Lab 8: Spectral signature analysis & resource monitoring

Goal
The main purpose of this lab is to gain experience on measuring and interpreting spectral reflectance signature of a large number of surface materials from satellite images. This lab also will help us with basic monitoring skills using band ratio techniques. This information can help distinguish vegetation presence and health.

Methodology

Part 1: Spectral signature analysis
For this section of the lab, we were tasked with collecting spectral signatures of 12 different surface features. these features include the following...

 1. Standing Water

2. Moving water

3. Vegetation

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 (Parking lot)

With this goal in mind, I opened the Eau Claire image from the lab 8 folder to an ERDAS viewer. From here, I digitized 12 locations that I felt matched the surface feature in question. I also added a new signature and examined the highest and lowest spectral reflectance (bands) in micrometers. the reflectance graphs of each feature type can be seen in figure 1.

Figure 1

Part 2: Resource monitoring
In this section of the lab, we were given the task of performing band ratio by implementing the Normalized Difference Vegetation Index (NDVI)  and a ferrous mineral ratio on an image of Eau Claire.


Section 1: Vegetation health monitoring
This section was dedicated to using the NDVI to interpret areas of high and low vegetation. Using the unsupervised raster tool, we were able to create an image on a grey-scale that showed areas different vegetation presence.

Section 2: Monitoring Soil Health
Much like section 1, this section used the unsupervised raster tool to create an image using an indices method to produce an image on a greyscale that shows areas of poor soil health and good soil health.


Results


Part 1:
  The results of part one can be seen in figure 1 in the methodology section. Overall, the most common high reflectance band was the green band and the lowest was the red. There are major differences between the bands of water based features and those of dry features. This is due to the high impact that water's presence has on surface features reflectance. Overall, those with similar make-ups (i.e. most concrete and asphalt features) have similar reflectance graphs which would make sense.


Part 2:
When looking at the presence of vegetation, the map in figure 2 was created to show the location of vegetation. Areas that are dark grey or black have very little vegetation or none for that matter. These areas are near urbanized regions of Eau Claire or is indicative of the presence of water.

Figure 2

However, when looking at the health of soil and therefore vegetation, the map in figure 3 was created. This map shows that the areas of high vegetation and therefor healthy soil is indicated by darker colors.

Figure 3

When comparing both of the maps, it is easy to see where vegetation is most prosperous. The region in the north and east of the Eau Claire shows the most promising land type for dense and healthy vegetation.


Conclusion
Overall, this lab lead us to gain experience measuring and interpreting different spectral reflectance signatures of various surface feature types. Also, we were able to learn the different techniques of band ratios to investigate areas of interest. This information is important when conducting basic identification and can help aid in many land cover/ land type projects.