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
Table of Contents
1.
Introduction .......................................................................................................................................... 1
2.
Background ........................................................................................................................................... 1
2.1.
Data Creation ................................................................................................................................ 1
2.2.
Geodatabase Purpose ................................................................................................................... 1
2.3.
Datasets Used ............................................................................................................................... 2
3.
Goal ....................................................................................................................................................... 2
4.
Methodology......................................................................................................................................... 2
4.1.
Objective #1 .................................................................................................................................. 2
4.2.
Objective #2 .................................................................................................................................. 4
4.3.
Objective #3 .................................................................................................................................. 5
4.4.
Objective #4 .................................................................................................................................. 6
4.5.
Objective #5 .................................................................................................................................. 6
4.6.
Objective #6 .................................................................................................................................. 7
4.7.
Objective #7 .................................................................................................................................. 7
4.8.
Objective #8 .................................................................................................................................. 7
4.9.
Objective #9 .................................................................................................................................. 7
4.10.
Objective #10 ............................................................................................................................ 7
5.
Findings ................................................................................................................................................. 8
6.
Conclusion ........................................................................................................................................... 11
7.
Bibliography ........................................................................................................................................ 12
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
Spatial Analysis of Winery Contamination
December 12, 2013
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.
2.2.
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
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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).
2.3.
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.
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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
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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.
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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
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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
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in the map in Appendix A.
4.6.
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.
4.7.
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.
4.8.
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.
4.9.
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.
4.10. 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.
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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 75km2 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.
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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.
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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
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a much shorter distance and therefore it is much more likely that a white wine buffer would not
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 64km2 of the initial 75km2 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.
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7. Bibliography
ESRI. (2005, July 15). Geodatabase - Overview. Retrieved December 8th, 2013, from ESRI Products
ArcGIS: http://www.esri.com/software/arcgis/geodatabase
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