Goal:
The goal of this lab was to gather and interpret spectral reflectance signatures of 12 surface materials using a satellite image of Eau Claire. These reflectance signatures graphed, compared and analyzed. Also different band ratio techniques were used to analyze and map vegetation and ferrous soil in the Eau Claire and Chippewa counties.
Methods:
Part 1: Spectral Signature Analysis
The first task involved plotting the spectral reflectance of twelve common surfaces using a Landsat ETM+ image of the Eau Claire area. The image was brought into Erdas Imagine and a polygon was created over each of the following surfaces:
1. Standing Water
2. Moving water
3. Forest
4. Riparian vegetation.
5. Crops
6. Urban Grass
7. Dry soil (uncultivated)
8. Moist soil (uncultivated)
9. Rock
10. Asphalt highway
11. Airport runway
12. Concrete surface
After each polygon, the selection was brought into Signature Editor where it was labeled and then plotted so that the graph displayed the amount of reflectance there was at each of the six bands. Many observations were made in each individual graph of the different surface. For example, vegetation displayed high reflectance in the infrared bands, but not so much in the visible bands due to the fact the vegetation uses the visible band in photosynthesis and the infrared band is harmful to important proteins in the plant. The variance between dry soil and moist soil was also observed and it was noted that the moist soil displayed less reflectance due to the presence of water in the soil (Figure 1.) All the signatures were graphed together as well (Figure 2.)
Part 2: Resource Monitoring
In section one the vegetation of Eau Claire and Chippewa county were analyzed and mapped by using the normalized difference vegetation index (NDVI). To bring out the vegetation in an image, a formula is used:
NDVI=NIR-Red/NIR+Red
NIR and Red refer to the near infrared and red bands of the image. The NDVI tool in Erdas Imagine was used on a satellite image of the Eau Claire/Chippewa county area. The resulting NDVI map can be found in the results area (Figure 3.)
In the second section, the same process as in the first section was repeated, except the Indices tool was used to observe ferrous soils in the Eau Claire/Chippewa area. This process uses a different formula to highlight the ferrous soils in an image:
Ferrous mineral=MIR/NIR
A map of ferrous soils (Figure 4.) can be found in the results section.
Results:
Figure 1. shows the reflectance of dry soil and moist soil. The moist soil has less reflectance, because it contains water, which readily absorbs electromagnetic energy.
Figure 1.
Figure 2. displays the reflectance of all twelve surfaces observed in the lab.
Figure 2.
Figure 3. is a map of the vegetation in the Eau Claire/Chippewa area. The more intense the color green is, the more dense the vegetation in that area.
Figure 3.
Figure 4. is a map of the distribution of ferrous soil in the Eau Claire/Chippewa area. The lighter the gray, the greater the presence of ferrous soils.
Figure 4.
Sources:
Satellite image is from Earth Resources Observation and Science Center, United States Geological Survey.
Goal:
The objective of this lab was to calculate photographic scales, measure the area and perimeter of a feature and calculate relief displacement, as well as understand stereoscopy and perform orthorectification on satellite images.
Method:
Part One:
In the first section the scale of an aerial photograph of a section of the city of Eau Claire was calculated from given information and using a ruler to manually measure features on the screen. Every variable was converted to inches. The work and results of this section can be found in the “results” section of this post. Another aerial photograph of the city of Eau Claire was calculated, but this photograph was taken from a higher altitude. Every variable was given and converted to feet and the formula: S=f/(H-h) was used to find the scale.
In the second section the “measure” tool in Erdas Imagine was used to find the area and perimeter of a lagoon in Eau Claire. The polygon tool was used to measure area by tracing the perimeter of the lagoon. The area was 35.5957 hectares (92.9 acres). The polyline tool was used to trace the perimeter. The perimeter amounted to 4,100.25 meters (2.55 miles).
In the third section an image of the upper campus of the University of Wisconsin – Eau Claire was analyzed to determine relief displacement. Using a smoke stack that was altered due to the photogrammetric error the relief displacement was calculated in inches. A ruler was used to find the height of the smoke stack and its distance from the principal point. The rest of the variables were given. The answers can be found in the results section of this post.
