Christa's GIS Archive

This week's module covered all things classification from unsupervised to supervised. In ERDAS, we got to see how the two differed and how to preform each. It was really cool to see how the program would classify pixel areas for you based on what you essentially feed into it. Since unsupervised classification has users classify after the program categorized pixel values, it felt much easier and quicker; however, accuracy may not be as high when compared to supervised. Supervised classification took me much longer with all the steps we had to go through to identify to the program the classes/features themselves, although it was the most rewarding trying to wrap my head around everything. After learning how to preform both, the map deliverable this time around involved us taking a raster image from Germantown, Maryland and classifying its land use/land cover based on supervised classification. By the time we got to this image, I figured out that ERDAS had some nice preset color theme...

This week's module was on Spatial Enhancement, Multispectral Data, and Band Indices. I've never had to alter imagery when it comes to its spatial or spectral resolution, so this was very intriguing to learn but also a bit overwhelming at times trying to take it in for the first time. I'm sure in time, as I get exposed to these concepts more, I will become more confident doing these kind of image enhancements or alterations in the future. We first began by learning how to retrieve aerial imagery. I find that this can sometimes be the hardest part of a project. Locating the data or imagery needed can truly be half the battle. I am grateful that this lab gives us those resources and walks us through how to download imagery. If we don't have the data or images needed to conduct an analysis, then accomplishing the goal or finishing a project would be impossible. I will definitely be keeping these sources in mind for future projects, including the final for this course! Addit...

Oh we meet again, ERDAS Imagine. I haven't touched that program in quite some time -- probably at least a year or two at this point. We seldom use it for work; we mostly rely on it for creating and cleaning up large mosaics, like in the countywide historical aerial initiative that the GIS team was working towards a while back. Frankly, we haven't been keeping up with that legacy project, due to the workload and overall demand for GIS support increasing; however, I will admit my time with ERDAS was not the most pleasant back then when I first joined the GIS team. Lots of crashing and confusion occurred back then, especially when compared to ArcGIS Pro, the primary program that is utilized in our workflows. Thankfully, I was grateful for the kind and easy to digest introduction into ERDAS Imagine this second time around. Taking this course, I'm definitely seeing other ways of analyzing and processing imagery through this program, which is really cool! I've warmed back up ...

If I had one word to describe Module 2's lab, it would be "restraint". Restraint because I needed to restrain myself from being a perfectionist and trying to fix every little thing I catch. I can get lost in the weeds and not see the whole forest for the trees, so to speak. So, giving myself the room to not digitize as strictly as I would normally proved quite difficult. Module 2 covered Land Use/Land Cover as well as Ground Truthing of the Pascagoula, Mississippi area. We were provided an aerial to classify the LULC codes over the entire satellite imagery. Not gonna lie, this was pretty daunting. I've never had to do anything like this -- usually it's specific areas like mining or impact areas. So to do the entire tile felt intimidating, but I was up to the challenge. I made sure to break things up by the larger areas to smaller areas, that way the larger spaces could be accounted for first and I could worry about the finer detailed sections later. Honestly, I dr...