Methods
We
originally planed on performing a multi-criteria evaluation (MCE), but
then found out that most of our criteria were boolean, meaning that
values could either be 'good' or 'bad' but nothing in between. All
the conditions of suitable elevation, slope, aspect and land
cover and unprotected must be met before an area can be included
in the decision set. For example, no matter how good the slope, the
aspect or the elevation may be, it is impossible to build photovoltaic
cells on permanent ice (a land cover value). Therefore, we treated our
criteria as boolean constraints and not fuzzy, weighted factors typical
of a MCE. In effect, we performed a sieve-mapping analysis where the
different constraints were added one by one to remove unsuitable areas.
First, we gathered the data:
· The political boundary of Tibet
· a DEM of the area
· Land Cover data for the area
· Road and populated places in Tibet
See the Data section for information on where we obtained the data.
A global map data set was imported to Arcmap. Using this, a map of Tibet could be isolated. This required deselecting all unnecessary data in the global map data set. Next a definition query was done. (The steps were as follows: right click state-province areas under admin layer. Go to properties the Definition Query tab and click on Query Builder. In Query Builder click "ADMIN_NAME"='Xizang' (natuve name for Tibet) then OK and Apply.) The result is only only the shape of Tibet is identified and displayed. Using this, the Clip tool could be employed to extract data for Tibet only.
We then deselected the data outside of the Tibet border, our project’s study area. We used the Clip tool in ArcMap to get rid of unnecessary data outside of Tibet for all of our datasets. First we worked with the DEM (click on DEM to view the map). Because solar panels function more efficiently at higher elevations, we were only interested in siting the panels above 5000 meters. We used the Definition Query tool (‘Value’ > 5000) for the DEM. This left us with a DEM for Tibet with elevations only above 5000 meters.
From this DEM of Tibet’s elevation above 5000 meters, we created an aspect layer. The aspect map included a ‘Flat’ classification. We wanted to only look at pixels with an aspect of 112.5 to 247.5 degrees. Next we wanted to select for suitable slope. Solar plants should not be built on slopes greater than 5%. However, due to dataset limitations ArcMap was not able to calculate slope for the DEM. So we decided to only consider flat areas. To account for this in our multi criteria analysis, we reclassified the output from the aspect map as: ‘Flat’ = 1, all other values = 0. Then, to select and visualize only the flat areas, we used Definition Query for the reclassified aspect layer: ‘Value’ = 1.
This produced a map for the flat areas in Tibet above 5000 meters.
A land cover map displaying only land we deemed suitable for building on was created. Once a global data set for land cover was imported into Arcmap, the data for Tibet only could be isolated and extracted using the same method mentioned above. Once this was done the reclassify tool was used to create a map that only showed four land cover types (Bare areas, Sparse vegetation, Grassland and Shrubland). During reclassify all other landcover types were give a value of 'NODATA'. The resulting map was one showing the four land cover types (which covered a significant area of Tibet).
A map displaying protected areas of Tibet was also created. A polygon map displaying protected area of China was imported to Arcmap. The protected areas for Tibet only were then extracted using the same method outlined earlier.
After the land cover and protected areas layers had been produced as explained above, we used raster calculator to multiply the following raster layers: flat areas above 5000 metres, suitable land cover above 5000 m, and protected areas in Tibet. The rasters had been reclassified so that after multiplication, pixels with a value of one or greater symbolized areas in Tibet suitable for solar panels. All other pixels symbolized areas not suitable for solar panels. See the flow chart, the final map, and the results section for further explanation and discussion.
First, we gathered the data:
· The political boundary of Tibet
· a DEM of the area
· Land Cover data for the area
· Road and populated places in Tibet
See the Data section for information on where we obtained the data.
A global map data set was imported to Arcmap. Using this, a map of Tibet could be isolated. This required deselecting all unnecessary data in the global map data set. Next a definition query was done. (The steps were as follows: right click state-province areas under admin layer. Go to properties the Definition Query tab and click on Query Builder. In Query Builder click "ADMIN_NAME"='Xizang' (natuve name for Tibet) then OK and Apply.) The result is only only the shape of Tibet is identified and displayed. Using this, the Clip tool could be employed to extract data for Tibet only.
We then deselected the data outside of the Tibet border, our project’s study area. We used the Clip tool in ArcMap to get rid of unnecessary data outside of Tibet for all of our datasets. First we worked with the DEM (click on DEM to view the map). Because solar panels function more efficiently at higher elevations, we were only interested in siting the panels above 5000 meters. We used the Definition Query tool (‘Value’ > 5000) for the DEM. This left us with a DEM for Tibet with elevations only above 5000 meters.
From this DEM of Tibet’s elevation above 5000 meters, we created an aspect layer. The aspect map included a ‘Flat’ classification. We wanted to only look at pixels with an aspect of 112.5 to 247.5 degrees. Next we wanted to select for suitable slope. Solar plants should not be built on slopes greater than 5%. However, due to dataset limitations ArcMap was not able to calculate slope for the DEM. So we decided to only consider flat areas. To account for this in our multi criteria analysis, we reclassified the output from the aspect map as: ‘Flat’ = 1, all other values = 0. Then, to select and visualize only the flat areas, we used Definition Query for the reclassified aspect layer: ‘Value’ = 1.
This produced a map for the flat areas in Tibet above 5000 meters.
A land cover map displaying only land we deemed suitable for building on was created. Once a global data set for land cover was imported into Arcmap, the data for Tibet only could be isolated and extracted using the same method mentioned above. Once this was done the reclassify tool was used to create a map that only showed four land cover types (Bare areas, Sparse vegetation, Grassland and Shrubland). During reclassify all other landcover types were give a value of 'NODATA'. The resulting map was one showing the four land cover types (which covered a significant area of Tibet).
A map displaying protected areas of Tibet was also created. A polygon map displaying protected area of China was imported to Arcmap. The protected areas for Tibet only were then extracted using the same method outlined earlier.
After the land cover and protected areas layers had been produced as explained above, we used raster calculator to multiply the following raster layers: flat areas above 5000 metres, suitable land cover above 5000 m, and protected areas in Tibet. The rasters had been reclassified so that after multiplication, pixels with a value of one or greater symbolized areas in Tibet suitable for solar panels. All other pixels symbolized areas not suitable for solar panels. See the flow chart, the final map, and the results section for further explanation and discussion.
Continue to Results.