Biscayne Shipwrecks - Analyze Week

   In this week's lab, analysis was conducted on the benthic and bathymetric data from last week. Buffers and clipping was used to determine what type of benthic features could be found within 300 meters of the Heritage Trail shipwreck sites. The benthic and bathymetric data was further analyzed through reclassification in order to determine areas that could be potentially dangerous for ships to travel through. Finally, this reclassified data was ran through a weighted overlay analysis, combining both inputs together to create an output that displays potential areas for shipwreck locations.

300 meter buffer displaying benthic features around each site

Reclassified data

Weighted Overlay Model output

Supervised Classification

In this lab, a supervised classification of current land use in Germantown, Maryland was conducted using ERDAS Imagine. AOI signatures were selected by hand using the polygon tool and recorded in the Signature Editor dialog box. All signatures were analyzed through the Mean Plot tool to determine which bands provided the greatest difference between signatures. The bands 3, 4, and 5 provided the greatest difference in signatures and was set as the band combination to reflect the data best. The signatures were then run through the Supervised Classification tool, with an additional Distance File output to show if any signature features are likely to have the wrong classification (symbolized as bright spots). The Distance File is used as a reference for correcting any wrongly classified signatures. Lastly, the supervised image is recoded by consolidating the signatures to eight classes. Those classes are agriculture, deciduous forest, fallow field, grasses, mixed forest, roads, urban/residential, and water. The final output map was created through ArcMap.

Modeling Biscayne Shipwrecks - Prepare Week

   This week, we gathered data on shipwrecks in the Biscayne National Park. This data will be used to generate a weighted overlay model. Data gathered includes a historical nautical chart from 1892, a current ENC, and bathymetric data for the Biscayne Bay. The historical chart was downloaded from the NOAA's Historical Map and Chart Collection and georeferenced to the location. The bathymetric data was downloaded from the NOAA's National Geophysical Data Center and symbolized to reflect depth in meters (shallow in red, deep in blue).

Unsupervised Classification

   In this lab, an unsupervised classification was performed on an aerial image of the UWF campus, in ERDAS Imagine, using the Unsupervised Classification tool in the Raster tab. Afterward, the results of the unsupervised classification was further reclassified by condensing the original output of fifty color categories into just five color categories. These five categories are grass, trees, shadows, roads/buildings, and mixed surfaces. Mixed surfaces is classified as pixels that can be found across multiple surface types and can not be pinpointed to just one category.

   The total area of the campus is 232.26 hectares. Of that total, 142.735 ha (61%) was classified as permeable while 89.5237 ha (39%) was classified as impermeable. Permeable surfaces consisted of the categories grass, trees, and shadows. While some shadows covered impermeable surfaces, the majority covered permeable surfaces. Impermeable surfaces consisted of roads/buildings and mixed. While some mixed surfaces covered permeable areas, the majority covered impermeable surfaces.

Thermal Imagery

The feature I identified for this lab was a large tract of bare soil located at the southern tip of the city, surrounded predominantly by urban area and some vegetation directly to the south of it. I was looking over the stretched symbology (Band 6) of the image in ArcMap when I saw a bright spot in that area, surrounded by grey (urban area) and a darker spot just below it (which looks like vegetation in the natural color image). Further analysis and comparison between the two images (natural color and thermal) determined this was bare soil. I chose to use the band combination Red- 6, Green- 3, Blue- 2. This band combination is used to distinguish between different soils and soil moisture content. The 6, 3, 2 band combination made soils appear in light to dark reds, starkly contrasting it with surrounding colors.

Scythian Landscapes - Analyze Week

In this lab, Elevation, Slope, and Aspect are taken into consideration and reclassified in ArcMap to aid in the interpretation and analysis of the Tuekta Mounds study area. They were each simplified for further analysis by condensing their data into smaller groupings, as reflected in their legends. Contour lines in meters of elevation were made for the Tuekta area as well. Also, a shapefile was made including point locations of up to 50 mound sites in the georeferenced Tuekta Mounds image.

Image Preprocessing 2: Spectral Enhancement and Band Indices

In this lab, we used ERDAS Imagine to perform various image processing tools. Tools and topics covered were the histogram, the Inquire tool, the help menu, and interpreting features digital data. The deliverable for this assignment was to locate 3 features based on pixel variations using the directions provided in the lab. The features I located are water, ice, and water body variations. Below are my map outputs.