GIS 5013 - Peer Review #1


In the article by Jisheng Xia and Pinliang Dong titled “A GIS add-in for automated measurement ofsand dune migration using LiDAR-derived multitemporal and high-resolutiondigital elevation models”, the development of an add-in tool bar for ArcGIS using Python was created to automatically detect, measure, and store dune migration direction and rate at random point locations.  The model was then tested out on White Sands National Monument in New Mexico.
The introduction effectively discusses the importance of having a tool that will automatically conduct dune studies. The article states that the previous methods (before the development of the tool bar) involved remote sensing and LiDAR, however the interpretation was visual and the measurements had to be done manually (which are subjective based on the experience and judgement of the operator). For sand dunes that are constantly changing and are an important part of our landscapes, it is important to have an automated process as errors are prominent in manual methods, and time is of essence.  The authors also went into the steps that were taken to get to the point of the toolbar. The first part involved Dong proposing a method (pairs of source and target points – PSTP) and implemented this using ModelBuilder. After, Dong paired up with Xia to develop an add-in toolbar using Python specifically made to measure dune migration direction and rates.   
The methods thoroughly explain the PSTP method, however a little mind boggling and technical to myself, I am sure would make sense to the seasoned GIS professional. Within the methods, the article created a subsection describing the methods and laying out the steps for the use of python and ArcGIS which made it organized and easy to follow.  The presentation within the methods is effective as it screen clips an example toolbar and explains the 6 parts that were created.  The presentation of the article also lays out the pseudocode that was developed. I particularly appreciate how simple, yet detailed the pseudocode is.  As a beginner, I can easily see how the code was developed and the steps that were taken to create the toolbar. On first look (and without getting hands on experience with the tool), the pseudocode looks complete and concise as it does not contain anything that is not needed.   With a little more experience and teaching, any of us could probably replicate this process.
The article then shows an example of the toolbar application in White Sands National Monument. The most interesting aspect of this, for me, was actually seeing how the dunes have shifted within a year, also that the processing time was only two minutes! The authors also discussed how this differs from the previous methods on manual interpretation and measurements and nearly every manually measured point is slightly off from the toolbar measurement.  
Overall, this article clearly lays out the necessity for a sand dune measurement tool bar.  It went into enough detail to describe the process and how the script to make the toolbar was created.  The greatest strength of this paper (and the script) is that it followed the Zen of Python. Mainly in that it was not too technical or overwhelming, and the pseudocode created was not unnecessarily complicated. I clearly got the gist for how the toolbar was created in python and have confidence that one day I could easily replicate and maybe even create something similar.

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