In this lab I learned how to build, manipulate, and present elevation data collected by a land survey. Using data available at gis.joewheaton.org for the Bridge Creek area, survey points were transformed into a TIN. This TIN was then used to generate a DEM. DEMs are a very useful and visual way to present elevation data, and can be used for analysis. Some of the analyses performed in this lab included generating a water depth DEM and finding erosion/sedimentation in the area between 2010 and 2011.
The Bridge Creek area is located in Oregon. Below is a google map showing the spacial context of where this lab takes place.
The raw survey data shown below were downloaded from Joe Wheaton's website as a .csv, and imported into ArcMap (spacial reference is shown in the google map, not each figure to save time and space).
These points were then used to create a TIN. By isolating the points that represented grade changes, the TIN became more accurate.
A water profile through the main channel was generated using the 3D analyst tools. This is shown in the chart below.
Aerial LiDaR data is created using a plane with a laser and sensor. This can determine the distance from the plane to the ground at multiple locations, creating a three-dimensional image of the location. The LiDaR data available for this location is rather coarse (1m resolution). If collected periodically, and at a higher resolution (like 25cm), it could be useful for analyzing the surface to detect changes in channel morphometry. Unfortunately we only have one year of data, collected in 2005. In certain situations survey data may be more beneficial, as elevations that are obstructed by aerial view (by trees and things) can be collected.
A model was created using two DEMs provided. The model found the differences in surface elevation between 2010 and 2011. This shows locations on the river that have had erosion and deposition of sediment. The model found the differences between the two DEMS, removed the places where the elevation change was an uncertain value, then outputted the new change DEM. A visual description of this process is below, and the toolbox can be downloaded here.
The results of the analysis is shown in the figure below overlaid on the LiDaR DEM. PDF.
Overall, this lab was useful but required a lot of time. DEMs are powerful tools, but extremely prone to data corruption. Also, data management is extremely necessary, as this lab dealt with nearly 30 different data sources. The model creation and batch processing tools were likely the most useful part of this exercise.