Alec's GIS Blog

The lab assignment for module 5 focused on applying data exploration and manipulation. The core of the assignment involved automating several geoprocessing tasks to streamline data management. This was primarily achieved by first establishing a new geodatabase, a central repository for all geospatial data, and then programmatically populating it with existing feature classes from a designated data folder. This initial data handling laid the groundwork for subsequent analysis and ensured a clean and organized workspace for the module's objectives. A key aspect of the data manipulation in Module 5 involved extracting specific information from a feature class and structuring it for further use. This was accomplished by employing a search cursor to iterate through records and selectively retrieve attributes like city names and populations, specifically focusing on "County Seat" cities in New Mexico. This targeted data extraction was then used for populating a Python dictionar...

In Module 4, we explored geoprocessing in ArcGIS Pro, focusing on how Python can automate GIS tasks. Geoprocessing in ArcGIS Pro refers to the framework and tools used for processing and analyzing geographic data. It allows users to perform operations like data conversion, spatial analysis, and data management tasks. Essentially, it transforms geographic data, taking an input, performing an operation, and producing a new output dataset. For the lab in module 4 assignment there were two main parts. First, I used ModelBuilder to create a visual workflow. This model clipped soil data selected specific areas and then erased those areas from a basin. ModelBuilder is a good way to see how geoprocessing tools connect. See the results below. Model  Model Runs Successfully Results  Second, I wrote a Python script in an ArcGIS Pro Notebook. This script processed hospital data by adding XY coordinates, creating buffers, and then dissolving those buffers into a single feature. Key aspects...

 In module 3 we covered debugging and error handling. Debugging and error handling are important aspects of writing code in python. Debugging involves identifying and resolving errors in the scripts you write. Error handling focuses on potential issues and managing them during runtime.  In our lab assignment we got some hands-on experience debugging and error handling three different scripts. For the first, we were given a script with the task to identify and fix two errors. This involved examining the code for logical flaws or syntax mistakes. Once the errors were identified I ran the code to make sure that the errors had been fixed and that there were no more errors. The complexity increased for the next two scripts.  The objective of the second script was the same, identify the errors or exceptions so that the code could run properly. The second script was more challenging due to a file path error. The file path was inaccurate in the script and needed to be corrected i...