Using GIS to Locate Spiranthes diluvialis: A Report


As the GIS analyst, my job was to prepare a map that will help a botanist locate Spiranthes diluvialis in the Okanagan Valley area. Therefore, I produced a multi-criteria model that highlights potential habitat and helps direct her search efforts.

The goal for this lab was to identify the best 700 hectares of habitat to help guide a botanist to find a rare species of plant called Spiranthes diluvialis.

My analysis used TRIM data for elevation, water and transportation in the study region (Map 1). Using the polygon TRIM data, I created a Triangular Regular Network (TIN). After the TIN was created, it is very simple to put together a Digital Elevation Model (DEM) raster layer to conduct our analysis. The botanist relayed that there are three habitat characteristics that our rare plant prefers: low slope, south facing aspect and medium elevation. After creating the three layers from the DEM, I transformed each using the ‘Fuzzy Membership’ operation which ranks the preferred habitat characteristics between 0 and 1 individually.

Map 1

The botanist relayed that the Aspect is more important to the species than the slope or elevation and that both elevation and slope were equally important. Using this information, I performed an analytical hierarchical approach (AHP) and determined the relative importance to apply to each factor (See Figure 1). This means that in our Multi-Criteria Evaluation (MCE), a South facing aspect will be prioritized.

Figure 1

The MCE overlays each layer and locates the areas where all three characteristics exist in the top ranked class. We can then locate the top 700 hectares based on that ranking system.

While the weighted MCE analysis should potentially provide a prioritized and specific outcome, conducting a sensitivity analysis would prove useful as a comparison and to help validate the findings from the weighted MCE. Therefore, another MCE analysis was conducted with the weights for the three characteristics equal to each other.

For Map 2, the two MCE results were overlayed. The map indicates ‘Ideal’, ‘Great’ and ‘Good’ habitat. The ‘Ideal’ classification covers the area where both analysis overlap and consists of 514 hectares. The ‘Great’ habitat is the result of where only the weighted analysis (favouring Aspect) covers and consists of 203 hectares. The ‘Good’ habitat is the area where only the results of the sensitivity analysis are and consists of 200.5 hectares. In my opinion, it would be best to begin in the ‘Ideal’ classified areas and then work out towards ‘Great’ and ‘Good’ for the search.

Map 2

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