Photo Interpretation and Remote Sensing (GIS4035): Module 8

In this week's lab, we learned about the use of thermal imaging identify features based on the temperature that the object is emitting. The map above is identifying the temperature fluctuation in the bay area of Pensacola Beach.The heat islands near the bottom of the image are what caught my attention and then I notice the temperature fluctuation in the water in the bay area. The band combinations that I used for the feature to stand out are red – 3, green -2, and blue -7. The movement of the water’s fluctuating temperature can be seen when it get cooler as it touches the shoreline of Pensacola Beach.

Special Topics in GIS (GIS5935): Lab 8

IDW Interpolation

In this week's lab, we learned about different interpolation techniques and applied to water quality sampling points of Tampa Bay area. Three different interpolation techniques were used which were Thiessen, IDW, and Spline. The numerical results of both Thiessen and IDW were very similar; however the patterns of the results were quite difference from each. Thiessen retained it's polygon features when converting into a raster dataset unlike IDW which does not having any polygon features or outlines. The Spline interpolation technique shows the BOD concentration’s minimum is in the negatives and is higher than the previous interpolation techniques that were applied to this data. By having a higher minimum, the surface curvature minimum is that particular area to be extremely high since there are no sampling points in this area to create a smooth surface for the Spline interpolation. The Spline interpolation relies heavily on the input points to create a smooth surface. Lack of points in a particular location of the data will create a distorted when using Spline interpolation. To remedy this problem, deleting a point from the wq_bod data will reduce the minimum value of the points which will create a smooth surface.

 

Photo Interpretation and Remote Sensing (GIS4035): Lab 7

In this week's lab, we learned how to utilize EDRAS for a multispectral analysis of an aerial image. The image's histogram helped identify spikes in pixel values which help with deducing the features that match the pixel value of the spike. To enhances the features that were being identified, we changed the band combinations of the image and manipulated the contrast of the image. Also, we created NDVI to help differentiate the clearcut areas in the image that was provided. Here are the deliverables that we had to created of the features that we found for Lab 7.

Feature 1: The feature that I identified was a body of water. From the reading the histogram of Layer 4 and seeing the spikes between 12 and 18, this indicated that the map has a large portion of dark features in it. The feature that would match this is the body of water which is located in the southeast part of the map. The band combination that was used to make the feature stand out was Layer 4 for Red, Layer 3 for Green and Layer 2 for Blue. 

Feature 2: The feature that I identified was snowcapped mountains which are located in the northwest part of the map. Since the small spikes in pixel value was 200 through layer 1 through 4 and the large spike had a pixel value between 9 and 11 in layers 5 and 6, this indicated that the feature would lighter in layers 1 through 4 and the darker in layers 5 and 6. I examine the image in multispectral and the area that match this description was the snowcapped mountains. To verify that the mountains had the correct pixel values, the Inquire Tool was utilized. The band combination that was used was Layer 5 for Red, Layer 4 for Green and Layer 3 for Blue. 

Feature 3: Since we are identifying an area of water that are brighter than normal in layers 1 through 3, layer 4 is somewhat brighter, and layers 5 and 6 stay unchanged, the feature that was selected was a water feature which is located in the south central area of the map. I examine this feature in both greyscale and multispectral to identify it. The band combination that I used was True Color which is Layer 1 for Red, Layer 2 for Green and Layer 3 for Blue.