Meet Chuck - Our Field Spectroradiometer

Meet Chuck – Our Field Spectroradiometer

Shawnee Reynoso

Sonoma State University

Reflectance. To most of us, it is just light bouncing back from a surface. Most of us refer to it when talking about a mirror or road signs. To a JIRPer, it is the reason behind our most frequent and prominent sunburns. As a glaciologist, reflectance is the key to understanding the relationship between incoming solar radiation, glaciers, and melt. When dust or ash or algae is deposited on a glacier’s surface, it gets darker and melts more. It is important for us glaciologists to measure and understand these processes. But how?

To measure the glacier surface reflectance, JIRP faculty member Allen Pope introduced us to the field spectroradiometer. We named it Chuck. Why you may ask? Because it stuck. That’s pretty much the only requirement to name things here at JIRP.

Chuck the field spectroradiometer is a lightweight box you can easily carry into the field. So what does a spectroradiometer do? It measures the amount of visible and near-infrared light being reflected off a surface. Along with the spectroradiometer comes a Spectralon panel. Spectralon is a ceramic white palette which is very bright in almost all wavelengths, making it close to 100% reflective. This Spectralon is used as a reference for how much light is present where you are currently taking surface reflectance measurements.

Deirdre Collins, Brittany Ooman, and Kate Bartell discuss reflectance data in the field. Photo by Shawnee Reynoso.

Deirdre Collins, Brittany Ooman, and Kate Bartell discuss reflectance data in the field. Photo by Shawnee Reynoso.

To use Chuck the spectroradiometer, you hold it as far away from you as possible and point it at your intended surface. First, you take a snap of your Spectralon to get a reference reflectance. This device is highly sensitive meaning that the color clothing you are wearing or your shadow can significantly influence its results. Next, you take a measurement of your surface and then you can see a graph on the computer screen showing your results. This graph shows highs and lows throughout visible and near-infrared light indicating which colors are being reflected and which are being absorbed.

Excited at how easy it was to use Chuck, we ran around camp and found various surfaces to measure and then compare. We pointed Chuck at brightly colored clothing, green moss, white snow, dark pools of water, and more! In measuring the reflectance of a reddish-tan granite, the graph peaked near the red point of visible light. This is the result we would have expected considering the tint of the rock. White snow matched up with our expectation of a bright and even reflectance spectrum throughout the visible light (because white is made up of all colors of light) but darker in the near infra-red (which is typical), and so our results made logical sense, which is always encouraging.

Deirdre Collins uses Chuck the Field Spectroradiometer to investigate the reflectance of various surfaces near Camp 18. Photo by Shawnee Reynoso.

Deirdre Collins uses Chuck the Field Spectroradiometer to investigate the reflectance of various surfaces near Camp 18. Photo by Shawnee Reynoso.

This exercise allowed us first hand experience with one of the research tools used by scientists. Allen’s research then uses this type of field data to help better interpret satellite imagery, for example. We were able to explore potential for what we could learn being able to get this data from specific locations in the field. Automatically retrieving the data also allowed us to consider and discuss the data while we were still collecting it in the field. (On another day, we used the data to calculate how much darker algae on the snow made the surface.) Aside from data collecting this was a fun activity that allowed me to understand reflectance in a clearer way then I had previously.

 

Student Project: Icefield Reflectance and Albedo

2015 JIRP Student Project: Icefield Reflectance and Albedo

Faculty Experts: Allen Pope

Overview: Surface reflectance (sometimes called albedo, although if you choose this project you will learn why that isn’t strictly accurate) is an important property for understanding how much melt energy a glacier is absorbing. The Icefield reflectance project will use a field spectroradiometer to measure the spectral reflectance of glacier surfaces, studying the spatial and temporal variability of glacier spectral reflectance and albedo. Students will develop questions relating to processes that influence surface reflectance and design data collection strategies accordingly. Some suggestions are given below. The goal of this project is a better understanding of temporal and spatial variability in Icefield reflectance.

Level 1 students are not expected to continue their work beyond the summer field camp unless computations and write up are not completed during summer.

Level 2 students should expect to continue to work on data analysis beyond the summer season, with a more detailed analysis and report turned in near the end of fall semester.

