Lab 6: Geometric Correction

Goal

The name of this lab is "Geometric Correction" and our main goal was to fix the distortion between two maps that are representing the same image and creating a new map with less to no distortion. During this lab we learned a few new skills while doing it, for instance we learned two major types of geometric correction, one was the pre-processing of activities prior to the extraction of the biophysical and sociocultural information from satellite images. In order to complete these tasks and to learn these skill sets, we needed to use Erdas Imagine to help us complete each of the tasks that were represented to us in the lab. 

Methodology/Results 

The first step of the lab was to upload two maps that represented the same location and try to fix the distortion for one of them so than both maps would match exactly. In order to do this we had to upload both maps into Erdas, and than find the control points that were made on the map originally, the points that were causing the distortion in the first place. Once we deleted all of the control points it was our job to make our own and try to get the points to match correctly in each map so than the points would be in the exact same location. Once we created three control points and attempt to match them up every point after that would automatically match up because the polynomial order is at 1 meaning that there only needs to be three points for the points to start matching up by themselves. After we got our four points on their our goal was to get the Root Mean Square (RMS) error down to 2.0 or lower, the lower the RMS was the less distortion we would have in the image. Below is an image of the maps known as figure 1 with the four control points on it and with the RMS lower than 2.0 or is this case at 1.5757.

Figure 1

The next step for the lab was the same objective as the first, compare two images that are representing the same area and try to find and get rid of the distortion by using Erdas Imagine. This time its a little more difficult though because we were asked to change the polynomial order from 1 to 3 which means that we need to use more control points before they automatically get added to the corresponding map. In this case we had to add ten different control points all over the map and try our best to match the points from one map to the other before they would automatically match. After we added the ten control points we were asked to add two more and then try to get the RMS error below 1.0. In order to do this we needed to change the location of almost every single control point ever so slightly so than the RMS would read below 1.0. Below is an image known as figure 2 and this figure represents the two new maps being compared, with 12 control points and with an RMS of 0.7137. 

Figure 2

This lab was very helpful is finding out different ways on Erdas to remove distortion from images or at the very least get rid of some of the distortion. I thought of this lab as a great learning experience, and plan to use all of the skills picked up this lab in the future.

Lab 5 Remote Sensing

Goals

The goal of this lab was to teach the students how to properly build a data structure by using Lidar and also properly process data in Lidar. There were a few specific objectives that we were supposed to keep in mind while going through this lab and these included; processing and retrieval of various surface and terrain models, and processing and creation of intensity image and other derivative products from point cloud. 

Methodology/Results

In order to complete this lab we had to apply ourselves in different ways that we haven't tried yet for instance we had to use different aspects of both Erdas Imagine and ArcMap in this lab in ways we haven't. First we had to create a LAS data set using ArcCatalog, this was the first step and we had to create this LAS data set as a Point Cloud in order to access different lidar point clout tiles. After we created the LAS data set we had to add all of the different .las files that we were given to it so than the data set would actually contain some data. We then had to explore all of the properties of the LAS data set so than we would know everything that was in it and have a better understanding of what we were trying to do for this lab. The data that we were using was representing the city of Eau Claire, we had to use this data to find out different max and min values for both X, Y and Z. In order to do this we would use the statistics tab in ArcCatalog which would give us all of the information that we needed to complete this step. After we had finished up fine tuning all of the data on ArcCatalog it was time to move the LAS data set over to ArcMap for the remainder of the lab. We had to use multiple tools during this lab, these tools included; the Identify tool, the LAS Dataset Tool bar, and many more. The LAS Dataset Tool bar helped us with a lot of different steps in this lab, it helped us look at the map in many different forms, for example we looked at the map where it specifically defined all of the areas with elevation, slope and contour which was very helpful in understanding all of the different things that ArcMap can do. The next step was to look at the layer properties of the map and change around the different classification codes and returns which would present the layout of the map in different ways. For example some would focus more the ground level of the area in question and other settings would focus on non ground areas of the map such as rivers and mountains. 

Once we got through all of those steps the next step was for us to change the LAS data set into a raster so than we could get different aspects of the map which would lead to us finding out different information about the surrounding area of Eau Claire. The first raster that we created we used 3D Analyst to help us perform the task correctly and once we had the raster created we wanted to use another tool on ArcMap called Hillshade which would help define the hills from the rest of the map. If you look at the image below you will see the first Hillshade map that we created and how it defines the hills or areas with major elevation over the rest of the map. 

As you can see in the map above that the area that really pops out and is easy to see are the hills because of the Hillshade tool that was used earlier in the lab. The next step of the lab was to do the same exact thing but with different properties being selected while changing it from an LAS data set to a raster. Then since we couldn't really see the map too clearly we had to open the map in Erdas Imagine so than we could get a more clear look at the map. Below is the map that was moved to Erdas and notice that the main visible part of the map are the rivers and man-made features. 

Overall this lab was very helpful in learning different tools and aspects of ArcCatalog, ArcMap and Erdas Imagine and discovering what they can do and being able to use these tools later in life. The lab was challenging but a good learning experience.