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I will post my assignments from GIS4035/GIS4035L in Photo Interpretation and Remote Sensing.

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Module 3-Intro to ERDAS Imagine and Digital Data

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   Hi Everyone!  Module 3 focuses on properties of EMR and the basics of ERDAS Imagine.  Lab 3 consisted of using ERDAS Imagine to analyze remote sensing digital data. The map above is a land classification subset from a larger AVHRR image. First I worked in the ERDAS Imagine software to view the image, then convert it to a classified map export in ArcGIS.
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Module 5-Supervised and Unsupervised Classification

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   Hi Everyone!  Module 4 focuses on an overview of spectral classification and unsupervised/supervised classification methods. Supervised classification is characterized by matching pixels, whereas unsupervised classification involves manual processing and predetermined pixel values. Lab 4 used ERDAS Imagine to classify digital imagery (unsupervised and supervised ) and ArcGIS to make layouts.   The map above displays a band combination that prevents spectral confusion and makes each feature stand out. The main image displays the classifications, which are described in the side legend.
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Lab 4-Spatial Enhancement, Multispectral Data, and Band Indices

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  Hi Everyone!  Module 4 focuses on the representation of remote sensing data in multispectral bands and the use of greyscale and spectral enhancements to analyze brightness, sharpness, and contrast in imagery. Lab 4 used ERDAS Imagine to analyze remote sensing digital data  and ArcGIS to make layouts. The map above displays TM false natural color imagery, which offers a wide range of information and color contrast. Green indicates vegetation and salmon represents soil. The map above displays the brightness of the water feature and vegetation. This was done by examining the true color image and adjusting the radiometry to brighten and emphasize the severity of the features. The map above displays true color imagery to highlight the white snow on the mountains.
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