## 3 Results
### Net Ecosystem Exchange
Also similar to Figure 7, the decrease in MWIOLIS at the end of the summer (Figure 8c), while the vascular plants are still green, indicates the index is also sensitive to the potential water stress in vegetation due to high evapotranspiration, high air temperature, and low water table. While both models in Figure 8a,c are significant, the yearly cumulative NEE model from the 10 years of Landsat TM 5 data (Figure 8a) provides a stronger intuitive measure of predictive utility [52]. To examine the transferability of the temporal NEE models to other sensors with finer spatial and spectral resolutions, we applied the functions from Figure 8a-c to MWI calculated via Equations 4 (MWI\({}_{\text{S2}}\)) and 5 (MWI\({}_{\text{S2 Re}}\)) to Sentinel-2A and resampled CASI HSI imagery (Tables 2 and 4). The resulting modeled relative NEE for the tower footprint was then compared to daily average (daytime only) and 30 min tower observations averaged over a 3 h window surrounding the image acquisition time. Due to high altitude cirrus contamination (i.e., thin, transparent, or semi-transparent clouds \(\sim\)6-7 km above the Earth's surface) in two of the Sentinel-2A scenes (24 May and 19 August) that was not adequately removed by Sen2 cor and no tower NEE data for the November image, only six images from Table 4 were examined in the correlation. A larger number of images is necessary to determine if the effect size (\(r=-0.72\)) between MWI\({}_{\text{S2 Re}}\) and actual tower measured NEE is reliable. Figure 7: MWI\({}_{\text{TM5}}\) from Landsat TM5 over the 2009 growing season. Dotted line illustrates the average (\(\sigma=1.13\)). The results in Table 5 indicate that, while the models derived from multitemporal Landsat imagery are transferable to other sensors, there is an overwhelmingly improved performance of calculating MWI through Equation (5) (MWI\({}_{\text{52 Re}}\)), which substitutes the narrow red-edge band for the red band. Due to the MWI being sensitive to both the phenospectral properties and the water stress of the vegetation, it is a reasonable proxy for NEE of the bog. However, in order for the index to track changes in the spectral properties of the bog, the bands must be sensitive to subtle and sometimes rapid changes in the spectral properties of the surface [51]. Figure 9 illustrates the 10 years Landsat TM5 model with Equation (5) (MWI\({}_{\text{52 Re}}\)) applied to individual Sentinel-2A scenes. The NEE represented in Figure 9 range from approximately \(-0.9\) to \(-6\) g C m\({}^{-2}\) (high uptake). Due to the high-altitude cirrus contamination, the scenes from 24 May and 19 August should be interpreted with caution. The multitemporal spatial surfaces of relative NEE illustrate the same temporal trend as seen in Figure 7, with increased CO\({}_{2}\) uptake as the vascular plants green up followed by a decrease in late July/August when the vegetation is water stressed due to a low water table. The CO\({}_{2}\) uptake recovers for a short period in September followed by a decrease in C uptake as the vascular plants senesce. Figure 8: (**A**) Relationship between yearly cumulative NEE (g C m\({}^{2}\) year\({}^{-1}\)) and the yearly average MWI\({}_{\text{TM5}}\) calculated from Landsat TM5 over a period of 10 years. Confidence intervals (95%) are shown as the dashed lines (\(P\) = 0.003). Green point represents the year 2001. Only one scene was available for the senescent portion of the growing season in 2001 and is therefore not included in the model; (**B**) relationship between yearly cumulative NEE and the yearly average MWI\({}_{\text{OLIB}}\) calculated from Landsat 8 OLI imagery over the 2013–2016 period (\(P\) = 0.12); (**C**) relationship of MWI\({}_{\text{OLIB}}\) calculated from individual Landsat 8 OLI scenes and 3 h average NEE centered around the Landsat 8 OLI image acquisition time for 2016 (\(P\) = 0.0049).