/n HOPKINS TRANSIT STATION ANALYSIS GEOG 502 INTRODUCTION For this project, we use Hopkins transit station analysis data. For this transit station analysis, the study area is Hopkins. Hopkins is a suburban city in Hennepin County, Minnesota, United States, located west of Minneapolis (Figure 1). The city is four square miles in size and is surrounded by the larger, west suburban communities of Minnetonka, Saint Louis Park, and Edina. Hopkins is about 98% developed with little remaining vacant land. The objective of the project is to demonstrate our understanding in GIS and our ability to solve real world problems using our geospatial data management and analysis skills. Expected outputs are outlined for guiding the analysis processes. These guidelines are by no means limit your analysis. Please use your creativity to get any outputs from your analysis. Winnipeg BRUNSWI Quebec City Montreal MAINE Ottawa VERMONT MINNESO Toronto NEW HAMPSHIRE MASSACHUSETTS Minneapolis wisCONSIN NEW YORK RI MICHIGAN CT New York ° Chicago PENNSYLVAN IOWA ASKA OHIO ILLINOIS INDIANA Indianapolis Washington tes Kansas City KANSAS MISSOURI VIRGINIA KENTUCKY Nashville TENNESSEE NORTH CAROLINA Charlotte innetonka SOUTH CAROLINA OKLAHOMA Atlanta ARKANSAS MISSISSIPPI ALABAMA GEORGIA Dallas TEXAS Austin San Antonio Jacksonville Orlando LOUISIANA ° Houston New Orleans St Louis Park 100 Hopkins 169 FLORIDA 494 Miami The Bahamas 62 Edina LEON Figure 1: Study area location map. The following instructions are produced to give you some of the scenarios how the expected outputs are produced. You can use your own creativity to produce the expected outputs. Feel free to change the scenarios in producing the expected outputs. PART I: PRODUCE STANDARD LAYOUT MAP 1. Create a workspace for this project, and copy all the data into a directory. 2. Create a base map using Arc Pro or ArcMap. 3. Load the proposed station location (station), a 0.7 mile radius circle (station_buffer1), and parcels (parcels_shady_oaks), into a data view. 4. Create and print a properly titled map, north arrow, scale bar, grid, your name and simple description in place of a formal legend. Save the map composition (..aprx or .mxd file) for later work (see course project_video_1). Page 1 of 7 GEOG 502 PART II – PROJECTIONS, HILLSHADE, EDITING ArcToolbox 1. Add the Focus_Zone shapefile, dem_shadyoaks1, NE, NW, SE, and SW to the project created in Part 1. Examine the properties for each data set, particularly the map projection of each data set (right click the data name in the table of contents, then properties-source). Some data layers are not in our preferred projection, UTM, NAD83 zone 15 meters. Project all offending data layers into our preferred UTM. Make sure the data frame coordinate system is also set to UTM, NAD83 zone 15 meters. From now on, any reference to data layers is to these new, projected layers. 2. Create a hillshade layer from the DEM, and save it as an output grid (ArcToolbox-Spatial Analyst-Surface-Hillshade, specify an output data file – see the graphic on right/below, see course - project_video_2). 3. Now create a “buildings” data layers. Use ArcCatalog to create an empty polygon data layer, in the UTM zone coordinate system you are using. Display the NE, NW, SE, and SW, 1-foot resolution images. Using the images as a guide, digitize all the buildings within the "Focus_Zone” area. If you wish, you may choose a different area, of approximately the same size, and digitize all the buildings within the area (see course project_video_3). Save the data to a new data layer, named something like "buildings." 4. TurnIn: print a properly composed map that shows the hillshade, parcels, buildings, and station location. Place the hillshade on the bottom, the station and buildings on top, and make the parcels transparent (no color or hollow) to make the hillshading visible. Symbolize the parcel lines, buildings, and station so they stand out. Server Tools Spatial Analyst Tools Conditional Density Distance Extraction Generalization Groundwater Hydrology Interpolation Local Map Algebra Math Multivariate Neighborhood Overlay Raster Creation Reclass Solar Radiation Surface Aspect Contour Contour List Contour with Barriers Curvature Cut Fill Hillshade Observer Points PART III: CONTRIBUTING WATERSHED AND IMPERVIOUS SURFACE Rainfall runoff, accumulation, and management is important. We want to identify areas with high flow accumulation so that we may avoid flooding within the focus area, and not contribute to problems below the focus area. Here, we wish to identify areas with high impervious surface that Page 2 of 7 GEOG 502 drain into the focus area, and areas with high impervious surface that are within the focus area. We will prioritize mitigation for those areas with higher than 35% impervious surface. You may ask why 35% threshold for impervious areas? This is experts' recommendation for managing impervious areas and accept as it is recommended by the experts. Calculate likely runoff flowpaths (in the ArcToolbox, use the Spatial Analyst Tools, then under Hydrology, choose Fill - Flow direction - Flow accumulation, see course project_video_4). Display and symbolize flow accumulation to show watercourses draining the area. Note that flow accumulation values are recorded as cells, so you'll need to calculate the number of cells for that given area to identify the watercourse. You can find the cell dimension by right clicking on the TOC (Table of Content in ArcMap) entry for the flow accumulation layer, then properties – source, and remember the data are stored in UTM meters. The cell dimension is given, so you can calculate the number of square meters per cell, and then the number of cells per hectare, given that there are 10,000 square meters per hectare. Set the threshold in your symbology at this number of cells, white above, black below, to identify watercourses (see course project_video_4). Where is the discharge point? To get the discharge point, please create the river network and show where the water is leaving the focus area (see course project_video_5). Create a "discharge point" at the watershed outlet where it leaves the focus area layer, and calculate the corresponding watershed (you should have an area that appears similar to the graphic to the above - note the discharge point is a small green dot at the bottom of the focus area, and the station location the yellow dot. There may be a difference between this map and your new map. This difference is expected and you can continue to produce your own outputs from the analysis. Discharge location Now we would like to identify areas that have greater than 35% impervious cover within both the focus area and the contributing watershed. You should end up something like the feature below (see also the course project_video_6). Page 3 of 7 GEOG 502 Discharge location Discharge location First, load the impervious surface layer. Reclassify the layer (see course project_video_6,) Spatial Analyst-Reclassify) to categorize those areas above 35% to a value of 1, and below 35% as 0. Note that the yellow dot is the proposed train station within the watershed. Create and export a layout that shows the areas greater than 35% impervious surface. Set the symbol for 35% to red. Set the transparency to 50% (Properties – Display tab, then fill the transparency box with a 50% value). Display these over the images, for a layout pane that looks similar to the above figure at the right side, and add a legend, North arrow, scalebar, and title, as usual. Again, your output may be different from the above figure. This is acceptable and expected. TurnIn: Now turn the maps you produced for watershed management. Page 4 of 7 GEOG 502 PART IV - HIGH DENSITY POPULATION SERVICE AREAS, EXISTING AND TO DEVELOP Your remaining tasks (see course project_High density population service areas_video_7) are to create a map that depicts a parcels which currently fall (completely or partly) within areas of high population density, and b) areas with low population density that are also inexpensive, and thus candidates for increasing population density. For a) calculate population density from the Shady Oaks census data layer. Note that these data are bit messy, population are in the populatio2 item, and there are some small polygons that are artifacts/errors. Also note that these data are in UTM NAD83 Zone 15N coordinates, but this is not recorded for these data (no prj file), so you will likely need to fix this (ArcToolbox, the data management tools, projections). Add a float or double column, calculate the area in sq km for each polygon (to 4 decimal places at least). Select and delete polygons with areas < 0.0049 sq km, add another column, and calculate the population density. Identify areas with a population density greater than or equal to 1000 persons per sqkm within the boundary of shady_oak_census. Save these polygons to another data layer, named something like CenHiDen. Identify polygons in the Shady Oaks parcels layer that intersect with these high-density census areas (use the tool we learned in the Lab exercises to select, top row of main window, Selection, Select by location, select features from parcel_shady_oaks that intersect with your CenHiDen layer). Save these parcel polygons to a new layer, and clip them to the Station Buffer1 layer. Remove all the parcel/polygons with a value = 0 in the TOTALVAL column (these are public lands). You should have a set of polygons similar to the figure at the right. Now, identify candidate areas for increased density. Go back to the parcels_shady_oak layer, and add a value per square meter column, similar to your calculation for population density for the census data layer. You'll need to create a column and calculate the area via calculate geometry, and then create another column to hold the value per square meter. Total value for the parcel is in the item TOTALVAL, divide by area to get value per square meter. Delete those parcels with totalval of zero, these are public or restricted land. Within the area of the station buffer, identify those parcels that have a value per square meter < $60/sq meter. Now, select from these low-cost parcels those parcels that have a popden of less than 250 people/square kilometer (as you did above, first identify the census areas with low popden, then select by location). Clip to the study Page 5 of 7

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/n HOPKINS TRANSIT STATION ANALYSIS GEOG 502 INTRODUCTION For this project, we use Hopkins transit station analysis data. For this transit station analysis, the study area is Hopkins. Hopkins is a suburban city in Hennepin County, Minnesota, United States, located west of Minneapolis (Figure 1). The city is four square