Lab 7: Photogrammetry

Lab 7: Photogrammetry

Goal and Background

The main goal of this lab is to develop skills in photogrammetric tasks on aerial photos and satellite images. Specifically the goal is to understand the mathematics behind calculating photographic scales, measuring areas and perimeters of features, and calculating relief displacement. In addition the lab is intended to introduce stereoscopy and performing orthorectification on satellite images. After the completion of this lab we will have the ability to perform diverse photogrammetric tasks.

 There are three parts to this lab: part 1-scales, measurements and relief displacement, part 2-stereoscopy, and part 3- orthorectification.

Part 1, Section 1: Calculating scale of nearly vertical aerial photographs.
Part 1, section 2: Measuring areas of features on a photograph.
Part 1, section 3: Calculating relief displacement from object height.
Part 2, Section 1: Created an anaglyph image with the use of a Digital Elevation Model (DEM).
Part 2, Section 2: Created an anaglyph image through the use of a LiDar derived Digital Surface Model (DSM).
Part 3: An Orthorectification was performed between various images to create a planimetrically true orthoimage.

Methods

Part 1: Scales, measurements and relief displacement 
Section 1: In this first section of part 1 the scale of a nearly vertical image was calculated. This was done by measuring a distance between point a and b on the image with a ruler, then determining the value of the distance in real life which was given to us. To determine the scale the distance in real life is divided by the distance on the image. the distance given to us of the actual feature was 8822.47 feet, and since the image on the computer was measured in inches, 8822.47 ft was converted into inches by multiplying by 12 this means the area in real life was 105869.64 inches. Then when 105869.64 is divided by 2.75 that equals 38498.051. Therefore the scale is 1:38498.051

Next the scale of an image was calculated through the use of a focal length, height above sealevel, and height of the surface of the image above sea level. This used the equation focal length/(height of aircraft-height of surface) then set that equal to 1/x to determine the scale. with the given number converted to feet, the equation looked like:  (.4987/(20000-796))=1/x   x(scale)=38508.1211
1:38508.1211.

Section 2: In this section we determined how to calculate areas of features in an image by utilizing the measuring tool in ERDAS imagine and digitizing around the image, to see what the area and perimeter is.

Section 3: In this section relief displacement was calculated from the height of an object. To do this the relief displacement equation was used which looks like this:
d=(h*r)/H

d=relief displacement (0.23")
h=height of object (real world) (1283.6")
r=radial distance of displayed object (8.5)
H=height of camera above local datum (47760)

Part 2: Steroscopy
Section 1: In this section a Digital Elevation Model (DEM) was converted to an anaglyph through the use of Erdas Imagine.
Section 2: In this section a LiDar derived Digital Surface Model (DSM) was converted into an anaglyph through the use of Erdas Imagine.

Part 3: Orthorectification
This portion of the lab required the most time. An orthorectified image will be created by obtaining GCP points between the use of two ortho images and an orthorectified aerial photo. In doing this images need to be selected to represent different axis horizontal (x,y) or vertical (z). the reason already orthorectified imagery is used to orthorectify the images is because they all ready have a higher level of accuracy compared to non-orthorectified imagery.
First spot_pan.img and spot_panb.img were orthorectified to correct the spatial errors of having no reference system.

Then 10 GCP points were collected between the two images to set part of the horizontal reference source.

Then 2 more GCP's were collected from the image NAPP_2m-ortho.img to utilize a different scale and resolution.

Then GCPs were collected in spot_panb based on the 12 previously collected GCPs. however only 7 GCPs overlapped into that image so all 12 were not needed.

Then finally the triangulation process was performed to finalize the orthorectification, here the tie points in the overlap ares were measured and aligned.
Results
Part 1: Scales, measurements and relief displacement 
Section 1
The results of determining the scale of the photo Eau Claire_West-se.jpg (Figure 1) is 1:38498.051. 
The results of determining relief displacement on the second image ec_west-se.img (Figure 2) is 1:38508.1211

Section 2:

The image ec_west-se.img (Figure 3)  shows an x over a lake, and this is the area that is to be digitized with the measuring tool, and when this was done, the area= 92.8579 acres. The perimeter = 2.5687 miles

Section 3:
The ec_west-se.image (Figure 4) relief displacement came out to be 0.23"
Part 2: Stereoscopy
Section 1: The anaglyph derived from the DEM created a 3d image of Eau Claire (Figure 5). Except the image is not a smooth transition between elevation changes like how it occurs in real life, the image is like steps going up or down in elevation change.
Figure5: this is a zoomed in DEM anaglyph of Eau Claire where you can see the blocky 3 dimensional features with the use of polaroid glasses.

Section 2: The anaglyph derived from the DSM Lidar Derived image of Eau Claire (Figure 6), shows a better 3 dimensional image where elevation change has a smoother transition rather than a blocky look like in the DEM anaglyph
Figure 6: This is a zoomed in portion of the DSM anaglyph of Eau Claire and with the use of polaroid glasses the 3 dimensional features of the land surface appear more smooth and natural.

 Part 3: Orthorectification
Here is the orthorectified image zoomed all the way out the seem is visible (Figure7). And zoomed in over the seam (figure8) the seem is slightly visible, but lines up very nicely..


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. 

Comments

Post a Comment

Popular posts from this blog

Lab 8 Spectral Signature analysis and Resource Monitoring

Image
Lab 8 Spectral Signature analysis and Resource Monitoring Goal The main goal of this lab is to interpret spectral reflectance of various Earth surfaces and near the earths surface from satellite images, and to perform monitoring of surface features. In this lab we will collect spectral signatures from remotely sensed images, and create maps showing Different spectral signatures. Methods Part 1: Spectral Signature Analysis First spectral signatures were gathered by finding areas in the image that contained a surface feature we were looking for, and an area of interest was put in the area, and the spectral signature was recorded. This was done for 12 features some of them being Crops, Dry and Wet soil, standing water, moving water, and some more. Part 2: Resource Monitoring Section 1: Vegetation and Health Monitoring IN this section of part 2 vegetation was the focus, and a NDVI or normalized difference vegetation index was produced for Eau Claire and Chippewa Counties. This in...
Read more

Lab-5 LiDAR Remote Sensing

Image
Goal and Background The goal of this lab is to gain basic LiDAR skills through the use of ArcGIS. Some Specific goals were processing and retrieving surface and terrain models. The creation of an intensity image and other point cloud images. The LiDAR data used is in LAS file format which is easily manipulated through the use of ArcGIS. Methods Part 1: Point cloud visualization in Erdas Imagine The first part of this lab Erdas Imagine was used to input point clouds and visualize the LiDAR imagery. This was done by opening each individual LiDAR point cloud file in .las format and this gives the ability to view the LiDar image as a whole (Figure 1).  Figure 1: This image shows the importing process of LAS files into Erdas Imagine.  Next we brought these same files into ArcMap where it is easier to manipulate Lidar imagery. This was done by creating an LAS data file where LAS point cloud imagery was added of Eau Claire county. This data appears in a bunch of tile...
Read more