spatio-temporal data models
Predictive spatio-temporal models for spatially sparse environmental data
... apply the model building strategy desribed in the previous setion, where the station ordering. (3) is dened by onsidering asending distanes, see Figure 3[r] ...
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Bias correction and change measurement in spatio temporal data
... selection models, the resulting models have type II errors for rare habitat use and incorrect conclusions regarding selection versus avoidance (Rettie and McLoughlin, ...enough data from stationary ...
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Multiplicative Spatio-Temporal Models for Remotely Sensed Normalized Difference Vegetation Index Data
... forecasting models for normalized difference vegetation index (NDVI) data recorded by remote sensing via satellites in East ...Africa. Spatio-temporal auto-regressive moving average (STARMA) ...
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Spatio-temporal approach to moving window block kriging of satellite data v1.0
... of spatio-temporal covariance Existing studies have used a number of models to estimate spatio-temporal covariances for a variety of ...applications. Models used include the ...
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Using long-term datasets to assess the impacts of neonicotinoids on farmland bird populations in England
... long-term data have suggested that neonicotinoid applica- tion has had a detrimental impact on bird populations, but these studies were either limited to a single species or neglected to analyse specific exposure ...
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Spatio temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana
... above models were fitted to take into account spatio-temporal ...density data, respect- ...all models used are given in Additional file ...
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Considering groups in the statistical modeling of spatio-temporal data
... A spatio-temporal process is said to be non-separable if its spatio-temporal covariance function cannot be obtained as the sum or the prod- uct of a spatial covariance function and a ...
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Spatio-temporal forecasting of network data
... these models address is that of identifying the local or dynamic STN, which is the the neighbourhood of features or variables that is relevant to the location of interest at a given ...purely temporal ...
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Thermal spatio-temporal data for stress recognition
... facial data in the thermal (TS) and visible (VS) ...computational models for stress recognition using both TS and VS imaging together as ...from temporal and texture characteristics of facial regions ...
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Challenging Issues of Spatio-Temporal Data Mining
... Spatio-temporal data mining is becoming now very important field of research as it focuses the data for not only static view point but also on time and ...of spatio-temporal ...
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Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data
... trajectory data are of- ten aggregated to protect ...aggregated spatio-temporal population data of 500- meter grid squares that are generated based on operational data from mobile ...
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Survey on Spatio-Temporal Database and Data Models with relevant Features
... Spatio-temporal datamodels are the core of a Spatio- Temporal Information System (STIS); they define object data types, relationships, operations and rules to maintain database ...
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A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage
... on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values ...
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Identification of partial differential equation models for a class of multiscale spatio-temporal dynamical systems
... 3000 spatio-temporal observations randomly selected out of 513 × 101 data points was used for the ...simple models, the number of final model terms was set to be ...
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Joint Models for Spatial and Spatio-Temporal Point Processes
... model, data are assumed to arise as a mixture of a point mass at zero and a Poisson component with component membership for observations being ...health data, the zero-inflation component serves as an ...
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Finding Spatio-Temporal Patterns in Multidimensional Data Streams
... The spatio-temporal analysis of data streams can handle a continuous data stream, considering the data reading, timestamp and also the geographic position where the sensor (data ...
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A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London
... residual spatio-temporal auto- correlation in the respiratory disease data after the covar- iate effects have been removed, which if ignored can bias the estimated health effects of air ...of ...
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Traffic occurrence detection using spatio temporal data mining
... geometric models proposed for better sequential mining ...and temporal information are measured to identify the possible ...and temporal information are measured to discover the probable ...transfer ...
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Human Mobility Mining Using Spatio-Temporal Data
... space-state models, use sequence models and probabilistic automation for mining location history [19, 25, 29, ...the data that is not immediately observable by training the model: location history in ...
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Spatio-temporal Background Models for Outdoor Surveillance
... the models defined in Section 4 are the choice of the model, image blurring filter, exponential forgetting factor (over-weighting the newest data, as discussed above), and a threshold to interpret the score ...
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