Suitability Analysis

            UCLA has proven to be a top university continuing to attract applicants all around the world. As a matter of fact, it has been known as the most applied-to university in the nation. UCLA operates on a global level, with diversity surrounded by one of the most recognized cities in the world, Los Angeles. UCLA has gained reputation of excellence and prosperity. Most importantly, UCLA makes a difference in the world and students, along with staff members, are a huge part of it. The performance of UCLA in academics, research, and service is dedicated to maintaining the purpose of creativity, perseverance, and achieving great accomplishments and discoveries. If building an extra UCLA campus and naming it UCLA2 sounds exciting, it is even more interesting to learn about what is being done here, now, at UCLA department of Geography, focusing on Geospatial Information Systems (GIS) and Technology. Suitability analysis is conducted to analyze the best possible location for a new UCLA2 campus. Several parameters are being considered including, but not limited to, the influence of slope, urban areas, burglary incidents, and distance from major highways. The new campus is supposed to serve approximately 5,000 additional students and staff. The UC Regents and LA County have put out a Request for Proposals to locate the best place for building a new campus. The only criterion given for the project was that the campus must be built in Los Angeles County. The capabilities of GIS are powerful and technical enough to effectively support the decision to establish a satellite campus, UCLA2.

                The procedure of this exercise is detailed, but at the same time repetitive and simple with sufficient practice and understanding of the material being performed. This analysis involved working with the projection of UTM Zone 11, except for crime data which was projected to State Plane 5 format (California V). Needed data was downloaded from UCLA GIS Mapshare and Los Angeles County GIS Data Portal. Also, a mosaicked DEM from a past lab assignment was needed to generate a slope map. There are a total of four parameters that were converted into a raster (slope is already in raster form) and reclassified accordingly based on suitability. At the end, a final map of suitability was calculated and boxes were drawn to indicate the best possible locations for UCLA2.

                Slope is given the most weight because construction of a new campus on a steep slope is not only dangerous, but impractical. A mosaic DEM from a previous lab assignment was utilized to generate a slope map. Reclassification was necessary to indicate the steepest slope as the lowest number and the most gradual slope as the highest number. A higher number indicates higher suitability for construction. A total of 5 classes with equal intervals were assigned for reclassification. After reclassification, the slope map was clipped with extract by mask tool with the LA County layer. This reclassified raster is now ready for the final calculation of suitability analysis. An important note to consider is that the slope map will determine elevation and this can also affect the dangers associated with earthquake damages. Higher elevation means more earthquake damage. In turn, construction on a lower elevation location is safer and reliable.

                Highways are given the second highest weight because transportation is important in traveling from and to campus both for students and staff. UCLA is actually built right by the 405 freeway and is very convenient especially during heavy traffic hours. Therefore, highways are essential in building UCLA2. The data for highways was obtained from UCLA GIS Mapshare. The data is major highways of Los Angeles County. The shapefile was then buffered with the multiple buffer tool. Buffers of 1 and 3 miles were assigned. The buffers were then converted into a raster and reclassified. Realistically thinking, 1 mile from the highway is too close for any construction so 3 mile buffer was given the most emphasis on suitability. The area beyond the 3 mile buffer was given the second highest suitability score. It is thus important to remember that the “No Data” value for reclassifying should be given a number. This number would be the second highest suitability and is shown with the color blue on the map. Green indicates the most suitable. This reclassified raster is now ready for final calculation.

                Burglary was given the next highest weight because burglary is actually the number 1 committed crime around university campuses. Students are desperate to steal laptops and even cars. Libraries are constantly informative on warning theft and not leaving valuable unattended. A stolen laptop or folder can cause extreme loss of academic achievement and personal possessions. Therefore, burglary is unacceptable under any circumstances and should occur away from campuses where students and staff deserve peace and quiet. Crime data was downloaded from the Los Angeles County GIS Portal. Part 1 was downloaded which includes all crimes committed within the last 30 days, as stated by the FBI. The file was saved as an excel file as filtered for burglary only. The filtered results were then saved again as an excel file (old version). The X and Y columns were separated by Text to Columns in the Data tab and checking the comma delimiter. The X and Y were then added to ArcMap by adding X and Y data. This data had to be projected to State Plane 5 to match the Los Angeles County layer. Zooming into LA County layer makes the points visible. The points were then given multiple dissolved buffers of 1, 2, and 3 miles. The procedure after this was then similar to major highways, but instead the No Data value was given the highest suitability, with descending suitability scores as buffers approach the points. The closest buffer to the crime point is the least suitable and is indicated in purple on the map. The most suitable locations are colored in red. At least 3 miles should be given from theft incidents. Of course, the points were converted to raster before reclassification and are now ready for the final suitability analysis.

                 Urban areas were given the least weight out of all the other factors because it is not absolutely necessary to build UCLA2 on an urban area. Data for urban areas was obtained from UCLA Mapshare. The data was in polygon format. One single 10 mile buffer was created using the buffer tool. The 10 mile dissolved buffers are shown in pink on the map and the rest are areas not close to or near an urban area and are shown as worst locations. Urban areas are emphasized as the best locations. The buffers were converted into raster and reclassified. Again, the No Data value was given a lower number. These areas are nonurban. All the reclassified and masked rasters are now ready for final suitability analysis.

                Results are calculated with raster calculator by adding all the reclassified and masked raster layers. A final suitability layer is created. The symbology color ramp was changed and given the maximum number of classes. Blue indicates the least suitable areas while red indicates the highest suitability. Reasonable locations for the new satellite campus UCLA2 is marked by rectangular boxes in black. One of the most suitable locations is right above UCLA and is underneath the 118 freeways, above the 101 freeways, and east of 405 freeways. This is actually a huge area of consideration and can be utilized to its full potential nearby freeways. Another suitable location is underneath the intersection of the 138 and 14 freeways. It is in Lancaster. The last suitable place for UCLA2 is also nearby major freeways and is located right above Angeles National Forest. 

                Issues associated with this lab assignment were ongoing and complicated. Issues were especially difficult to solve when working with the crime data. Crime point data was big enough to freeze the computer and crash ArcMap. Buffers also took a longer time than expected. Smaller buffers were then created as an alternative route. Reclassifying also took a lot of trial and error. The most important part to remember is to give a value for No Data when making an argument outside the buffers. If a value is not given pre raster calculation, the areas outside the buffers are going to be completely ignored sice it does not interact with other reclassified raster buffers. Therefore, every single space within Los Angeles County boundary must be given a value. Also, if realistically thinking, there are hundreds of parameters that might influence the construction of UCLA2. It is important to note that this is just a proposal of the best possible location of UCLA2. Further research should be done for other parameters that might affect the best suitable location for UCLA2. But overall, this lab assignment ended and completely successfully with time strenuous effort and redoing steps over and over again. In the end, the final suitability was worth the hardships because UCLA2, if built, will not only be safe from burglary, but it will also be conveniently located nearby highways and urban areas. Nevertheless, this UCLA2 campus will be safe from earthquake damage and will have more than enough space to fit 5,000 additional students and staff, even with built in gyms, stores, and sporting fields.