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Wilson and Cowan neglected spatial interactions in their original 1972 paper [16] in order to investigate temporal dynamics of a localized cortical column; they then extended their model to spatially distributed neural populations in their 1973 paper [17], and modeled 1-D rods and 2-D sheets of cortical and thalamic tissue.
We apply the model to spatially distributed salmon and fry data from the River Eden, Cumbria, England.
First, we applied the model to spatially nested landscapes to evaluate the effect of landscape size on the HRV pattern metrics.
Then, we adopted a CLUE-S model to spatially analyze changes in the landscape pattern and ecosystem services by simulating the following three scenarios: a historical trend, non-selective management of tea plantations, and selective management of tea plantations.
This work is a first step toward the development and application of a physics-based computer model to spatially complex, elevated, vegetation present in forest stands and in the wildland urban interface.
We used an algorithm (the so called 3T model) to spatially extrapolate the measured E of a reference lysimeter based on differences in surface temperature, net radiation and soil heat flux.
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This may occur when an average ES value is attributed to a distinct cartographical unit (i.e. land use/cover type) and (2) a combination of plot measurements and empirical geostatistical models to spatially model ESs provision.
Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models.
Such methodological differences are analogous to the use of a GWR (The weighting is controlled by a weighting function) or a regression with a spatially auto correlated (error term) when choosing a regression model to study spatially referenced data.
The TOA methodology is based on spatially explicit econometric simulation models linked to spatially referenced bio-physical simulation models to simulate land use and input decisions.
In this paper, we propose a new location model to support spatially configuring a system of recharging stations for commercial drone delivery service, drawing on literature from planar-space routing, range-restricted flow-refueling location, and maximal coverage location.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com