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
Category: Remote Sensing
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
Introduction In this project, I completed a full ortho mapping workflow in ArcGIS Pro to create accurate satellite imagery products. The goal was to correct geometric distortion in raw satellite images so they can be reliably used for mapping, analysis, and measurement. This workflow included creating an ortho mapping workspace, performing block adjustment, adding ground control points, generating a digital
In this lab for REM-617-01: Image Analysis & Information Extraction, we performed image manipulation and atmospheric correction using a Landsat ETM+ scene in ENVI. The assignment required stacking spectral bands, interpreting RGB composites, creating a Region of Interest (ROI), building a mask, computing statistics, and applying Dark Object Subtraction (DOS). The objective was to move from raw satellite data to
Every pixel carries a truth invisible to the eye. Hyperspectral imaging doesn’t just capture color, it captures the chemistry of the world. Intro This post is based on one of our lab assignments in Applied Remote Sensing at Delta State University. The task was to explore the power of hyperspectral imagery, the kind of data that captures hundreds of spectral
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
There is a quiet precision in Lidar work. Every return pulse is a story, every elevation layer a whisper of the terrain. What looks like color and code is a dialogue between light and surface. This lab took that conversation apart, from raw LAS files to a three-dimensional rendering of life above and below the canopy. Importing Lidar Data and
Intro Multispectral scanning allows for the acquisition, display, and interpretation of the thermal properties of the Earth’s surface. Many multispectral systems sense radiation not only in the visible and reflected infrared but also in the thermal infrared range (3 μm – 15 μm). Thermal remote sensing differs from optical imaging: it measures emitted energy rather than reflected sunlight. The boundary