Beyond RGB: Interactive Exploration of NEON's Hyperspectral Data
As a research specialist focused on remote sensing applications in semi-arid rangelands, I'm constantly seeking tools that can enhance our ability to process and analyze large-scale geospatial data. The excitement of discovering new platforms that streamline complex workflows never gets old, especially when dealing with the massive datasets typical in remote sensing research.
My journey with Fused began unexpectedly through the "Minds Behind Maps" podcast, where host Maxime Lenormand interviewed Sina Kashuk, Co-Founder and CEO of Fused (see episode). The conversation sparked my curiosity, leading me to explore Fused's community examples and documentation. After joining their waitlist and receiving access, I knew exactly how I wanted to test it: an interactive tool for exploring NEON's Airborne Observation Platform (AOP) data.
Find Guillermo's UDF code and App associated with the blog post here:
Making Hyperspectral Data Accessible
For those unfamiliar with NEON AOP, it's an NSF-funded initiative revolutionizing ecological observation. Using advanced imaging spectrometers, NEON collects hyperspectral data across 426 distinct wavelength bands at 1-meter resolution. Imagine having 426 different perspectives of the same landscape, each revealing unique insights about vegetation, soil composition, and ecosystem health.
Source: NEON Imaging Spectrometer.
The real challenge, however, isn't collecting this rich data - it's making it accessible and actionable for researchers. This is where Fused enters the picture. Diving into their documentation and gallery of click-and-run examples, I found myself inspired by the platform's potential. By combining elements from various examples, I began building my first User Defined Function (UDF), eventually discovering the App Builder - a feature that would prove crucial in creating an interactive interface for hyperspectral data exploration. Having worked extensively with Google Earth Engine (GEE) and NEON data, the recent announcement of NEON AOP's availability through GEE presented the perfect opportunity to test Fused's capabilities. My goal was simple yet powerful: create a user-friendly application that could tap into this wealth of hyperspectral data and make it instantly accessible to researchers.
Building the Fused App
The resulting application streamlines what traditionally would be a complex data acquisition process into a few simple clicks. Users can select any NEON site and survey year from a dynamically populated list - a feature that automatically stays current with GEE's data catalog, as NEON sites are surveyed at different frequencies. Once a site is selected, users can click anywhere within the highlighted area to instantly view all 426 bands of spectral data in an interactive plot.
Under the hood, each click triggers a carefully crafted UDF that connects to GEE's data catalog, extracts the hyperspectral values for that specific location, and transforms them into a clear, interactive visualization. What makes this particularly exciting is how Fused handles all the infrastructure complexity, letting me focus solely on the analytical workflow and user experience.
Looking Ahead
Looking ahead, I'm already planning the next phase of this app. I just want to add functionality that tracks sampling locations and allows users to export their collected data as CSV files, complete with all 426 bands and additional metadata. This will enable data users to easily build training datasets for Machine Learning applications, develop new spectral indices, or conduct detailed statistical analyses.
The experience of building this demo app has reinforced my belief in the importance of platforms like Fused in the geospatial community. They serve as crucial bridges between massive datasets and practical applications, eliminating infrastructure headaches and letting researchers focus on what matters most - the science.
For those interested in exploring NEON's hyperspectral data or learning more about this application, feel free to connect with me or try the app for yourself here.
The future of remote sensing analysis lies in making powerful data more accessible, and I'm excited to be working in this field.