middle of each stream. Figure 7 below shows the results of the hydrology buffer. We can see from this image that a 1200m buffer on all of the hydrology within the Niagara Region creates a buffer zone that covers a very large portion of the Niagara peninsula. The large amount of streams, rivers, and other assorted waterways, especially west of St. Catharines, are almost certainly going to be contaminated by any chemical or waste leakage. Within Niagara-on-the-Lake however there are small areas where the hydrology buffers do not cover and essentially these areas would be areas where leaks could occur and they would not make it into the water cycle. JB Industries 8

12 Figure 7: Results of 1200m hydrology buffer Aside from two white wine producers, every other winery lies within a hydrology buffer zone which already indicates that if any leakage occurs at these sites, even if it does not travel, it will contaminate the local hydrology. The third and final analysis that was performed was an overlay analysis using the intersect tool in the ArcToolbox. This tool creates a geometric intersection of two or more layers and outputs the result as a new feature class within the geodatabase. Using our hydrology buffer combined with our winery buffers we were able to find the areas where these two buffer zones intersected. The results from the overlay analysis are present in Figure 8 below. JB Industries 9

13 The image in Figure 8 shows multiple red polygons that represent areas where the hydrology buffer and the winery buffers overlapped. Any location within one of these red polygons indicates an area that if a chemical was dumped via winemaking that this chemical would contaminate one of the local waterways. Therefore any winery that falls within these red polygons is essentially Figure 8: Result of overlay analysis intersecting hydrology buffer with winery buffer contaminating the local waterways. Out of our twelve wineries, ten fall into areas covered by red polygons indicating that they are contaminating the local hydrology. The two wineries that ended up not being water contaminators are this way due to a couple reasons. Firstly, the only two wineries that do not fall into one of the contamination zones are white wine producing wineries. The white wine producers had a considerable smaller buffer zone applied to them compared to red wine and rose wine producers because the contaminants used in the white wine production travel a much shorter distance and therefore it is much more likely that a white wine buffer would not JB Industries 10

14 intersect with a hydrology buffer compared to the other two types of wine. For example there is one other winery in the same general location as these two wineries but it falls within the red contamination zone because it is a rose winery as opposed to a white winery. Secondly, and quite obviously, these are the only two wineries that are not situated directly in the middle of a large cluster network of streams and rivers. The fact that these two wineries are so far from any hydrology is the reason that they are the only two wineries who do not contaminate the local water system. 6. Conclusion The overlay analysis performed in this project provided ample information as to how the local wineries in the Niagara Region are affecting the hydrology. With ten of the twelve wineries mapped falling into the contamination zones we can definitively say that there is heavy contamination of the hydrology within Niagara-on-the-Lake, particularly along the south shore of Lake Ontario. One of the main reasons for this is the rose wineries whom have contaminants that can travel up to 2.5km from where they were produced. The rose wineries accounted for approximately 64km 2 of the initial 75km 2 covered by the buffer of all the wineries so without the rose wineries the contamination zone would have been considerably smaller. Another factor in the large amount of contamination is the amount of streams and rivers in the Niagara Region and in particular within Niagara-on-the-Lake. None of the streams or rivers along the south shore of Lake Ontario were more than 1200m apart creating a buffer zone wall that would have intersected with any winery located in that region, even if the winery buffer was only 50m. With so much hydrology in the area combined with the amount that these wine contaminants can travel, it is very difficult to not be contaminating the hydrology within this area. In all, depending on the strength and effect of the chemicals that enter the water system, waterways in the northern Niagara peninsula could be greatly contaminated. All streams that fall into the contamination zones flow either into Lake Ontario or the Niagara River which also flows into Lake Ontario. If the chemicals used were highly toxic or if a large quantity were being dumped then all of Lake Ontario could potentially become contaminated affecting a much larger area than just the Niagara Region. Locally the contaminants could also have an effect; any residence that is using the local ground water as a water supply in and around the Niagara-on-the-Lake region will probably have to invest in water filters or a whole new water system to avoid the contaminated water. The most worrisome would be the southernmost red winery which falls directly into a set of streams; as these streams flow north and into Lake Ontario they will be bringing all of their contaminants with them thus making the water of that stream unhealthy or unusable for a long distance. Overall the contamination discovered in the Winery Spatial Analysis could prove to be detrimental to local water supplies, nature and wildlife both in the streams and along the riverbanks/wetland areas, and potentially much larger watersheds such as Lake Ontario. JB Industries 11

15 7. Bibliography ESRI. (2005, July 15). Geodatabase - Overview. Retrieved December 8th, 2013, from ESRI Products ArcGIS: JB Industries 12