Joel Sexson's GIS Blog UWF

 Hello all, in this week of Photo Interpretation and Remote Sensing, we learned about how remote sensing data is represented in multispectral bands, as well as using greyscale and spectral enhancements to learn about brightness, sharpness, and contrast in imagery. We used ERDAS Imagine to analyze the images and ArcGIS to make layouts.  This image uses true color imagery to showcase the brightness of the snow on top of the mountains in contrast to the dark green vegetation surrounding it.  This image uses a unique band combination (shown in the legend) to showcase the variation in brightness of the water.  This image uses false color imagery to showcase the dark blue/black water in contrast to the red vegetation around it. The vegetation is not actually red, this is just a false color image.  Thank you, Joel Sexson

 Hello all, in this week of Photo Interpretation and Remote Sensing we practiced using ERDAS Imagine to analyze remote sensing digital data. We also learned about the EMR spectrum and how data is digitized differently to get higher resolutions, e.g. radiometric or spatial resolution with maximum pixel amount and pixel size, respectively.  This map depicts the small subset of an image that had been exported from ERDAS Imagine to ArcGIS to be able to display it in a more friendly way. The image's data (such as the area and classification) was preserved over the exportation, which made the whole process quite easy.  Thank you, Joel Sexson

 Hello all, in module 2 of my PI&RS course, we practiced land use/land classification (LULC) on a photo. We also got practice with digitally truthing to test out the accuracy of our classifications.  I have included the map from the exercise below. The map shows the LULC in slightly transparent colors and the accuracy of the random points. The legend gives a brief description of each type of LULC code. This exercise was useful in learning how to use some interpretation skills that I learned from the previous model on classifying areas within a photo.  Thank you, Joel Sexson

      Hello all, in the first module of my PI&RS course, we practiced three different methods of visual interpretation. We used aerial photos and practiced identifying features based on tone, texture, shadows, shape/size, association, and patterns. We also compared a true-color image to its false-color counterpart to understand the contrast between how colors are displayed between the two methods.      I have included the map layouts of my visual interpretations from Exercises 1 and 2, but not the map from Exercise 3 which involved the color method comparisons.      The first map depicts the interpretation of different levels of tone and texture on an aerial photo. The tone ranged from very dark to very light and the texture ranged from very fine to very coarse. The texture was easier to determine than the tone which caused the tone portion of the exercise to take longer; however, I was able to complete it fully in the end.    ...

 Hello all, in the final week of GIS Programming we learned how to work with geometric data from ArcGIS in Python. This included each level of geometric data, from features and arrays down to just point and coordinate data. We also practiced writing data to a text file and using the nested for loops to reach different levels of data. The getPart method was used in particular to skip a loop and retrieve the coordinate data for the rivers.  I've included a small text file section where I printed the OID, vertex ID, x,y coordinates, and the feature's name (from left to right).      The assignment was very logical and did not create too many problems for me. I need to remember to close the text file at the end so that the processes will actually occur and write to the text file. I've included a flowchart of the logic of my script below: Thank you,     Joel Sexson

 Hello all, in the 5th week of GIS Programming we learned how to deal with data. As the title of the module states, we explored data using things like describe functions and search cursors, and we manipulated data by learning about insert/update cursors and how to create different data (such as creating a file geodatabase or a dictionary).      The assignment was to create a script that made a new file geodatabase, copied over feature classes from one folder to the geodatabase, and then populated a dictionary using data from a search cursor done on the cities layer in the fGDB.      Below is a picture of the flowchart of my script:       The results of the script are shown above. There are print statements throughout the script to explain what processes were happening and when they were completed. The only problem that I ran into with the script actually helped me learn how to determine if my script is working the way I want it to i...