The main goal of this lab is to gain experience on the measurement and interpretation of spectral reluctance of Earth surfaces and near surface materials captured by satellite images. We were tasked to collect spectral signatures from sensed images and using ERDAS Imagining software we were able to graph and preform analysis on these images.
Data:
that data provided to us in the lab folder was a Landsat ETM+ image that covers Eau Claire and other regions in Wisconsin and Minnesota. this was used to collect and analyze specific signatures of various Earth surfaces and near surface features.
Methods:
To collect the spectral reflectance of the images the Landsat ETM+ image was used. using this data we were to collect reflectance signatures from 12 different sources found on earth. these are the 12 signatures:
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
The first signature that we collected was from Lake Wissota. In order to collect a signature we needed to digitize an area around. To do this we used the polygon digitizing tool. next we clicked on Raster processing tools and used the signature editor tool. using the new signature from the area of interest we created a new class and changed it to standing water. when we used the display mean plot window we were able to show the spectral reflectance band.
Standing Water
After this band was completed we were able to collect the other AOI by using the same method multiple times until we completed all 12 signatures.
Conclusions
Collecting all the bands together created an interesting view of the captures. The collected captures show which type of signature is the highest. in this case it was the dry soil signature that reflected the most. while standing water reflected the least. This is unsurprising since the soil reflects back energy similar to a mirror due to the lack of moisture in the soil. The water however absorbs a lot of the energy due to water being a primary absorption band.
All Captures on same Signature Mean Plot
