Lab 3

Goals and Background

          The goal of Lab 3 was to learn how to delineate watersheds and understand the concepts behind the analysis. Watersheds are geographically and environmentally important because the water within coverage at low points within the area and exit at a single point, forming rivers and lakes. This network of water sources make pollution particularly troublesome as it can effect all water sources downstream from it's point of origin. Therefore, delineating watershed is of special interest of land and water managers in order to help monitor the amount and quality of water networks within different watersheds.

Methods

          To begin Lab 3, download the Adirondack Park Boundary shapefile from the New York Stat Clearinghouse and unzip the data to your geodatabase. Open ArcMap and notice that the projection for Adirondack Park Boundary feature class is in NAD 1983 UTM Zone 18N in meters. All other features are going to be reprojected to this projection. But first, open the Buffer tool from the ToolBox within Analysis Tools > Proximity. Create a 20 km buffer around the park boundary, setting Dissolve to All. This will create smoother watersheds later in the analysis. 

          Use the Reproject tool from Data Management Tools > Projections and Transformation and reproject the hydrology feature class to the same projection as the park boundary. Utilize Import Projection to easily accomplish this. Use the Clip tool to clip the reprojected hydrology feature class to the original park boundary layer. 

          From Add Data From ArcGIS Online, add a raster called 30-arc-second DEM of North America. Since the DEM has a different project than the layers in the data frame, a window will appear. Click Transformations and set the transformation as convert from GCS_WGS_1984 to NAD 1983. Clip the DEM to the park boundary buffer and check Input Features for Clipping Geometry. Remove the original DEM as it's not needed anymore. Use the Project Raster tool to reproject the clipped DEM to the same projection as the park boundary layer. Use the same method as with the hydrology layer, but include the WGS_1984 to NAD_1983 transformation, choosing bilinear resampling method, and set the X and Y output cell size to 60 m. Once finished, display data that is only in the UTM projection.

          To delineate watersheds, flow directions need to be calculated for each cell. In the Spatial Analyst Tools > Hydrology, select the Flow Direction tool. Use the reprojected DEM as the input surface raster. Next, sinks need to be removed so that the water flow won't be disrupted falsely. Use the Fill tool (also in the Hydrology category) to fill sinks in the reprojected DEM. Determine flow direction for the filled DEM. Water accumulation areas need to be determined. Open the Flow Accumulation tool (Hydrology category) and use your second flow direction output as input. Lastly, a source raster is needed to create a threshold to determine the minimum number of cells that flow into any cell before it is designated as a stream cell. Open the Con tool from Spatial Analyst Tools > Conditional. Choose your water accumulation output as your input conditional raster. Set Type to Value > 50,000 and use 1 as your input true raster value. Label it as net_50k and run the tool. Open the Stream Link tool (Hydrology) to assign unique identifiers to each stream reach. Use net_50k as your input stream raster and use your second flow direction output as your input flow direction raster. Label it as source and run the tool. Open the Stream to Feature tool (Hydrology) to create vector streams using the source raster as your input stream raster and your second flow direction output as your input flow direction raster. 

          Finally, to delineate watersheds, open the Watershed tool (Hydrology). Use you second flow direction output as your input flow direction raster and your source raster as your input raster. Run the tool. Clip the output to the park boundary, checking Input Features for Clipping Geometry. Add the clipped hydrology layer to compare than generated watersheds to the stream locations (Figure 1). 

Results

          Comparing the results from the watershed delineation from a DEM with a cell size of 60 m (Figure 1) to a DEM with a cell size of 120 m (Figure 2), the differences are quit evident. Designating a larger cell size for the same DEM will simplify the raster, cascading its effects to the delineation. This creates less and oversimplified watershed areas. 

          The Vector Streams created from the Methods section are much more simplified versions of the hydrology layer (Figure 3). They follow the general trends of the rivers, being based of the flow direction, water accumulation, and an arbitrarily defined threshold value. 

Figure 1: Watershed delineation with a 50,000 cell threshold derived from a 60 cell size DEM.

Figure 2: Watershed delineation with a 50,000 cell threshold derived from a 120 m cell size DEM.

Figure 3: Vector streams from the watershed analysis compared to the hydrology feature class.

Sources

Barge, J. (n.d.). Adirondack Park Boundary [Downloaded Data]. Retrieved from http://gis.ny.gov/gisdata/inventories/details.cfm?DSID=303.

 National Aeronautics and Space Administration (NASA), the United Nations Environment Programme/Global Resource Information Database (UNEP/GRID), the U.S. Agency for International Development (USAID), the Instituto Nacional de Estadistica Geografica e Informatica (INEGI) of Mexico, the Geographical Survey Institute (GSI) of Japan, Manaaki Whenua Landcare Research of New Zealand, and the Scientific Committee on Antarctic Research (SCAR). 30-arc-second digital elevation model (DEM) of North America. Retrieved from ArcGIS Online.

Cornell University. hydrology. Retrieved from https://cugir.library.cornell.edu.

Lab 2

Goal and Background

          The main purpose of Lab 2 was to familiarize with georeferencing and digitizing techniques from GIS I in order to solve spatial referencing problems and analyze spatial data in preparation or new concepts in GIS II.

