Month: December 2015

 

Our final project is aim to give a realizable estimate of the amount of land within the Central Coast district, which is reserved for agriculture.  The Agriculture Land Reserve (ALR) was established by BC provincial government in 1973. It is a policy to make more contribution to protects the agriculture land to strengthen provincial food security. However, in recent years, the ALR was threated by the increasing urbanization and lad development.  In order to analysis the efficacy of the ALR we need know how much of ALR is being used for agriculture. To do this, we used the GIS software to analyze different data to evaluate the ALR in central coast in both biogeographically and social aspect, specifically, we target on the forest cover, soil types, parks, roads, water features and so on. So as to accomplish the project, our teammates followed the proposal, we did the map through regular lab time and organized the report through google doc. Jerry is mainly responsible for the map-making, Tina and I was helped with download the data, and Ziyu is assist Jerry with map and along with record the necessary data. And finally, we finish the report together, and Tina—as the main editor, she went through each part and generalized the report.

As for my personal contribution to the group, I found this project is not only useful, but also helped me develop some GIS skills, especially how to find the data—some of the data is provide freely by the BC government. I can easily access the Terrain Resource Information Management (TRIM) data, download what Jerry need, by buffering all the lakes and rivers, Jerry conducted a map of water features in the central coast area. (MAP 3) I was also used the Digital Elevation Management data (DEM), to reclassify and determine how much of the ALR is over 30 degree, which is not suitable for agriculture land. Thanks to Jerry’s technology skill, he perfectly performs the data by using the ArcMap software.

The use of land in one region should be very diverse, especially for places with urban development. In Central Coast region, we were expected to evaluate the different types of land use, however, it was very challenging to accomplish this task with detailed analysis. We searched data from DataBC, CHASS and Geofabric but the only land use types we got was building, commercial, roads and parks, (map 6 &7) which were the very basic ones. Broad research about the use of land in the following categories: factory, industry, school, hospital, community centers, recreational centers, shopping malls, clinic etc. could not be conducted due to the limited data provided. Although this region has very small population compared to other districts in British Columbia, it does mean that this region is not an important piece of land in BC. It can be developed in to a center of economic and recreational activities in the future. The government should provide data about detailed land use, so that scholars are able to study the geography of this area, and companies can get to know the region for future investment.

 

 

Accomplish Statement

• Effective team-working skills by conducting a team report with specific agricultural land reserve area in Central Coast, in order to see how much of the area could still currently be used for agriculture, and the implications and reasons for our findings.

Lab4

Manipulated visual outcomes of maps by using various breaks to show ethical implications of using different data classification methods in maps.and also gained knowledge in downloading and importing spatial and tabular data to analyze housing affordability in Vancouver and Montreal

Lab5

Found and retrieved data from reliable sources online to conduct an environmental impact analysis within a proposed ski hill area to determine the severity of impact the project would have on the area. and effectively performed data visualization: acquired, parsed, filtered, represented, and refined spatial data to assess the environmental impact of a proposed ski resort.

Housing Affordability— Vancouver and Montreal         affordabilityVM

Click the link to access the map

This map clear shows the housing affordability in Vancouver and Montreal, by comparing the median income to housing cost and family earnings in a certain census tract.  This is a more effective way of accessing housing affordability, than just rely on housing cost, because the families who earn more highly possible live in more expensive house. According to the 11^th Annual Demographia International Housing Affordability Survey, it categorized the following affordability: Severely Unaffordable 5.1 & Over, Seriously Unaffordable 4.1 to 5.0, Moderately Unaffordable 3.1 to 4.0, Affordable 3.0 & Under. The rating is aim to monitor the affordability of the two cities and to alert the government have to control the cost through the Macroeconomic regulation. It is obvious that the map indicate Montreal is much more affordable when taking median house cost and familial earning into account. After all, most census tracts in Vancouver are shown in this map as severely unaffordable.

 

classification method

Click the link above to see the map

This map shows the data for housing coast in Vancouver in different classification method – Equal Interval, Natural Breaks, Manual Breaks and Standard Deviation. The data shows differently with different method of classification. The equal interval classification method is by creating breaks to divided the range into equal sized classes, including the outliers and the extreme values of the dataset, which doesn’t consider the distance between the data points. The drawbacks of this method is when the outlier are too large or too small from the majority, then a majority of points that are observed within a close distance. In the map of Vancouver, we can see that the equal interval method skews the data so that it appears that the majority of the houses are affordable because there are some outliers at the very expensive end of housing costs. The standard deviation method classifies the data by the standard deviation from the mean. The disadvantage of this method are that readers will hard to understand the map, might cause confusion the the purpose of the map nor its legend. The second map is using the natural breaks, this method takes into account the distance between data points and places the breaks in relation to that distance. However, in terms of the legend, since the numbers are automatically calculated by the computer, it will not always be rounded. Finally, the manual breaks method allows the users to “customized” their own breaks. It is significant for the users to considering all of the ethical implications of the display of data, and to choose the most suitable method to classify the data.