Exploring and Manipulating Data

In this week's lab, we were tasked with creating a new geodatabase and copying data to that gdb. Once that was complete, we had to populate a dictionary using some of the data from the new geodatabase. With all of the practice using Python these last several weeks, it really feels as though I've made progress in learning this skill. So, the first part of this lab went smoothly for me. However, the part of the assignment in which we had to create a Search Cursor, a dictionary, and populate the dictionary really gave me some trouble.

Below is a screenshot of the geodatabase (jag198.gdb) and data copied over to it. 

 

Geoprocessing with Python

By now, we're all very familiar with using geoprocessing tools in ArcGis. But this week gave us the opportunity to learn how to utilize those tools with Python scripting.

After each tool is performed, your script will print a message with information about its successful execution and a time stamp of when the tool was executed. The screen shot above is an example of such a message. For this exercise, we were tasked with writing a code that would add x,y coordinates and a 1000-meter buffer to the designated shapefile. 

Since I am still very new to writing code, the Esri website was very helpful in guiding me through this process.

Debugging in Python

 

Python Fundamentals

 

Python Environments and Flowcharts

This first assignment in GIS programming was designed to show us the Python environment, how to use it, and how to create flowcharts. Going into this class with no prior experience in programming, I feel much more at ease after completing this week's module. Below is a simple flowchart created to demonstrating the logical process of how the problem (degrees=radians*180/pi) can be solved.

Another requirement for this week was to read “The Zen of Python” by Tim Peters. This is a set of 19 "guiding principles" that can be found by typing import this into IDLE. I believe these guiding principles are a shared philosophy within the Python community to emphasize to the user the importance of simplicity, clarity, and readability when writing code in Python. The purpose is to set a standard that anyone and everyone can understand and use. Python is, after all, for anyone who wants to learn to code and not just for the coding experts. The line “Explicit is better than implicit” resonates with me most, as I value clear and concise instruction that is unambiguous, leaving little space for guessing at any underlining meaning.

 

Supervised Classification

 

Spatial Enhancement, Multispectral Data, and Band Indices

 
This week's lab focused on my neck of the woods in the Pacific Northwest.  It was fun getting to learn about different spectral combinations to identify features in a region that I am very well acquainted with.

The focus this week was to learn how to use different processes to identify features in an image. Some of these processes included the use of histograms, image enhancement methods, and the use of spectral characteristics.