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Estimating pedestrian journey time to health facilities using a GIS Click to Continue.

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Presentation on theme: "Estimating pedestrian journey time to health facilities using a GIS Click to Continue."— Presentation transcript:

1 Estimating pedestrian journey time to health facilities using a GIS Click to Continue

2 Consider a simple scenario: Estimating pedestrian journey time to health facilities using a GIS

3 Consider a simple scenario: We have a set of health facilities distributed across a region, represented in a GIS as points on a raster grid. Estimating pedestrian journey time to health facilities using a GIS

4 The first job is to construct an impedance grid. This defines the journey time in minutes required to cross every grid cell on foot. To do this we need input GIS data on things that affect journey time… Estimating pedestrian journey time to health facilities using a GIS

5 We need input data on where the roads and footpaths are. They can be classified into different types e.g. tarmac pavement, unmade track etc. Roads and footpaths

6 Estimating pedestrian journey time to health facilities using a GIS We need input data on any natural barriers such as rivers or lakes. Natural barriers

7 Estimating pedestrian journey time to health facilities using a GIS We need input data on the gradient of the land. This can be calculated within a GIS using data on elevation. Such data is commonly in the form of a digital elevation model (DEM). Elevation

8 Estimating pedestrian journey time to health facilities using a GIS When we have assembled our landscape data, we must assign each grid cell an impedance value. This is a function of the type of landcover (is it road, non-road etc), whether a barrier is present, and the gradient of the land. These factors allow estimation of walking speed, which can be combined with knowledge of the size of each cell to estimate the time taken to cross it. Impedance (red = low green = high blue = barrier)

9 Estimating pedestrian journey time to health facilities using a GIS The final step is to use a shortest-path algorithm in the GIS to determine the fastest route from each grid cell to the nearest facility, and to calculate the time required to make that journey. Such an output is also known as a cost surface. Journey time to facility (minutes) (white = small values dark red = high values)

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