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What is a shapefile?

A shapefile is an Esri vector data storage format for storing the location, shape, and attributes of geographic features. It is stored as a set of related files and contains one feature class. Google Earth, an Online Satellite Imagery (OSI) Technique, is a tool for generating shapefiles.

Question 2: In your project, what geometric analysis tool have you used? How was the experience? Give one example / some examples.

One example:

We used ArcGIS to create a few population maps of To Kwa Wan.

We first selected the population and working population data from the C&SD department. Second, we opened TPUs with the population data in ArcGIS. The area of the TPUs was then calculated based on Hong Kong 1980 Grid, and hence the population densities of those TPUs were determined. Next, these processed data were used to create maps with different population densities and graduated colours were used to represent different densities on the maps. Finally, the maps were exported.

It was convenient to calculate the population densities of the TPUs and useful of ArcGIS to generate maps with different population densities.

Some examples:

We used Google Earth and QGIS to find out the catchment area of recreational areas and main transport spots, as well as the distances from residential buildings to recreation areas and main transport spots.

First, we used Google Earth to make shapefiles of recreational areas, main transport spots and residential buildings in To Kwa Wan. Next, the shapefiles and the TPU file were opened in QGIS. We give different colours and symbols for different shapefiles for easy recognition. We chose 200m as the buffer distance of recreational areas and 100m as the buffer distance of main transport spots. After that, we dissolved and clipped the buffer. The map of catchment areas were exported. We then calculated the size of catchment areas, the number of residential buildings within the catchment areas and the distances from residential buildings to recreation areas and main transport spots. The shortest distances were selected and shown in interval of 100m in bar charts.

It was very tedious and time-consuming to pin the residential buildings as there were about 800 of them. However, seeing the outcome gave us a great sense of accomplishment. Moreover, it was interesting to discover the coverage of the recreational areas and main transport spots by using Google Earth and QGIS.

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