Although the hydrological effects of land use change have been studied extensively, only few datasets are available to accurately describe, model, and predict detailed changes in spatiotemporal patterns of hydrological fluxes and states due to land use change.
However, few datasets were available for comparison in our study.
There is even few public infrared datasets available for supporting the fundamental evaluation requirements of this research.
Although we could not consider the leakage effect directly given that there are few global-scale datasets available [38], [39], we expect that leakage is either proportional to absolute wealth and intensity of development, or it could even increase (e.g., exponentially) with increasing wealth.
However, very few datasets are publicly available.
In the field of digital image and video forensics, only few datasets have been made available to the research community, especially for the source device identification problem.
Also, very few datasets addressing this question are publicly available and have been repeatedly used for bioinformatic analyses.
Further, because site-level datasets often focus on relatively few sampled variables, these datasets will be far more useful for answering broad scale research questions when combined with complementary geographic information system (GIS) datasets, available at national scales for features such as land use/cover, climate, topography and atmospheric deposition, to name a few.
Interactive graphs and datasets available at my Plot.ly profile here.
You can see a sample of the datasets available and what formats are available.
