Suitability and Least-Cost Analysis

For this analysis, suitability of black bear habitat was defined using Euclidean Distance followed the Reclassify tool to define distance from the road. Next, the elevation layer was reclassified to identify mid-elevation ranges and finally the land cover data was reclassified showing different values for different habitat types. Once each layer was reclassified, the criteria for suitable black bear habitat were combined using the Weighted Overlay tool. From there, cost surface was created by inverting the suitability (10-suitability). The Cost Distance tool was then run from each Coronado forest polygon using the cost surface. Then using the two cost distance rasters, the Corridor tool was run. From that point, the best corridor cells were selected using a threshold on corridor values and the final corridor raster was created.

Damage Assessment

 Final Results

 

Structure Damage Category	Count of Structures 0-100 m from coastline	Count of Structures 100-200 m from coastline	Count of Structures 200-300 m from coastline
No Damage	0	0	13
Affected	0	8	17
Minor Damage	0	14	4
Major Damage	0	11	4
Destroyed	9	6
Totals	9	39	38

Coastal Flooding Analysis

In this week's lab, the focus was on the analysis of coastal flooding. The first part of the lab was focused on the aftermath of Hurricane Sandy after making landfall along the coast of New Jersey in 2012. The data we worked with was LiDAR data downloaded from the NOAA website. When analyzing LiDAR data in GIS, the .laz file must be converted to a .las file because GIS does not support .laz. So, the first step in this lab was to convert the data into a .las file. To do this, the Spatial ETL tool was used. 

Once the data was converted, the next step is to create digital elevation models (DEM's) so we can create an elevation change layer to better see the impacts a storm surge. Working with this kind 

The map below shows the elevation changes along the coast of Mantoloking, NJ after Hurricane Sandy.

 

Forestry and Lidar

 

Crime Analysis

Working with Geometries

    In this final week of GIS Programming, we were tasked with creating a text file that reads data from the shape file rivers.shp. Below is the final result from the text document created as well as a flow chart demonstrating steps to complete the assignment.

 

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.