# Coupled Spatiotemporal Characterization of Monsoon Cloud Cover and Vegetation Phenology
## 5 Conclusions  
We present a simple method to characterize the spatiotemporal dynamics of cloud cover and vegetation phenology for monsoonal landscapes. The method first uses the Principal Component transform to distill the full spatiotemporal complexity of an image time series into a small number of dominant modes of variability, and it then uses the temporal feature space of the low order Principal Components to identify the most distinctive and physically meaningful temporal patterns present in the data. The most statistically extreme temporal endmember patterns are identified. Pixel time series from the rest of the image can be represented as linear combinations of these endmember time series. The inversion of a linear temporal mixture model generates maps of the most statistically distinct and physically meaningful spatiotemporal patterns. Trends in individual regions may be investigated with greater accuracy than analyses relying on either pixelwise or total spatial averaging methods, because statistically similar pixel time series are selectively grouped together so that their common phenologies combine in phase to suppress noise and amplify any spatial or temporal differences among regions. Because of the reflectance signatures of green vegetation, non-photosynthetic vegetation, soil, and clouds, both cloud cover and vegetation phenology can be simultaneously quantified using an image time series of a single variable (NDVI). Near-daily imagery can be used to avoid the temporal aliasing inherent in the commonly used 8- and 16-day MODIS vegetation index composites.  
To illustrate the method, we apply it to an example time series featuring 17 years of daily MODIS NDVI imagery of Jabal Dhofar, southern Oman. The daily MODIS data captures rapid greening and rate-varying senescence of post-monsoon vegetation as well as spatial transitions between grasslands and forests. Characterization reveals five distinct spatiotemporal phenologies in Jabal Al Qara and two in Jabal Al Qamar, with clear gradients associated with both topography (between forests and grasslands) and longitude (between east and west) in each range. The distribution of these endmember patterns is spatially coherent, which indicates that the structure of the temporal feature space contains meaningful geographic variations in cloud cover and vegetation phenology. We find substantial interannual variability in cloud cover and vegetation phenology in every endmember region. Only one minor (+0.02 NDVI/year) statistically significant trend is observed in the 21 anniversary date--endmember region combinations examined. Moving forward, the global coverage, near-daily temporal resolution, and 18+ year record of MODIS data allows for this method to be applied to characterize the variability and trends in monsoonal vegetation anywhere on Earth.  
Conceptualization, D.S. and C.S.; methodology, D.S. and C.S.; validation, D.S., C.S., A.S. and A.K.; formal analysis, D.S.; investigation, D.S., C.S., A.S. and A.K.; writing--original draft preparation, D.S.; writing--review and editing, D.S., C.S., A.S. and A.K.; funding acquisition, C.S., A.S. and A.K.  
Work done by [PERSON] was conducted with Government support under FA9550-11-C-0028 and awarded by the Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. CS was supported by the NASA MultiSensor Land Imaging program (grant NNX15 AT65G). Fieldwork was supported by the Sultan Qaboos Cultural Center in the form of an SQCC Research Fellowship to [PERSON].  
The authors thank two anonymous reviewers and an anonymous academic editor for constructive comments which helped improved the manuscript. [PERSON] thanks [PERSON] for innumerable illuminating conversations.  
The authors declare no conflict of interest.