Algorithm Performance on the Estimation of CDOM and DOC in the North Slopes of Alaska

• Main Author: Weisenbach, Monica
• Format: Text
• Language: unknown
• Published: University of Massachusetts Amherst 2021
• Subjects: Arctic; Climate change; Alaska
• Online Access: https://dx.doi.org/10.7275/24572353.0; https://scholarworks.umass.edu/masters_theses_2/1102

Use of satellite imagery makes environmental monitoring easy and convenient with little of the logistics involved in planning sampling campaigns. Colored dissolved organic matter (CDOM) is an important component to track as a proxy for the large pool of dissolved organic carbon (DOC). In a world contending with the looming issue of global climate change, the ability to investigate the carbon cycle of inland to coastal environments allows for examination of the magnitude of carbon flowing through the system and potential changes over years. The Arctic region is a critical area for climate change impacts but is a difficult landscape for sampling implementation and is thus an excellent target for satellite monitoring. This thesis focuses on the North Slopes region of Alaska to take advantage of the Toolik Lake monitoring site. Landsat 8 imagery has the appropriate spatial, spectral, and temporal resolutions for use in inland water and coastal environments. There are numerous developed algorithms for CDOM estimations, but many algorithms are designed for specific regions. A special challenge in inland environments is the bottom reflectance contribution to the outgoing light signal. An algorithm designed specifically for optically-shallow water environments (SBOP) was tested against two algorithms designed for optically-deep water environments (QAA-CDOM, K05). The relationship between CDOM and DOC was also investigated and used as further validation for algorithm performance. The SBOP algorithm shows promise iv alongside QAA-CDOM at estimating CDOM absorption, but the number of validation point makes pinpointing one algorithm difficult. All algorithms performed well at estimating DOC concentrations.