DEMs and Terrain Modeling

            The purpose of this particular lab assignment is to develop an improved understanding of performing terrain analysis on vegetation types relevant to topography. The specific area of interest is the Santa Monica Mountains (SMM). After the detailed procedure of calculating slope, aspect, and solar radiation of the DEM obtained from USGS, a complex calculation of average annual insolation and mean values are calculated, then compared with vegetation types and graphed.

            First, the DEM of a part of SMM is needed to be downloaded through the seamless USGS website. A 30 meter resolution DEM must be downloaded and opened in ArcMap. Before moving on to the next step, the metadata of the DEM must be clipped with the vegetation data provided by the instructor. This clipped metadata identifies the vegetation types within the chosen DEM. It is also important to change the projection for the vegetation layer and DEM to UTM Zone 11N. Now, calculating slope and aspect is easy. Make sure Spatial Analyst is checked under Extensions. Navigate to Spatial Analyst Tools in the ArcToolbox and open slope or aspect under Surface. The input raster should be the projected UTM Zone 11N DEM. Save the output raster to the appropriate drive and click OK. The aspect and slope map should be generated in less than a minute.

            The next step is to calculate the solar angles by using the Hillshade tool. The Hillshade tool is also under Surface. Unlike previous introductory labs, this hillshade calculation requires the azimuth and altitude values for each season. Google Equinox and compute the solar angles from Sustainable by Design website. There should be no daylight saving, elevation is 0, and the time should be set to 12:00 PM. Zero azimuth is South and input the dates according to the Equinox and season. The longitude and latitude is found from the DEM properties from ArcMap. If azimuth is a negative value, just add 360 to the value. Type in the azimuth and altitude values in the hillshade tool with input raster to the projected DEM. Z factor should be left to 0 and run results. Repeat these steps for each season. There should be a total of four hillshade layers.

             The solar radiation algorithm is provided in the last slide of the lecture slides. The equation is I = S * Hillshade/255. The "I" stands for insolation and S equates to 1000. Plug in the hillshade calculated above and compute the insolation for each season using the raster calculator. These four insolation maps should be submitted as part of the final layout. And it is evident that the four insolation maps correspond to the calculations as shown on the layout. Insolation maps provide essential information on the amount of solar radiation each season receives. The season with strongest solar radiation exposure is summer. The darker areas indicate less solar insolation exposure and the lighter areas receive more solar radiation. Of course, the lightest areas receive the most solar radiation. It is indicated in the Legend also the range of solar radiation values from low (dark) to high (pure white).

            In order to show a clearer perspective of the importance of vegetation types related to slope, aspect, and solar radiation, tables or graphs can be generated. For this lab, graphs showing solar radiation regime vs. season, slope mean vs. vegetation type, aspect mean vs. vegetation type, and elevation mean vs. vegetation type was created. It is recommended to pay very close attention to the following steps for calculating mean. The mean values are calculated using the Zonal Statistics as Table tool, located under Zonal in Spatial Analyst tools. For slope and aspect mean values, the input raster should be the clipped metadata and zone field should be changed to WHRNAME (vegetation names). The input value raster should be either slope or aspect depending on what is being calculated. Save into the appropriate drive and change the Statistics type to mean. Repeat these steps for input value rasters spring, summer, fall, and winter insolation. Once the mean table is calculated, open the attribute table for each season and find the sum mean under statistics. The mean sum for each season should be inputted into Excel and saved. Open the Excel spreadsheet by adding it as data. This table is used for creating a graph that shows annual solar radiation mean for each season. Lastly, the mean should also be calculated for elevation. The projected UTM Zone 11N DEM is used to find the mean elevation. The graphs are simply created by opening the tables and clicking on create graph under table options on the top left corner. An issue of exporting the finished map layout as a PDF is that the y-axis titles appear as rotated horizontally. This is fixed by deleting the title from the create graph tool, and manually type the text with the draw tool.

            It is clear that chamise redshank chaparral has the highest elevation and slope mean values compared to the other vegetation types. Coastal scrub is seen to have the second highest elevation and slope mean values. These mean values can be referred back to the slope map. The higher the elevation, the more solar radiation it is possibly receiving. However, this is not always true for slope. When determining how much solar radiation an area is receiving according to the slope map, the aspect has to be considered. The closely surrounding low areas near the high elevations are receiving the least incoming solar radiation because of shadows. Summer is proven to receive the most solar radiation out of all the other seasons, which seems very obvious. This result is evident in the graph as well. The lighter the gray shade in the hillshade maps, the higher the solar radiation. The aspect map refers to the directional measure or compass direction of the slope and indicates that north facing slopes are more likely to be exposed by solar radiation. The aspect mean graph hence indicates that chamise redshank chaparral has the lowest mean aspect value. Therefore, this vegetation type includes the most vegetation facing north. There are no flat surfaces in this DEM. Therefore, in the case of an emergency plane landing, there is no particularly safe place to land. It was interesting to see that the solar radiation mean for spring and autumn were almost identical. Spring was just slightly higher. Winter obviously had the lowest solar radiation exposure. All of these results refer to one day of each season. The spatial variability of insolation changes with day and time of year. Nevertheless, studying solar radiation strongly helps determining the effects of solar radiation on many biological and physical processes.