The main goal of this lab was to introduce the concept of spectral reflectance and perform basic functions for the interpretation of spectral signatures. This included collecting spectral signatures for a dozen different surface features, graphing them, and analyzing them. Also, spectral analysis would be used for the classification and analysis of vegetation health and ferrous soil concentration.
Methods
Part 1: Spectral Signature Aanlysis
First, the eau_claire_200.img Landsat ETM+ image was brought into a Erdas Imagine viwer. Then, using the drawing tool, a polygon was drawn around a lake located in the image. Then, using the Signature Editor tool, a new Signature form was created from the AOI of the drawn polygon. This signature was labeled "Standing water". This process was repeated for eleven more surface materials: moving water, forest, riparian vegetation, crops, urban grass, dry soil (uncultivated), moist soil (uncultivated), rock, asphalt highway, airport runway, concrete surface (bridge, parking lot, or any type of concrete surface).
Part 2: Resource Monitoring
In this section, simple band ratio was used to monitor and classic both vegetation and soils. The Raster Unsupervised tool "NDVI" was first opened in Erdas. The image ec_cpw_2000.img was input into the the Indices interface. The sensor was set to Landsat 7 Mulispectral and the function was set to NDVI. The process was then run. The image was then used to create a visually appealing map illustrating vegetation in the image area.
A similar process was completed again, this time for the ferrous mineral content of soils of the ec_cpw_2000.img image. The Raster Unsupervised tool Indices was launched, with the ec_cpw_2000.img image being input into the tool. The sensor was set to Landsat 7 Multispectral and the function set to "Ferrous Minerals". The tool was then run, and the output image used to cartographically pleasing map.
Results
Part 1
The resulting signature mean plots, taken from the twelve created spectral signature, show that features made up of similar materials seem to have similar spectral signatures. Man made surfaces have similar reflectance, vegetation types share similarities, exposed soils are similar. Several of the surface feature types, like exposed rock and cropland, are different from most other signature types.
Based on the resulting image, the majority of health vegetation lies to the eastern half of the counties, or lines the very edge of the river. This is likely because the west is more densely populated than the east, and it is difficult to populated the area directly on the edge of the river.
Based on data taken from the map, the densest quantity of ferrous minerals lies to the direct west of the Chippewa river. This is likely what used to be the floodplain of the Chippewa River, and the area least covered by dense vegetation, exposing the soil.
Sources
Earth Resources Observation and Science Center. In United States Geological
Survey. Retrieved 12/14/2016, from http://eros.usgs.gov/usa
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