Lab 8 Spectral Signature analysis and Resource Monitoring

Lab 8 Spectral Signature analysis and Resource Monitoring
Goal
The main goal of this lab is to interpret spectral reflectance of various Earth surfaces and near the earths surface from satellite images, and to perform monitoring of surface features. In this lab we will collect spectral signatures from remotely sensed images, and create maps showing Different spectral signatures.

Methods
Part 1: Spectral Signature Analysis
First spectral signatures were gathered by finding areas in the image that contained a surface feature we were looking for, and an area of interest was put in the area, and the spectral signature was recorded. This was done for 12 features some of them being Crops, Dry and Wet soil, standing water, moving water, and some more.

Part 2: Resource Monitoring
Section 1: Vegetation and Health Monitoring
IN this section of part 2 vegetation was the focus, and a NDVI or normalized difference vegetation index was produced for Eau Claire and Chippewa Counties. This index is created in Erdas, and utilizes the equation NDVI= ((NIR-Red)/(NIR+Red)). This tool and equation produces an image where vegetation density is shown clearer, Erdas shows high density vegetation areas in white, and black being no vegetation.

Section 2: Soil Health Monitoring
In this section the same process was done except for minerals, and Indices was used instead of NDVI. This tool takes the image of Eau Claire and Chippewa Counties, and produces a shaded image that symbolizes High Ferrous minerals down to no exposed soil, and vegetation. this is done through the equation Ferrous mineral=(MIR/NIR). This allows the reflectivity of different soils to become apparent and produce a shaded image.


Results
Part 1: Spectral Signature Analysis.
The results for this section gave a chart showing the reflectivity of each feature (Figure 1).

Figure 1: Spectral Signature chart showing all 12 features in part 1.

Part 2: Resource Monitoring
Section 1: Vegetation and Health Monitoring
A map showing vegetation Density based on spectral signatures was produced (Figure 2). Dark Green areas are areas with high density vegetation, and Red is areas made up of mostly water.
Figure 2: This map shows the different areas in Eau Claire and Chippewa County that have dense and less dense areas of vegetation.
Section 2: Soil Health Monitoring
An Image showing places with high levels of Ferris Minerals to Low and no levels of ferrous minerals was created (Figure 3).


Figure 3: This map shows where minerals are present, and where they are not.

Sources
Satellite image is from Earth Resources Observation and Science Center, United States Geological Survey.



Comments

Post a Comment

Popular posts from this blog

Lab 7: Photogrammetry

Image
Lab 7: Photogrammetry Goal and Background The main goal of this lab is to develop skills in photogrammetric tasks on aerial photos and satellite images. Specifically the goal is to understand the mathematics behind calculating photographic scales, measuring areas and perimeters of features, and calculating relief displacement. In addition the lab is intended to introduce stereoscopy and performing orthorectification on satellite images. After the completion of this lab we will have the ability to perform diverse photogrammetric tasks. There are three parts to this lab: part 1-scales, measurements and relief displacement, part 2-stereoscopy, and part 3- orthorectification. Part 1, Section 1: Calculating scale of nearly vertical aerial photographs. Part 1, section 2: Measuring areas of features on a photograph. Part 1, section 3: Calculating relief displacement from object height. Part 2, Section 1: Created an anaglyph image with the use of a Digital Elevation Model (DEM). ...
Read more

Lab-5 LiDAR Remote Sensing

Image
Goal and Background The goal of this lab is to gain basic LiDAR skills through the use of ArcGIS. Some Specific goals were processing and retrieving surface and terrain models. The creation of an intensity image and other point cloud images. The LiDAR data used is in LAS file format which is easily manipulated through the use of ArcGIS. Methods Part 1: Point cloud visualization in Erdas Imagine The first part of this lab Erdas Imagine was used to input point clouds and visualize the LiDAR imagery. This was done by opening each individual LiDAR point cloud file in .las format and this gives the ability to view the LiDar image as a whole (Figure 1).  Figure 1: This image shows the importing process of LAS files into Erdas Imagine.  Next we brought these same files into ArcMap where it is easier to manipulate Lidar imagery. This was done by creating an LAS data file where LAS point cloud imagery was added of Eau Claire county. This data appears in a bunch of tile...
Read more