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Lab 8

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Goal and Background           The purpose of Lab 8 was to learn the prerequisites for correct image classification, that is, to gain experience in measuring and interpreting the spectral signatures of various Earth surfaces an materials. Specifically, spectral signatures will be collected, graphed, and analyzed whether or not they have spectral separability. Methods           In Erdas Imagine, bring in the 2000 Landsat ETM+ of Eau Claire, WI into the viewer. Spectral signatures are going to be collected from twelve different materials. 1. Standing Water (Figure 1) 2. Moving Water (Figure 2) 3. Deciduous Forest (Figure 3) 4. Evergreen Forest (Figure 4) 5. Riparian Vegetation (Figure 5) 6. Crops (Figure 6) 7. Dry Soil (uncultivated) (Figure 7) 8. Moist Soil (uncultivated) (Figure 8) 9. Rock (Figure 9) 10. Asphalt Highway (Figure 10) 11. Airport Runway (Figure 11) 12. Concrete Surface (Figure 12) ...
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Lab 7

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Goal and Background           The objective for Lab 7 is to offer an understanding and a practice of important photogrammetric tasks on aerial photographs and satellite images. Certain tasks include calculating photographic scales, measuring the areas and perimeters of features, and calculating relief displacement. Lastly, concepts such as stereoscopy and orthorectification will be introduced and implemented with aerial photographs and satellite images. Methods           Lab 7 began with viewing a JPEG of an aerial photograph of the western part of Eau Claire county, which showed a portion of Interstate 94. Measuring the segment AB on the screen, the photo distance is approximately 2.5 inches. The true ground distance of that distance is 8822.47 feet. To calculate the scale of the image, divide the photo distance from the ground distance (S = PD/GD). The image's scale is approximately 1":42,347".         ...
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Lab 6

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Goal and Background           Before a satellite image is analyzed, a number of preprocessing activities must be performed first to prepare the image for accurate information extraction. For Lab 6, students were introduced to the preprocessing exercise known as geometric correction. The two geometric correction processes introduced in this lab are image-to-map rectification and image-to-image rectification.  Methods           In Erdas Imagine, display the Chicago USGS 7.5 minutes Digital Raster Graphic and the 2000 Chicago satellite image from the Lab 6 folder in two separate viewers. The satellite image needs to be geometrically corrected based on the accurate DRG in a image-to-map rectification. With the satellite image activated, click on Control Points in the Multispectral tab. Select Polynomial in the Set Geometric window. Accept Image Layer (New View) as the default in the GCP Tool Reference Setup window. Next, navigate...
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Lab 5

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Goal and Background           The purpose of Lab 5 was to be introduced basic LiDAR data structure and processing, such as processing and retrieving surface models and digital terrain models (DTM) and processing and creating intensity images and other derivative products from a point cloud. The LiDAR data in this lab is in LAS format. It's important for a student to have experience in working with LiDAR data, as its role and potential is only growing in the remote sensing world.  Methods           For the first part of the lab, bring in the .las files in the Lab 5 folder into Erdas Imagine viewer. Change File Type to LAS as Point Cloud so the las. files can be retrieved from the Select Files window. A warning will pop up about the layer not having level of detail (statistics). Uncheck Always Ask and click Ok as this will be computed later. It's essential that LAS data that is being worked on have Metadata and a Tile Index. Th...
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Lab 4

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Goal and Background           The objective of Lab 4 was to introduce students to numerous functions and processes in Erdas Imagine that will build up skills in image processing. The particular processes in Lab 4 include: two methods of delineating a study area from a satellite image, optimizing spatial resolution through pan-sharpening, a radiometric enhancement technique, linking a satellite image to Google Earth, resampling methods, mosaicking images, and binary change detection through simple graphical modeling. Subsequently, students are better prepared for image processing, enhancement, and interpretation with experience with these techniques and methods. Methods           The first skill introduced was subsetting images in order to focus on an area of interest. One method was using an Inquire Box - a simple, but limiting method because areas of interest are often not simple square or rectangle. Using an image of Eau Claire ...
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