Saturday, July 23, 2022

Visibility Analysis









For this lab I learned about the basics of visibility analysis, how to use line of sight analysis, viewshed analysis, and how to share the outputs of these techniques. I learned about how the z coordinate can affect eh data and how to use it to accurately make 2D data into 3D data. I learned how line of sight can accurately show what is visible from certain location and how it can be used to position thing for the best visibility. Additionally I learn the different types of viewshed and their advantages and disadvantages like the triangulation based data. I learned how effectively share the data which I already understood the only thing that was new was learning is how to create and share a hosted scene layer. 
 

Sunday, July 17, 2022

Forestry and LiDAR






For this lab I word with topographic LiDAR data to show and analyze vegetation and Canopy data in a National Park in Virginia. For me this lab had several challengers that took a lot of time overcome especially the large amount of processing time that was needed to render the output. Though I really struggled with creating the canopy density map since my output was not similar to the example provided and I redid the step at least 5 times until it finally after much trial and error looked correct. I also struggle to create an appropriate scale bar for the 3D maps but I also manage to get it to scale correctly by copying a scale bar from a 2D layout and like magic it scale properly. All in all I learned a lot about 3D analysis and imaging.
 

Saturday, July 9, 2022

Crime Analysis


 
For this lab we created 3 maps to analyze the crime in Chicago and using it to predict future crimes. Each map used a different technique to create a hotspot layer of the map. In general I experienced a few issues with two of the techniques the were appeared to be GIS issues and simply rerunning the tools and repeating previous step allowed me to get the correct outputs. And from a comparison of the data it was determined that the Grid based map was the best at predicting future crime due to the small area it produced compared to the other two and its high density of crime located within its boundaries. This would be useful for policing to know since they have limited resources and accurately predict where crime will appear.  


LAB 6 Scale Effect and Spatial Data Aggregation

In regards to the effects of scale on vector data I learned that as the larger the scale the larger the units that are measured come out to ...