Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

2018 ◽  
Vol 494 ◽  
pp. 76-86 ◽  
Author(s):  
J.P. Juchem Neto ◽  
J.C.R. Claeyssen ◽  
S.S. Pôrto Júnior
Keyword(s):  
Growth Model ◽  
Transport Cost ◽  
Spatial Growth ◽  
Spatio Temporal ◽  
Spatial Growth Model

An application of a spatial growth model of Scots pine on drained peatland

1991 ◽  
Vol 41 (3-4) ◽  
pp. 265-277 ◽  
Author(s):  
Jari Miina ◽  
Taneli Kolström ◽  
Timo Pukkala
Keyword(s):  
Growth Model ◽  
Scots Pine ◽  
Spatial Growth ◽  
Spatial Growth Model

Spatio-Temporal Testing Of New Crop Growth Model

2011 ◽  
Author(s):  
Mikko Hakojärvi ◽  
Mikko Hautala ◽  
Berit Mannfors ◽  
Laura Alakukku ◽  
Antti Ristolainen
Keyword(s):  
Growth Model ◽  
Crop Growth ◽  
Crop Growth Model ◽  
Spatio Temporal ◽  
New Crop

Spatio-Temporal Estimation of Wildfire Growth

2013 ◽  
Author(s):  
Balaji R. Sharma ◽  
Manish Kumar ◽  
Kelly Cohen
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Real Time ◽  
Growth Model ◽  
Wildland Fire ◽  
Time Estimation ◽  
Fire Growth ◽  
Growth Data ◽  
Partial Differential ◽  
Spatio Temporal

This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.

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