Photo Interpretation and Remote Sensing (GIS4035): Lab 3

In this week's lab, we looked at an aerial photograph of Pascagoula, MS and determine the land use of each part of the town. After determining that land use, a code was assigned to each type of land use. ArcMap was utilized for this assignment which allow us to create a landcover of Pascagoula. We used the LULC land classification system and the level that was primarily used for the map was level II and there were some level III codes used as well.

Special Topics in GIS (GIS5935): Lab 2

In this week's lab, we had to determine the horizontal positional accuracy of road network according to the NSSDA. 20 random points were selected from the City shapefile and these points had good intersections and straight or close-straight angles. Using these points, the matching 20 points were found on the StreetMap shapefile. Once these points were found, a reference points were placed according to visual sense of where the true location of the points were. The XY Coordinates tool was used to all three point shapefiles so that each of the shapefiles' XY coordinates would be applied to the accuracy statistics chart. The attribute table of the shapefiles were exported as Excel files which I was able to copy and paste each of the X and Y data into the accuracy statistics.

1.       The City Results’ Horizontal Positional Accuracy: Tested 88.85 feet horizontal accuracy of 95% confidence level.

The StreetMap Results’ Horizontal Positional Accuracy: Tested 517.6 feet horizontal accuracy at 95% confidence level.

Photo Interpretation and Remote Sensing (GIS4035): Lab 2

In this week's lab 2, the first exercise looked at identifying various tones and textures in an aerial photograph which shown in the map 1. In the second exercise, features had to be identified in the aerial photograph which is shown in map 2. The features that we had to identify were shape-size, shadow, pattern, and association. The last exercise, we had to select five features and note the color changes between a true color photograph and a false color photograph. This lab was very interesting since we were applying the knowledge of the recognition elements to our examination of these aerial photographs.

Special Topics In GIS (GIS5935): Lab 1

In this week's lab, we learned how to calculate metrics for spatial data quality. The first image shows the precision and accuracy of the GPS Unit's results. The number of waypoints that were analyzed were 50. The data had to be projected from GCS WGS 1984 to UTM N17 NAD 1983. This allows us to be able to measure these points using metrics instead of degrees. We had to find out the accuracy and precision of the data. The result of the horizontal accuracy is 3.2 meters. The horizontal precision is 4.5 meters. The both of the results are 0.7 meters off from each other. The vertical accuracy is 5.96 meters and the vertical precision is 0.9 meters. The difference between the two vertical results is substantial. The measured difference between the two is 5.06 meters.  The second image is a CDF scatterplot chart of the error of x and y coordinates from 200 points. 

The horizontal accuracy was measured by measuring the reference point and the average location point. The Measure tool was used to measure the distance between the point which give the resulted number of what the horizontal accuracy is. The precision was found by sorting the distance field in the attribute table of the spatial joined data sets and assuming that the first number that was listed was 2% and count all the way to 68%.

Photo Interpretation and Remote Sensing (GIS4035): Own Your Map

In this week's lab, we had to created a map showing the UWF Campus location in Escambia County, FL. The major rivers and interstate data had to clipped to the shape of Escambia County. This assignment was relatively easy to complete since I had already done this assignment before in the Intro to GIS course this Spring and this lab was like a refresher for me.

GIS Programming (GIS5103): Module 11

In this week's module, we learned how to share tools that we created for ArcMap. The first way of sharing an ArcPy script tool is compressed the original folder that houses the script into a .zip file. The second way is putting the tool files on the local network (this is only relative if you are on shared network environment). The third way is to publish the toolbox as a geoprocessing service which can be publically assessable to anyone on the Internet.  We also learned how to embedded our scripts into the script. By embedding the script into the script tool, you can share the toolbox file instead of a .zip file which has three different files or more. Another benefit of embedding the script is that you can place a password on the script to prevent people from editing or viewing the script.

Some of the highlights of what I learned this semester:

1.       I think the interesting thing I learned in this class was in Module 9. I thought that using the Python script to find areas that had certain characteristics by using parameters, such as, slope, aspect, and landcover type was a great way to cut the time of finding each of these characteristics. It was kind of fun having a script that able to perform multiple functions.

2.       The most useful thing that I learned was making sure that the line of code was in the right location in the script because certain lines of code should not be placed in the for loop. I found this out when I was working on Module 8’s script; I was trying to print each point’s Feature OID, Vertex ID, X coordinate, Y coordinate, and the name of the river feature.

GIS Programming (GIS5103): Module 10

In this week's module, we learned aspects of creating a script tool for ArcGIS and how to modify the script to fit the need of the project's tool. We created a toolbox to house the newly created script tool. The parameters were set using the Parameter Tab in the Properties window so that the imported script will function in ArcMap. After setting the parameters in ArcMap, the script had to be modified in PythonWin. The parameters' variables had to be changed to from specifically located files to open input. The arcpy.GetParameter() function was applied to parameters' variables. Along with the changing the variables, the print statements had to be replaced with arcpy.AddMessage() statements so that ArcMap can print the messages in the Results tab.