Sentences with phrase «understanding spatial data»

Interactive maps obviously lend themselves to understanding spatial data.

Not exact matches

The room can understand and register speech, three specific gestures, the position of occupants of the room, their roles, and the spatial orientation of those occupants, triggering the correct cognitive computing agents to take action and bring data and information relevant to the discussion into the room in real - time.

This study highlights the need for high - resolution spatial data on tiger mosquito density, biting behavior, and seasonality to better understand, predict, and manage arboviral transmission risk in temperate cities.

High - frequency spatial and temporal data is incredibly important if we want to discern trends and understand how to manipulate ecosystems.

Multiplexed Imaging Here the goal is to add spatial resolution to cytometry - data in order to understand, in a tissue, WHERE immune and cancer cells interact We design, develop and apply methods for multiplexed visualization of protein and RNA molecules in tissue sections.

In learning about how this method works — its strengths and its weaknesses — I understood that the patterns it produces could reflect spatial structure in population data.

I understand the issue — that when considered as a whole, the data on the Nature cover may better capture the trends over time than any other method of determining the average trend over the continent — but that said, it is not accurate on the fine spatial scale that it is presented.

The goal is to provide the Arctic research community and other users of Arctic climate information with access to climate variability and change data on the smaller spatial scales that are needed for improved fundamental understanding and for decision support applications and assessment research.

Meanwhile, the few studies that involve a higher spatial resolution generally do so by sacrificing the temporal coverage of the data, providing them with a «case study» point of view of a particular weather event, rather than robust statistics required for an understanding of climate.

Analyses of tide gauge and altimetry data by Vinogradov and Ponte (2011), which indicated the presence of considerably small spatial scale variability in annual mean sea level over many coastal regions, are an important factor for understanding the uncertainties in regional sea - level simulations and projections at sub-decadal time scales in coarse - resolution climate models that are also discussed in Chapter 13.