Lab 8: Spectral Signature Analysis and Resource Monitoring

Introduction and Goals:

The purpose of this lab was to collect and examine the different signatures created from different materials, and to preform resource monitoring found within an image. Within this lab, there were two sections that focused on two different goals. They were:

To collect and analyze twelve different spectral signatures.
Preform NDVI, and ferrous mineral tests to monitor resource health.

Methods:

Before any steps were started, data management was completed by the creation of a folder that would be specifically used for the purpose of maintaining data, additional sub-folders, and any outputted images.

Part 1: Spectral Signature Analysis

The image used in this lab is a Landstat ETM+ image dubbed eau_claire_2000.img, and covers a larger portion of both Wisconsin and Minnesota. This image is used to locate the City of Eau Claire, which was used for spectral signature collection.

To do so, the first step was to upload the image into Erdas Imagine. Then within the drawing tab, the polygon tool was used to digitize the material we wanted to collect. For this first signature collected, we looked at standing water within Lake Wissota. In total there were twelve signatures collected. They were:

Standing Water
Running Water
Forest
Riparian Vegetation
Crops
Urban grass
Dry Soil
Moist Soil
Rock
Highway
Airport Runway
Concrete Surface

To record the materials' spectral signature, the raster tab was clicked, then the supervised function was accessed, and finally the subcategory, "signature editor" was entered into. Within the table that appears, the new signature was added in, and then displayed. This process was repeated for each material that was listed.

Part 2: Resource Monitoring

Section 1:

Within this section we looked at vegetation health through normalized difference vegetation index (NDVI). The equation for this tool is featured in figure 1.

Figure 1: The equation used for NDVI

Again within Erdas, the image ec_cpw_2000.img was inputted into the program. Then the raster tab was clicked. Within it, the NDVI subcategory was access within "unsupervised". Once this is done, a table appeared, and the image was inputted, the sensor was changed to "landstat 7 multispectral" and function to "NDVI". All other defaults were accepted and the tool, ran. The resulting image was brought into ArcMap and a final map was created from it.

Section 2:

This section of part 2, looked at soil health by monitoring ferrous material within the image. This section utilized the same image as section 1. Figure 2 is the equation used to find ferrous minerals.

Figure 2: The equation for ferrous mineral content

Again, the raster tab was accessed and "unsupervised" clicked. However, this time the subcategory "Indices" was used. Within the table that appears, the AOI is inputted, the sensor is again set to "landstat 7 multispectral" and fuction is set to "ferrous mineral". All other defaults are accepted, and the tool is ran. Again the resulting image was added in ArcMap to create a final map.

Results: