## 4 Discussion  
The catalyst for this study was EO-1's declining orbit and this work evaluated how it affected its instrument's data quality and stability though time. In general, it is demonstrated that surface reflectance retrievals were not seriously affected during the late mission precession period, typically being within 5% for VIS and 10% longer wavelengths for most surfaces, although the Libya-4 PICS desert variation was slightly higher due mostly to large dunes casting larger shadows from increased SZA from earlier overpass times. Other land cover types, including croplands and deciduous forests, were shown to have differences in reflectance between dates, but showed consistency when looking at their derivatives. All land cover types that we looked at, however, did not show marked increase or decrease in NDVI over the full precession range of the time series. It should also be stated that high off-nadir sensor view angles were avoided when selecting images to minimize variance due to view geometry differences.  
The effect of precession on other sensors has been studied, and these results can be compared to previous results. [PERSON] et al. (2017) measured orbital drift and its effects on Satellite Pour I'Observation de la Terre (SPOT) data, finding somewhat similar or slightly higher differences in spectral reflectance that ranged from 10-20% when in reference to another sensor, but the impact on NDVI was negligible. It is assumed that their study obtained slightly higher variances than those of the current study because the two SPOT sensors that were compared (i.e., VGT1 and VGT2) had differences in calibration accuracies, as well as slightly different spectral response functions  
This work provides insight on the limits of increasing SZAs on EO-1 surface reflectance data quality. This issue is important not only for the creation of consistent long-term satellite time series, but also help to define issues in combining data from multiple satellites with different overpass times, as have been proposed for future satellite constellations, and to merge existing or past data collections. Atmospheric correction models account for differences in the measured upwelling radiance  
Figure 10: Means of 172 calibrated Hyperion bands from 36 images acquired from 2004 to 2016 after use of three atmospheric correction models: (top row) least squares fit linear trend in surface reflectance; (bottom row) coefficient of variation (CV). The quadrature (combined uncertainty) is calculated as the square root of the sum of squares. Gray areas indicate atmospheric absorption bands ([PERSON] et al., 2017).  
for different acquisition dates and times and results could differ if only TOA products are used. Future work could study the limits of even earlier crossing times to see at what point the increased SZA starts to negatively affect data quality. [PERSON] (2016) found that the relative difference in reflectance values and NDVI increased moderately with increase in initial SZA up to 50\({}^{\circ}\), but beyond this, an increase in SZA resulted in an exponential change in relative difference. While this result is important, it was based on simulated SPOT data and only evaluated four multispectral bands. Our study is current as of late-2016, when the minimum SZA reached 50\({}^{\circ}\) (see Figure 3). Early in 2017, the last images were collected and the mission was decommissioned. At this point the minimum SZA was around 55\({}^{\circ}\), preventing us from determining the effects on data as the sun approaches the horizon at overpass time.  
Nevertheless, the first space-based measurements of a large methane leak from the Aliso Canyon, California super emitter were captured by Hyperion in January 2016 under low winter sun angles, and later verified by aircraft observations, demonstrating that even a nearly invisible gas plume above a complex landscape could be detected from orbit with a spectrometer (Stein