Remote Sensing - Lab 8

Background and Goals:
  The main goal of this lab is to gain experience in measuring and interpreting spectral reflectance (signatures) of various materials and Earth surface features captured by satellite images.  After collecting spectral signatures from remotely sensed images, they will be graphed and analyzed.  Another goal of this lab is to monitor the health of vegetation and soils using simple band ratio techniques.

Methods:
Part 1: Spectral signature analysis
  Using a Landsat ETM + image that covers the Eau Claire area and other regions of Wisconsin and Minnesota, spectral signatures were collected of the following various Earth surface and near surface features:4.

1.Standing Water
2.Moving water
3.Deciduous forest.
4.Evergreen forest.
5.Riparian vegetation.
6.Crops
7.Dry soil (uncultivated)
8.Moist soil (uncultivated)
9.Rock
10.Asphalt highway
11.Airport runway
12.Concrete surface (bridge, parking lot, or any type of concrete surface)

  These were then all put onto signature mean plot charts in order to compare the reflectance from different bands.  These results can be seen in Figures 3, 4, and 5.

Part 2: Resource monitoring
Section 1: Vegetation health monitoring
  By implementing the normalized difference vegetation index (NDVI) on an image of Eau Claire and Chippewa counties, a simple band ratio was performed.  Figure 1 shows the ratio used for this section.  A map was then created in ArcMap to show the abundance of vegetation present in the counties (Figure 6).

Figure 1

Section 2: Soil health monitoring
  By implementing the ferrous mineral ratio on the same image from Section 1, a simple band ratio was performed.  Figure 2 shows the ratio used for this section. A map was then created in ArcMap to show the spatial distribution of ferrous minerals in the counties (Figure 7).

Figure 2

Results:
Part 1: Spectral signature analysis

Figure 3: The first spectral signature is plotted.

Figure 4: This plot chart shows the differences in reflectance for bands 1-6 for dry and moist soils.

Figure 5: This plot chart shows all the spectral signatures collected in one window.  

Part 2: Resource monitoring

Figure 6: This map shows the result of the NDVI implemented to show vegetation abundance in the counties.

Figure 7: This map shows the result of the ferrous mineral ratio implemented to show the spatial distribution in the counties. 

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

Remote Sensing - Lab 7

Background and Goals
This lab is meant to develop skills in performing key photogrammetric tasks on aerial photographs and satellite images.  By the end of the lab, skills achieved will be: understanding the mathematics behind the calculation of photographic scales, measurement of areas and perimeters of features, and calculating relief displacement.


Methods
Part 1: Scales, measurements, and relief displacement
Section 1: Calculating scale of nearly vertical aerial photographs

Section 2: Measurement of areas of features on aerial photographs

Section 3: Calculating relief displacement from object height

Part 2: Stereoscopy
Section 1: Creation of an anaglyph image with the use of a digital elevation model (DEM)

Section 2: Creation of an anaglyph image with the use of a LiDAR derived digital surface model (DSM)

Part 3: Orthorectification
Section 1: Create a new project

Section 2: Add imagery to the block and define sensor model

Section 3: Activate point measurement tool and collect GCP's

Section 4: Set type and usage, add second image to the block and collect its GCP's

Section 5: Automatic tie point collection, triangulation and ortho resample

Section 6: Viewing the orthorectified images


Results




Sources
National Agriculture Imagery Program (NAIP) images are from United States Department of Agriculture, 2005.  Digital Elevation Model (DEM) for Eau Claire, WI is from United States Department of Agriculture Natural Resources Conservation Service, 2010.  Lidar-derived surface model (DSM) for sections of Eau Claire and Chippewa are from Eau Claire County and Chippewa County governments respectively.  Spot satellite images are from Erdas Imagine, 2009. Digital elevation model (DEM) for Palm Spring, CA is from Erdas Imagine, 2009.   National Aerial Photography Program (NAPP) 2 meter images are from Erdas Imagine, 2009.