In one of the labs in our Advanced GIS Applications course, we used ArcGIS Pro and Random Forest machine learning to predict the percentage of households without internet access across U.S. counties. That sounds more complicated than it really is. The idea was simple: take county-level data, prepare it properly, train a model, test it against data it had not
Tag: GIS
Using ENVI Classic, Landsat bands, K-Means, and ISODATA to turn a satellite image into a land-cover map In this lab, we used unsupervised image classification to separate land-cover types around Cañon City. The process started with a false-color composite, moved through spectral signatures, and then compared K-Means and ISODATA classification results. The short version: the computer can group pixels, but
Graduate school occasionally surprises you. You sign up for a GIS class expecting maps, coordinates, and perhaps the occasional argument with software that behaves like it personally dislikes you. Then suddenly, you are staring at satellite imagery from Peru, comparing a river before and after a flood, quietly realizing that modern geography has evolved into something resembling detective work from
Spring 2026 is officially over. Four courses completed. And after submitting the final exam for the last course, I experienced a feeling unfamiliar to graduate students: Silence. No deadlines.No discussion boards.No professor casually posting: “Just one final reminder.” That sentence alone has caused more stress than actual exams. The strange part is that this is already my second master’s degree.
Something interesting just happened in the world of maps. Ask Maps and immersive navigation were recently introduced by Google as part of the continued evolution of Google Maps. The announcement was described in Google’s official blog post, “Ask Maps: Immersive navigation powered by AI,” published on the Google Blog. On the surface, it looks like another shiny feature. AI answers
When people talk about evictions, the conversation usually focuses on numbers. We hear about eviction rates, percentages, and housing statistics. But those numbers rarely show where these problems are happening. That is where Geographic Information Systems (GIS) become useful. GIS helps us move beyond simple statistics and see the geography behind social issues. By mapping eviction rates, we can start
Most people think GIS is about making maps. In reality, the most valuable GIS work happens when spatial analysis supports real decisions. This lab focused on a practical problem faced by many communities: how to identify open-space parcels inside flood-prone areas that may qualify for FEMA Community Rating System (CRS) credits and potentially reduce flood insurance costs. What makes this
Approval feels good. Data availability humbles you. The False Victory You think the hard part is getting your topic approved.You polish your proposal, you lace it with academic keywords like geospatial, climate, temporal analysis, and you hit “submit.” You wait. You overthink. You refresh the page as if Canvas is a stock ticker. Then one day, the professor replies: Approved.
Intro This project demonstrates how an existing deep learning model can be refined to perform better on local data. It walks through how transfer learning allows a pretrained model to adapt to new imagery and conditions, using ArcGIS Pro as a complete workspace for deep learning. Preparing the Project The lab begins with the Seattle_Building_Detection project, which contains NAIP aerial
Introduction: From Pixels to the Real World Every satellite image tells a story, but that story only makes sense when you can trace each pixel back to the ground. In remote sensing, this connection between imagery and reality is called ground truthing. It ensures that what we interpret from orbit reflects what truly exists on Earth. As Campbell and Wynne