Joel Sexson's GIS Blog UWF

    Hello all, in this week of  Photo Interpretation and Remote Sensing, we learned how digital imagery is classified both unsupervised and supervised. Unsupervised classification is done manually and does not use a predetermined classification that matches pixels. Supervised classification is done under the supervision of an already established set of "spectral signatures". We used ERDAS Imagine to classify the images and ArcGIS to make the layout.  This image uses a band combination that helps each feature stand out and avoid being spectrally confused. The main image shows the classifications, explained in the legend on the side. The distance map shows the accuracy of the classification. Brighter spots on the distance map were more likely to have been spectrally confused.  Thank you,  Joel Sexson

 Hello all, in this week of Photo Interpretation and Remote Sensing, we learned about how remote sensing data is represented in multispectral bands, as well as using greyscale and spectral enhancements to learn about brightness, sharpness, and contrast in imagery. We used ERDAS Imagine to analyze the images and ArcGIS to make layouts.  This image uses true color imagery to showcase the brightness of the snow on top of the mountains in contrast to the dark green vegetation surrounding it.  This image uses a unique band combination (shown in the legend) to showcase the variation in brightness of the water.  This image uses false color imagery to showcase the dark blue/black water in contrast to the red vegetation around it. The vegetation is not actually red, this is just a false color image.  Thank you, Joel Sexson

 Hello all, in this week of Photo Interpretation and Remote Sensing we practiced using ERDAS Imagine to analyze remote sensing digital data. We also learned about the EMR spectrum and how data is digitized differently to get higher resolutions, e.g. radiometric or spatial resolution with maximum pixel amount and pixel size, respectively.  This map depicts the small subset of an image that had been exported from ERDAS Imagine to ArcGIS to be able to display it in a more friendly way. The image's data (such as the area and classification) was preserved over the exportation, which made the whole process quite easy.  Thank you, Joel Sexson