Creating an Earth observations web app during my time with NASA DEVELOP inspired me to create another for my home state. This Google Earth Engine based web app provides the power of near-real time observations in a simple form factor, harnessing Google Cloud Functions (Python).
After dealing with tiresome methods for finding spectral absorption features in reflectence spectra, I wrote some Python code to make the job really quick and easy. I sure love spectra!
Having a lot of spectra to plot and explore can be tough. Yes, you can make spectral libraries in ENVI but that is a bit laborsome as well and I'm not the hugest fan of the charts. I made a downloadable .exe application to explore spectra called Rad Spectra Viewer. You can also just run the python script. It's helped me so I figure I would share.
The fall colors this year are amazing and Sentinel-2 and Landsat capture the changes in an impressive fashion. This page allows you to explore the large changes in colors that happened in just 20 days, between Sep 9th and Sep 29th. Use the interactive map to zoom in-and-out, and drag the vertical bar to explore the differences.
While writing a bunch of functions for processing satellite imagery, as part of my PhD work, I came up with this package to more easily process Landsat and Sentinel imagery using the Google Earth Engine Python API. I tried to bundle lots of efficient functionality into this package and it is what is currently powering the Utah Remote Sensing Interface.
This paper outlines the evolution of the Great Salt Lake and the GSL lakebed from the 1980's to present using Landsat and Sentinel imagery, mapping the extent of water, vegetation, and mineralogy of the exposed lakebed. This paper provides quantitative insight to the evolution of the GSL and provides useful metrics for policymakers to more easily understand. The paper is open access thanks to the Utah Geological Association and was published in the UGA 2024 Guidebook.