Lab 8 Spectral signature analysis & resource monitoring

GEOG 338
Charlie Krueger
Lab 8: Remote Sensing of the Environment

Goal Background:

The goal of this lab for the class was to give us experience doing the tasks such as measuring spectral reflectance and interpret them. This would be done on many different types of materials that the Earth has to offer. The samples would be taken from satellite images of the counties of Eau Claire and Chippewa. The lab will instruct the students on how to collect spectral signatures from the samples, graph the samples in a program, and preform interpretations on them to see if they pass the spectral separability test. Another lesson that will be taught through this lab is the monitoring of the health of vegetation and soils using a band ratio technique. At the conclusion of this lab each student will be ready to analyze spectral signatures from samples that they collected from the Earth’s surface and monitor the health of soils and vegetation

Methods:

In the first part of this lab the class used a landsat ETM+ image to collect and then analyze the spectral signatures of the various Earth surfaces where in Eau Claire and Chippewa counties. First the program Erdas Imagine was opened then the surface image was opened on the screen. The tools that would be used in this section were in the spectral area of Imagine. The drawing tool section was selected then polygon tool was chosen so that an area inside one of the surfaces could be digitized. This mean a section was selected then a small shape was drawn on the surfaces that was to be sampled in the first section this was open water so Lake Wissota was selected for the class. Next in the raster tool area the supervised button was hit and that opened a drop down that showed all the options. The option that was selected for the lab was signature editor which created a new window were all the samples that would be collected would be shown. The class name was then changed to reflect the type of surface that was collected and in this case it was open water. The display mean plot button was selected next and this opened a window that showed a line of where the area that was collected had the highest spectral signatures and the lowest. This process was then continued to include 11 more different types of Earth surfaces. These were moving water, forest, riparian vegetation, crops, urban grass, dry soil, moist soil, rock, asphalt highway, airport runway, concrete surface. All of these were then compared on one of the graphs and shows the difference in all of the surfaces. See results for the graph.

The second part of the lab was performing simple band ration to see the health of vegetation and soils. The vegetation image was loaded into viewer and then the button under raster was selected and this was unsupervised and from that drop down NDVI was chosen. This opened the indices interface and this was where in the input image and output area were selected. The sensor was changed to Landsat 7 Multispectral. After all these changes were made the ok was given and a new image was created from the program that was run. The image was then taken and placed into ArcMap a map making program and the layers were then labeled so that a person on the street could understand the map. The same process was then run on the soil health in the same area and the vegetation in the first process. The only difference in the process was that under function ferrous minerals were selected because that was what was being looked at. Again the image was moved over to ArcMap was analyzing.

Results:

This was the first sample that was taken of the standing water and this is the graph that shows the signature mean of the spectral reflectance.

This is the image of all of the samples of the Earth surfaces on the signature mean plot graph. As someone could see there are many differences in the spectral reflectance of these samples. It was very interesting to see all the different samples next to each other.

This is the map that was created in ArcMap showing the difference in the vegetation in counties of Eau Claire and Chippewa. The map shows that the vegetation is higher in the eastern section were the development of bigger cities is very limited meaning that more vegetation is let grow.

This final image shows how common ferrous minerals are in the sample areas. The image shows that ferrous minerals are most common found in areas that are more developed than others. The area around the city of Eau Claire has more ferrous minerals because they were probably exposed during the development of the city.

Sources:

Satellite image is from Earth Resources Observation and Science Center, United States Geological Survey.

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Lab 7 Remote Sensing of the Environment

GEOG 338
Charlie Krueger
Lab 7: Remote sensing of the Environment

Goal and Background:
The main goal of the lab that was assigned was to improve on the skill of performing important corrections on aerial photos and satellite images. These images can have many issues when being viewed by researchers and by being able to correct these images leads to the improvement of data gathered from this research. This lab was created to strengthen and sharpen skills such as calculation of photographic scales, calculation relief displacement, and measuring the area and perimeter of objects in an images. The lab also brings in new information to the class about performing orthorectification on images taken by satellites and by the end the class will have the information to perform many different photo correcting tasks.

Methods:
The first part of this lab was focused on calculating scale of nearly vertical aerial photos which was covered in lecture and had been discussed prior to the lab. There were formulas that were need to solve each one of these problems plus the information that was given in the problem. On both of the problems a measurement on the computer screen had to be made to get info to solve the problem. This was a concern because of the fact that the screen was difficult to measure and could give different results if a different person were to measure it. In this same section the program ERDAS Imagine was used to find the perimeter and area of a lagoon taken for a satellite image. The program used a measurement tool and all that was done after that was carefully going around the edge and plotting point and then the answer was given after the whole lagoon had been surveyed.

The second part of this lab was stereoscopy which is the generation of a three dimensional image using an elevation model. The program that was used to create these 3D images was the ERDAS Image terrain tool Anaglyph which took the two images that were selected in the lab and ran a program over them creating the image. This was done twice in this section with the result from the second run program creating a very interesting 3D image. The 3D could only be seen while wearing blue and red lensed glasses or 3D glasses.

The last section of the lab was the orthorectification part which was the largest part of the lab and by far the most strenuous. This process takes two images that are close to each other in location but that do not fit together and runs programs so that it makes one smooth image. To begin with the toolbox button was selected and then Imagine Photogrammetry was selected and that brought up a whole new dialog box. The model setup was done by selecting polynomial based push broom and then SPOT Push broom. The coordinate system was then corrected was that the final images would line up with one and other in the same system. Next the images are added in the add frame icon, with this image on the screen the show and edit frame properties icon was selected which when looked and confirmed the image could then start to be edited. The Start point measurement tool was selected and the process of selecting ground control point began. In total 12 ground control points were selected between the reference image and the image trying to be corrected. The reference image was there to make sure that the positions of the ground control points were correct and the image would not be slanted in a strange way. After these points another reference image was added and another six ground control points were added. This second image was added to have another reference image and make the final image even more accurate. Next the reset vertical reference source icon was selected and this was allowed the Z value to be given to the images. The Z value would be the height in this image and would be given from the DEM palm_springs_dem.img. Finally, after a long process the Edit- Triangulation Properties icon was selected and there were many items changed in here because of the images specifics used in the program. The triangulation was run after this two images were selected to be made from this program and then these were brought to the viewer and held the end results.

Results:
Here is the image created from the Stereoscopy process. This image was created by a computer program that was given specific images that would create a 3D image. The process was simple because the lab laid out the specific details of how to create the image.

Stereoscopy Image

This second image is from the orthorectification process of the lab and it can be seen that there is a small black line that run in between the images. This goes away when the user zooms in using the Imagine program. This process was very detailed oriented and took a long process because of the selecting of the ground control points.

Orthorectification Image

Sources:
National Agriculture Imagery Program (NAIP) images are from United States Department of Agriculture, 2005.
Digital Elevation Model (DEM) for Eau Claire, WI is from United States Department of Agriculture Natural Resources Conservation Service, 2010.
Lidar-derived surface model (DSM) for sections of Eau Claire and Chippewa are from Eau Claire County and Chippewa County governments respectively.
Spot satellite images are from Erdas Imagine, 2009.
Digital elevation model (DEM) for Palm Spring, CA is from Erdas Imagine, 2009.
National Aerial Photography Program (NAPP) 2 meter images are from Erdas Imagine, 2009.