Part Two:
In this part of the lab a 3D image was created from an elevation model using the Anaglyph tool in Erdas Imagine. A 1-meter spatial resolution image of the City of Eau Claire was used along with a DEM version of the same image to create an anaglyph version of the image, which was saved in a personal stereoscopy folder. Next a digital surface model was combined with the original City of Eau Claire to create another 3D image using the anaglyph tool, but this anaglyph proved to better represent surface features than the DEM anaglyph.
Part Three:
This part of the lab utilized Erdas Imagine Lecia Photogrammetric Suite (LPS) to orthorectify images and create a planimetrically accurate orthoimage of a part of Palm Springs, California. In LPS a new block file was created for this project and it was set up using a polynomial-based pushbroom geometric model and the image spot_pan.img of Palm Springs, CA was brought in. The horizontal reference coordinate system used was UTM Zone 11 with using NAD27 (CONUS) datum and the Clarke 1866 spheroid. The SPOT PAN was filled out in the Sensor Information field to indicate that an image taken by the SPOT satellite was used. Next, the point measurement tool was opened, which is where all of the ground control points (GCP) were placed.
Before placing any GCPS on the spot_pan image, a reference image (xs_ortho) was brought in. Below the two images was a box where cells containing information about the GCPs would appear. Finally, using the Create Point tool, a GCP was placed in the reference image at certain point and then another one in the spot_pan image at the exact same spot. In total 9 GCPs were placed using xs_ortho as the reference image. The exact coordinates of where the GCPs needed to be in both images were provided in the lab instructions and were manually entered into the box where the GCP information cells were. For the last two GCPs NAPP_2m-ortho.img was the reference image. Once all the GCPs were placed the vertical reference source had to be set up. For this, the palm_springs_dem image was used to supply the height information of this orthorectified image. After that, the Type column for all of the GCPs was set as full and the usage column was set as Control.
Next, a second image was added to the block (spot_panb). In LPS seven GCPs were added to spot_panb in the exact same spot as the corresponding GCPs in spot_pan. Looking at the home screen of LPS the two images were overlayed and the shared GCPs were shown. The automatic tie point tool places tie points to create a more accurate placement of the overlayed image (spot_panb) onto spot_pan. 40 tie points were used when running the tool. After the tie points were created triangulation had to be performed to establish mathematical relationships between images, the sensor and the ground. For this the ground point type was set to same weighted values and the X, Y, Z coordinates for set to 15 to ensure that the GCPs were accurate to about 15 meters. The triangulation summary can be found in the results portion of the post.
Finally, the ortho resampling process was started. The resampling method that was used was bilinear interpolation and the output was labeled orthospot_panb. The ortho resampling process was run and the result can be found in the results portion of the post.
Results:
Part One:
This is the work for finding the scale of the first image of Eau Claire.
1. Actual measurement: 8,822.47 ft.
Ruler Measurement: 2.75 inches.
8,822.47 ft*12=105,869.64 inches.
2.75 inches on the screen represents 105,869.64 inches.
So 105,869.64/2.75= 38,498.05
Scale is 1:38,498
This is the work for the second image of Eau Claire where the formula used was S=f/(H-h) and all of the variables were given.
1. Formula: S= f/(H-h)
S=scale
f=152mm=.498688ft
H=20,000ft
h=796ft
S=.498688/(20,000-796)
S=.498688/19,204
S= 1:38,509
This is the work for finding the relief displacement using the smoke stack on upper campus of UW - Eau Claire.
1. Relief displacement=d=hxr/H
Height of object in image= .5 inches
Scale=1:3,209
Height of object=1,604.5 inches
d=1,604.5inchesx11.5inches/47,760 inches
d=.386 inches
The top of the tower should be moved .386 inches towards the principal point.
Part Three:
Below is the final product of placing all the GCPs, adding tie points, triangulation and ortho processing.
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
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