Project breakdown:

Spectral reflectance: This is the basic unit of all subsequent projects. Radiance and irradiance measurements will be collected and students will process these data into reflectance spectra. Students will choose a range of locations and times to understand the spatial and temporal variability in glacier surface reflectance. Levels 1 & 2

Albedo: The next step beyond reflectance spectra, students will incorporate spectral reflectance and irradiance measurements to calculate glacier surface albedo. Students will investigate temporal and spatial variability in albedo resulting from changing illumination conditions and surface properties. Levels 1 & 2

Grain size studies: Students will study temporal and spatial variability in snow grain size by comparing direct observations using a snow card with calculations based on measured reflectance spectra. Level 2 {Possibly level 1}

Impurities: Students will investigate the impact that impurities (dirt/dust/soot) have on spectral reflectance (and albedo). Students can design controlled experiments or locate appropriate natural study sites. Levels 1 & 2

Compare with remote sensing: Understand how your point data scale up to reflectance measurements from airborne and satellite remote sensing measurements. Level 1 students will learn how to directly compare with satellite imagery. Level 2 students will have the opportunity to compare with 2015 observations and design a larger experiment.

Link with energy balance: Join forces with the energy balance modeling project to understand what your albedo measurements mean for surface mass balance. Level 2

Advisor’s Note: I focus on glacial remote sensing, so I focus on pointing the field spectroradiometer at snow and ice. If you’re interested in looking at other reflectance spectra (rocks, algae, or something else), that is something I’m open to, too!

Timeline and Logistics: There are two main constraints on this project: availability of the field spectroradiometer and appropriate weather for data collection. The field spectroradiometer should be available for at least two weeks in mid July, and possibly in early/late July (depending on shipping constraints), but there is nothing we can do about the weather except hope it is good! The field spectroradiometer and controlling laptop need to be charged every night, so fieldwork will be based out of camps, but travel with skis and possibly snowmobiles will be incorporated as the science necessitates it. Locations and frequency of data collection will be determined by student interest. Preliminary analysis will be conducted in camp. Further data collections will then be planned.

References (in approximate order of priority):

1. McArthur, A., 2007. “ASD Collection and Processing Guides,” NERC Field Spectroscopy Facility.

2. Skiles, M., 2015. Snow Optics Lab Protocols.

3. Hendriks, J, and P. Pellikka. “Estimation of Surface Reflectances from Hintereisferner: Spectrometer Measurements and Satellite-Derived Reflectances.” Zeitschrift Für Gletscherkunde Und Glazialgeologie 38, no. 2 (2004): 139–54.

4. Pope, A., and W. G. Rees. “Using in Situ Spectra to Explore Landsat Classification of Glacier Surfaces.” Journal of Applied Earth Observation and Geoinformation 27A (2014): 42–52. doi:10.1016/j.jag.2013.08.007.

5. Gardner, A. S., and M. J. Sharp. “A Review of Snow and Ice Albedo and the Development of a New Physically Based Broadband Albedo Parameterization.” Journal of Geophysical Research-Earth Surface 115 (2010): F01009.

6. Schaepman-Strub, G., et al. “Reflectance Quantities in Optical Remote Sensing - Definitions and Case Studies.” Remote Sensing of Environment 103, no. 1 (2006): 27–42. doi:10.1016/j.rse.2006.03.002.

7. Takeuchi, N. “Temporal and Spatial Variations in Spectral Reflectance and Characteristics of Surface Dust on Gulkana Glacier, Alaska Range.” Journal of Glaciology 55, no. 192 (2009): 701–9.

8.  Greuell, W, C. H. Reijmer, and J. Oerlemans. “Narrowband-to-Broadband Albedo Conversion for Glacier Ice and Snow Based on Aircraft and near-Surface Measurements.” Remote Sensing of Environment 82 (2002): 48–63.

9. Nolin, A, W., and J. Dozier. “A Hyperspectral Method for Remotely Sensing the Grain Size of Snow.” Remote Sensing of Environment 74, no. 2 (2000): 207–16. doi:10.1016/S0034-4257(00)00111-5.

10. Dumont, M. et al. “Contribution of Light-Absorbing Impurities in Snow to Greenland/’s Darkening since 2009.” Nature Geoscience 7, no. 7 (2014): 509–12. doi:10.1038/ngeo2180.

11. Painter, T. H., and J. Dozier. “Measurements of the Hemispherical-Directional Reflectance of Snow at Fine Spectral and Angular Resolution.” Journal of Geophysical Research 109 (2004): 21 PP. doi:200410.1029/2003JD004458.