Results 11 to 20 of about 3,938,305 (341)
Biostatistics, 2018 AbstractThe analysis of area-level aggregated summary data is common in many disciplines including epidemiology and the social sciences. Typically, Markov random field spatial models have been employed to acknowledge spatial dependence and allow data-driven smoothing.
Katie, Wilson, Jon, Wakefield
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Ethnic inequalities in cycling to work in London: mobility injustice and regional approach
Regional Studies, Regional Science, 2023 This paper investigates ethnic inequity in cycling to work in London, as ethnic minorities in London cycle to work less frequently than white Londoners. The study adopts three methods: spatial statistics, linear regression and spatial econometrics based ...
Zofia Bednarowska-Michaiel
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Stochastic spatial models [PDF]
SIAM Review, 1999 The author considers a spatial model with the space represented as a grid of sites that can be in one of a finite number of states. The site changes its state with a rate that depends on states of a finite number of sites. Assuming that sites are independent, the behaviour of such models can be studied with the help of mean field ordinary differential ...
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Ecological Solutions and Evidence, 2023 Effective wildlife monitoring and management are reliant on unbiased estimators of population parameters. Most standard survey approaches ignore spatial pattern in the data although spatial relationships can be leveraged to produce more efficient designs
Joshua H. Schmidt +3 more
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Spatially embedded random networks [PDF]
, 2007 Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the ...
B. Bollobás +10 more
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Modeling spatial knowledge [PDF]
Cognitive Science, 1978 A person's cognitive map, or knowledge of large‐scale space, is built up from observations gathered as he travels through the environment. It acts as a problem solver to find routes and relative positions, as well as describing the current location. The TOUR model captures the multiple representations that make up the cognitive map, the problem‐solving
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OENO One, 2018 Aims: This work focuses on the study of the intra- and inter-annual Temporal Stability of Within-Field Variability (TSWFV) of Total Soluble Solids (TSS) as an estimate of grape maturity. Methods and results: The experiment was carried out between 2009
Nicolas Verdugo-Vásquez +5 more
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, 1999 The basic idea underlying the proposed approach to spatial-temporal modeling is to combine, at the different levels, the potential of various techniques and to exploit their performance. A three level procedure is used. Firstly low level polynomial interpolation removes a general trend; then finite element method follows to match local variations.
MUSSIO L, NOCERA, Rossella, POLI D.
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Environment and Natural Resources Journal, 2021 Spatial modeling is an analytical procedure that simulates real-world conditions using remote sensing and geographic information systems. The field data in this study were collected from 318 survey plots in the area surrounding highway 304 in the Dong
Paanwaris Paansri +4 more
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ASM Science Journal, 2021 The urbanisation process cause changes to the physical and non-physical environment to developing a town and Urban Quality of Life (UQoL). Kuala Terengganu is experiencing rapid urbanisation process over the past three decades. The main objective of this
Mohd Khairul Amri Kamarudin
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