However, accurate prediction of facies and fractures is hard in the absence of high-resolution advanced geophysical logs (e.g. image logs) and core samples.
High-resolution advanced microscopic techniques such as confocal laser fluorescence microscopy, atomic force microscopy, and scanning electron microscopy are capable of providing detailed morphological features and cytoskeletal information.
The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies.
Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released.
These investigations have generated increasing numbers of DHQase structures with high resolution and have significantly advanced the understanding of DHQase catalytic mechanisms (Chaudhuri et al. 1986; Deka et al. 1994; Euverink et al. 1992; Hawkins et al. 1993; Lee et al. 2003; Moore et al. 1993; Roszak et al. 2002; Singh and Christendat 2006).
It is undisputed that advanced high resolution SD-OCT technique is a prerequisite [19], [20], [24], [26] [29].
Immunolabeling of multiple components or live cell dynamic recording can be readily accomplished using fluorescence microscopy, while retrieval of high resolution structural data requires advanced electron microscopy.
The NDVI time series used in this study are from the global inventory monitoring and modeling studies (GIMMSs) database obtained from the advanced very high resolution radiometer (AVHRR) remote-sensed observations (Tucker et al. 2005).
Regarding a national scale of urban forest carbon offset, Nowak et al. [18] set a standardized urban forest carbon value from selected cities and upscaled it across the US using national tree canopy data retrieved from 1991 remote sensing imagery of advanced very high resolution radiometer (AVHRR).
The recent advent of high resolution smart water meters and advanced data analytics allow for a new era of using the continuous 'big data' generated by these meter fleets to create an intelligent system for urban water management to overcome this problem.
We have used Reynolds SST data (1° × 1° resolution) derived from daily merged in situ and high-resolution (9 km) infrared satellite observations from the AVHRR (advanced very high resolution radiometer) instrument on board NOAA satellites (Reynolds et al., 2002).
