Brooke's GIS Blog

  Numerical results: Horizontal precision -  My horizontal precision for 68% in meters was 6.812469.  The objectives for this lab assignment were to understand the difference between precision and accuracy, calculate vertical and horizontal position accuracy and precision, calculate root-mean-square error and cumulative distribution function. Detailing the first objective, the difference between precision and accuracy, precision refers to the position of the waypoints from eachother. For example, looking at my attached map, the waypoints are scattered all over the map frame, and cannot be identified as being near eachother. I would say this means that the collected data has low precision. On the contrary, accuracy refers to the position of waypoints in relation to a reference point, or the average waypoints data (represented by the star on the map). Because the majority of waypoints are contained within the specified buffers of 95%, 68% and 50%, I would say this means tha...

Beginning with the roads shapefile, I used the geoprocessing tool Euclidean Distance to establish cell values for the distance from the roads. From there, I used the geoprocessing tool Reclassify to reclassify the values according to suitability, as outlined in the laboratory guide. Moving onto elevation, I reclassified the values depending on suitability, and again, outlined in the laboratory guide. Landcover was completed similarly, except when using Reclassify I had to select unique values to assign a suitability value to each landcover value. After all the layers were properly reclassified, I used the Weighted Overlay tool to combine the three previously mentioned layers and used the relative weights listed in the laboratory guide. To invert the suitability model which was created with the Weighted Overlay tool, I inverted graduated red symbology. After, I had used the raster calculator with the expression ((10) – “ my weighted reclass layer ”). Once I had the raster layer with 9 s...

  Discussing the process to create a suitability analysis, I first began with the reclassification of the landcover layer using the Reclassification geoprocessing tool and specifying the suitability rating coinciding with the values for each land cover category. Once the first layer was completed, I moved on to the elevation layer, where I first had to find the slope before reclassifying it using the same parameters as discussed for the landcover layer. Again, I followed the same reclassification steps for the following layers: soil, roads and rivers, but I used the Slope geoprocessing tool to create a raster DEM and the Euclidean Distance Tool to establish cell values, respectively. Once the layers were reclassified, I began on the Weighted Overlay using the geoprocessing tool. I started the first analysis using a Weighted Overlay of 20% across the board for all 5 categories. The second analysis using Weighted Overlay was different, land cover was 20%, soils were 20%, slope was %4...