Methods

          Open ArcMap and set up the georeferencing toolbar from the Customize tab. Bring the Centerlines_clip shapefile into ArcMap so that the data frame projects on the fly for that projection. Then add the Topographic base map from ESRI. Next, bring in the scanned 1878 map of Eau Claire, WI which will be georeferenced to the Centerlines_clip as its reference. Using the georeferencing toolbar, Fit to Display the scanned map and shift and scale the map so that it relatively matches the base map. Adding transparency to the scanned map will make this process easier. Add control points by clicking the scanned map first and then to its corresponding place in the reference image or feature class. Control points should be equally dispersed across the target image, but in this case, that might not be entirely possible. Easily distinguishable features between the target and reference image were clustered around the center of the image. Add control points until the scanned map lines up with the reference image until it is satisfactory. The RMS might be high, but considering the 140-year gap between the reference and target image, if it visibly looks alright, it'll have to do. Set a transformation. A first-order transformation might be the most appropriate choice since the warping of the other orders aren't necessary for a scanned map and the exact coordinates aren't known for a spline transformation (if there's enough control points). Update georeferencing when finished. Set the transparency to 50% to inspect how well the georeferenced image fits the base map (Figure 1).

          The second part of the lab involving creating data to analyze the differences in water area between 1878 and 2018. First, create a new geodatabase. From the Toolbox, open the Create Feature Class tool. Set its location to the new geodatabase, name it hydro_1878, set its geometry type to polygon, and set its coordinate system to the same one as Centerlines_clip. Bring in the study area shapefile into the data frame. Open the Editor toolbar and click Start Editing. Edit the feature class hydro_1878. Using polygons, digitize the Chippewa River, Eau Claire River, and Half Moon Lake within the study area using the georeferenced 1878 scanned map as a reference. Save edits and click Stop Editing. Now create another feature class and call it hydro_2018. Start editing the hydro_2018 feature class. Digitize the Chippewa River, Eau Claire River, and Half Moon Lake within the study area using the ESRI Topographic base map as a reference. Save edits and stop editing. Open the new feature classes' attribute table and use Statistics on the Shape_Area field to compare the total area of water between 1878 and 2018. Visually compare the differences by displaying the feature classes together (Figure 2).

Results

          Figure 1 shows the 1878 scanned map georeference and displayed with a 50% transparency over a topographic base map. 

Figure 1: Map of the 1878 Eau Claire map georeferenced over a modern base map.

          Figure 2 shows the differences between water features in 1878 and 2018. Visually, there appears to be more water area in 2018, but in reality, there was more water area in 1878, given by the statistics in the attribute table.

Figure 2: Map of the water area differences in Eau Claire, WI between 1878 and 2018.

Sources

David Ramsey Map Collection (2018). Eau Claire and Medford. Retrieved  from https://www.davidrumsey.com/luna/servlet/detail/RUMSEY~8~1~4181~480085#.

Eau Claire County (2014) Master_Centerlines. Retrieved from Caitlyn Curtis.

ESRI (2018). Wold Topographic Map. Retrieved from https://www.arcgis.com/home/item.html?id=30e5fe3149c34df1ba922e6f5bbf808f.

Lab 1

Goal and Background

          The purpose of Lab 1 was to revisit key concepts and basics of GIS I and to familiarize with the software before learning new skills and techniques of GIS II.

Methods

          Within ArcCatalog, selecting the Connect to Folder icon will allow the user to bring in the desired directory to the Catalog Tree, where the desired folders and contents are easily accessible on the left side of ArcCatalog. The contents of the folder can be examined by clicking the + icon next to the folders. Connect to the Lab 1 folder and activate Countries94. In the Preview tab, the data Counties94 is shown in its original form. Preview other data within the Lab 1 folder.

          Open a blank map in ArcMap, where the data can be displayed and manipulated in layers. Open the ArcCatalog tab within ArcMap and drag the shapefile WorldCities into the display screen in ArcMap. Clicking on the colored box in the Table of Contents can allow the user to change the colors of the data.

          Under File, select Open. Navigate to the Lab 1 folder and select the Redlands map (it's a mxd. file). The map is displayed in ArcMap. Checking and unchecking the layers in the Table of Contents will display and remove layers on the display screen. Try displaying Railroads and Streets. Right click any of the layers and select Properties. Information about the layer and be viewed and altered in ArcMap, like its geographic coordinate and projected coordinate system. 

          The Redlands map has a stored bookmark. From the Bookmark tab, select ESRI. The display zooms in on the ESRI feature, the location of ESRI. ESRI and street names are now visible because the map creator put a scale limit to these two features. In the Toolbar, click on the Identity tool. Click on New York Street. A window opens with all the attribute information on New York Street. Clicking on the name of the street in the Identity window will flash the feature on the display screen. Selecting All Layers from the layer dropdown in the Identify window will display all attributes of all the layers that New York Street is contained in. Identify more features and review their attributes.

          Return to the original extent by clicking on Original in the Bookmarks tab. Right click Railroads and open its Attribute Table. Review its attribute fields and the number of rows. Do the same for the Donut Shops and Streets layer. 

          Open a new blank map in ArcMap. From the Add Data icon, navigate to the Lab 1 folder and add the Erie shapefile. Open its attribute table and take note of its attribute fields. Open the layers Properties window and go to its Symbology tab. Select Quantities and then Graduated Colors. For its Field, select Persons. Change the color ramp to an appropriate choice. Some data should be normalized. For example, if an attribute can be affected by how much land there is, it's a good idea to normalize it by Area. Normalize Person by Area to get a population density (Figure 1). From the Properties window, go to the Labels tab. Select Person as a Label Field. Right clicking the Erie layer in the Table of Contents and selecting Label Features will show the labels in the display screen. In the Symbology tab, create a graduated color scheme for another attribute and decide if normalization is appropriate (Figure 2).

          

Results

           The attributes Persons and Households were both normalized by Area to show more useful data - population density (Figure 1) and household density (Figure 2). Both variable show very similar patterns in which tracts have high and low densities. This comes to no surprise as both variables should go hand-in-hand.

Figure 1: Population density for Erie County.

Figure 2: Household density for Erie County.

Sources

Curtis, Caitlyn (2018) Lab 1 Data [Downloaded Data].