Brooke's GIS Blog

The objectives for this week's lab were to create 3D visualizations of elevation models, create and modify a TIN using various input datasets, compare TIN and DEM elevation models in terms of properties and derivatives. Beginning with the first part of this lab, Part A, draping an image over a terrain surface, the outcome was learning the basics of local 2D/3D scenes, how to navigate and display TINS/Elevation Surfaces. Next, part B involved using a DEM to develop a ski run suitability map, and the outcome of this was a suitability map showing the slope, aspect and reclassification suitability rasters as a 3D scene with a weighted overlay. The following section of the lab, part C, focused on exploring TINS, primarily the symbology and the meaning behind the symbology, for example: slope, edges and aspect. The end goal was symbology that displayed both the slope, edges and contours. Finally, part D was the creation of a TIN and the analyzing of the created TIN using the Create TIN a...

 The goals of this week's lab were to determine the completeness of road networks and summarize the analysis in textual, visual and numerical terms. Beginning with the readings for this module, one particular reading/study that interested me "A comparative study of OpenStreetMap and Ordnance Survey datasets" which followed the outline of this weeks lab for comparing the accuracy of roadway mapping. In this reading, crowdsourcing was defined as a benefit to the GIS community, with an ability for "large groups of users [to] perform functions that are either difficult to automate or expensive to implement" in regards to applications of GIS (Howe, 2006). However, also mentioned was the possible downsides of crowdsourcing - inaccurate information. Both this week's lab and this reading touched on a similar subject of how to analyze data for completeness. The steps I took in order to identify roadway accuracy in a grid system was f irst, I used the geoprocessing to...

  Accuracy statement   The project This project evaluated the accuracy of mapped intersections of roadways in Albuquerque, New Mexico. 20 reference points were chosen from the independent data set, and were tested with two additional datasets, totaling for a collection of 60 data points.   The tested data set The two data sets consist of polyline data of roadways in Albuquerque, New Mexico from StreetMap USA and the city of Albuquerque. The reference points chosen in the independent data set were tested with both StreetMap USA and the city of Albuquerque, for a total of 40 points.   The independent data set Ortoimagery was used to manually identify the center of intersections. The objectives of this lab were to learn how to determine the quality of road networks, determine positional accuracy of two road networks by comparison and understand the procedures provided by the National Standard for Spatial Data Accuracy. A brief overview of the steps tak...