The Spectral Ocean Color Imager (SPOC) – An Adjustable Multispectral Imager

SPOC (SPectral Ocean Color) is a 3U small satellite mission that will use an adjustable multispectral imager to map sensitive coastal regions and off coast water quality of Georgia and beyond. SPOC is being developed by the University of Georgia’s (UGA) Small Satellite Research Laboratory (SSRL) through NASA’s Undergraduate Student Instrument Project (USIP). UGA is working with Cloudland Instruments to develop a small scale (\u3c 1000 \u3ecm3) multispectral imager, ranging from 400-850nm, for Earth science applications which will fly as part of the NASA CubeSat Launch Initiative. The project is UGA’s first satellite mission and is built by a team of undergraduates from a wide range of backgrounds and supervised by a multidisciplinary team of graduate students and faculty. Development, assembly, testing, and validation of the multispectral imager, as well integrating it into the satellite are all being done in house. At an orbit of 400 km the resulting images will be 90 km x 100 km in size, with a default spatial resolution and spectral resolution of 130 m and 4 nm, respectively

A Comparison between the MODIS Product (MOD17A2) and a Tide-Robust Empirical GPP Model Evaluated in a Georgia Wetland

Despite the importance of tidal ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these wetlands remain poorly understood. This limited understanding results from the challenges associated with in situ flux studies and their correlation with satellite imagery which can be affected by periodic tidal flooding. Carbon dioxide eddy covariance (EC) towers are installed in only a few wetlands worldwide, and the longest eddy-covariance record from Georgia (GA) wetlands contains only two continuous years of observations. The goals of the present study were to evaluate the performance of existing MODIS Gross Primary Production (GPP) products (MOD17A2) against EC derived GPP and develop a tide-robust Normalized Difference Moisture Index (NDMI) based model to predict GPP within a Spartina alterniflora salt marsh on Sapelo Island, GA. These EC tower-based observations represent a basis to associate CO2 fluxes with canopy reflectance and thus provide the means to use satellite-based reflectance data for broader scale investigations. We demonstrate that Light Use Efficiency (LUE)-based MOD17A2 does not accurately reflect tidal wetland GPP compared to a simple empirical vegetation index-based model where tidal influence was accounted for. The NDMI-based GPP model was capable of predicting changes in wetland CO2 fluxes and explained 46% of the variation in flux-estimated GPP within the training data, and a root mean square error of 6.96 g C m−2 in the validation data. Our investigation is the first to create a MODIS-based wetland GPP estimation procedure that demonstrates the importance of filtering tidal observations from satellite surface reflectance data