scholarly journals Trade, migration, and the dynamics of spatial interaction

2019 ◽  
Author(s):  
Nicolas Gauthier
Keyword(s):  
Social Interaction ◽  
Settlement Patterns ◽  
Large Scale ◽  
Spatial Interaction ◽  
Interaction Model ◽  
Structural Features ◽  
Small Scale ◽  
Interaction Models ◽  
Road Map ◽  
Migration Flows

Archaeological settlement patterns are the physical remains of complex webs of human decision-making and social interaction. Entropy-maximizing spatial interaction models are a means of building parsimonious models that average over much of this small-scale complexity, while maintaining key large-scale structural features. Dynamic social interaction models extend this approach by allowing archaeologists to explore the co-evolution of human settlement systems and the networks of interaction that drive them. Yet, such models are often imprecise, relying on generalized notions of settlement "influence" and "attractiveness" rather than concrete material flows of goods and people. Here, I present a dis-aggregated spatial interaction model that explicitly resolves trade and migration flows and their combined influence on settlement growth and decline. I explore how the balance of costs and benefits of each type of interaction influence long-term settlement patterns. I find trade flows are the strongest determinant of equilibrium settlement structure, and that migration flows play a more transient role in balancing site hierarchies. This model illustrates how the broad toolkit for spatial interaction modeling developed in geography and economics can increase the precision of quantitative theory building in archaeology, and provides a road-map for connecting mechanistic models to the empirical archaeological record.

Intransitivity, the Spatial Interaction Model, and US Migration Streams

1980 ◽  
Vol 12 (10) ◽  
pp. 1131-1144 ◽  
Author(s):  
M F Goodchild ◽  
T R Smith
Keyword(s):  
Error Term ◽  
Sampling Error ◽  
Spatial Interaction ◽  
Interaction Model ◽  
Interstate Migration ◽  
Interaction Models ◽  
Spatial Interaction Model ◽  
Spatial Interaction Models ◽  
Large Numbers ◽  
Migration Flows

The flows predicted by a large class of spatial interaction models are transitive, yet US migration tables have been shown to contain large numbers of intransitivities. This paper investigates a number of possible conditions under which flows regulated by the spatial interaction model might be observed to be intransitive. A singly constrained gravity model is calibrated for a number of flow tables, and distorted by sampling error, by aggregation over strata, and by an independently distributed error term. Only the last distortion gives the correct bias in the relative abundance of intransitivities in numerical flows and flow probabilities. This conclusion is supported by further simulations using random spatial interaction models. The results of the calibrations of the spatial interaction model using US interstate migration flows, 1935–1970, are given and compared with others previously published.

Interzonal Migration: Some Historical Tests of Spatial-Interaction Models

1978 ◽  
Vol 10 (10) ◽  
pp. 1187-1200 ◽  
Author(s):  
J C H Stillwell
Keyword(s):  
Spatial Variation ◽  
Spatial Interaction ◽  
Interaction Model ◽  
Regional Variations ◽  
Interaction Models ◽  
Spatial Interaction Model ◽  
Spatial Interaction Models ◽  
Disaggregated Data ◽  
Migration Flows ◽  
Decay Parameters

Observed migration and survival flows between counties and between standard regions are used to test alternative calibrations of a doubly constrained spatial-interaction model. Spatial variation in the propensity to migrate over distance is examined in an analysis of zone-specific decay parameters, and two methods of splitting aggregate migration flows according to reason for move are investigated. The results of the model tests for age/sex-disaggregated data underline regional variations in propensities to migrate and in mean distances migrated.

scholarly journals MaBμlS-2: high-precision microlensing modelling for the large-scale survey era

2020 ◽  
Vol 498 (2) ◽  
pp. 2196-2218
Author(s):  
David Specht ◽  
Eamonn Kerins ◽  
Supachai Awiphan ◽  
Annie C Robin
Keyword(s):  
Proper Motion ◽  
Time Scale ◽  
Large Scale ◽  
Near Infrared ◽  
Event Rate ◽  
Structural Features ◽  
Small Scale ◽  
Stellar Kinematics ◽  
Full Account ◽  
Space Telescope

ABSTRACT Galactic microlensing datasets now comprise in excess of 104 events and, with the advent of next-generation microlensing surveys that may be undertaken with facilities such as the Rubin Observatory (formerly LSST) and Roman Space Telescope (formerly WFIRST), this number will increase significantly. So too will the fraction of events with measurable higher order information, such as finite-source effects and lens–source relative proper motion. Analysing such data requires a more sophisticated Galactic microlens modelling approach. We present a new second-generation Manchester–Besançon Microlensing Simulator (MaBμlS-2), which uses a version of the Besançon population synthesis Galactic model that provides good agreement with stellar kinematics observed by the Hubble Space Telescope (HST) towards the bulge. MaBμlS-2 provides high-fidelity signal-to-noise limited maps of the microlensing optical depth, rate and average time-scale towards a 400 deg2 region of the Galactic bulge in several optical to near-infrared pass-bands. The maps take full account of the unresolved stellar background, as well as limb-darkened source profiles. Comparing MaBμlS-2 with the efficiency-corrected OGLE-IV 8000 event sample shows a much improved agreement over the previous version of MaBμlS and succeeds in matching even small-scale structural features in the OGLE-IV event rate map. However, evidence remains for a small underprediction of the event rate per source and overprediction of the time-scale. MaBμlS-2 is available online (www.mabuls.net, Specht & Kerins) to provide on-the-fly maps for user-supplied cuts in survey magnitude, event time-scale and relative proper motion.

Empirically Derived Deterrence Functions for Maximum Performance Spatial Interaction Models

1977 ◽  
Vol 9 (9) ◽  
pp. 1067-1079 ◽  
Author(s):  
S Openshaw ◽  
C J Connolly
Keyword(s):  
Goodness Of Fit ◽  
Spatial Interaction ◽  
Model Performance ◽  
Interaction Model ◽  
Theoretical Research ◽  
Maximum Performance ◽  
Interaction Models ◽  
Spatial Interaction Models ◽  
The Relationship ◽  
Descriptive Models

The relationship between the choice of deterrence function and the goodness of fit of a singly constrained spatial interaction model is examined as a basis for improving model performance. The results show that there is no significant improvement in model goodness of fit until a deterrence-function characterisation is used which is based on a family of functions, with the spatial domain of each function being determined in an approximately optimal manner. These findings are consistent with theoretical research on microlevel trip behaviour and can be used to identify descriptive models which possess maximum levels of performance.

Dynamic Spatial Interaction Models: New Directions

1988 ◽  
Vol 20 (11) ◽  
pp. 1449-1460 ◽  
Author(s):  
P Nijkamp ◽  
A Reggiani
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Spatial Interaction ◽  
Interaction Model ◽  
Interaction Models ◽  
Shopping Centre ◽  
Spatial Interaction Models ◽  
New Directions ◽  
Interaction Research

Spatial interaction models have received a great deal of attention in the past decade. In recent years, various approaches have also been developed to take into account dynamic aspects of spatial interaction models, by means of, for instance, optimal control theory, bifurcation theory, or catastrophe theory. The present paper deals with new directions in dynamic spatial interaction research. The focus is on a general dynamic interaction model analyzed in the framework of optimal control theory. The objective function used is a bicriterion utility model, to be maximized subject to a set of differential equations which bear some resemblance to those used by Wilson in a shopping-centre context. The link between the model presented and a catastrophe type of model is investigated. It is demonstrated that catastrophe behaviour may emerge as a particular case of this optimal control model. Finally, it is shown how external influences (for example, stochastic impacts of the Brownian motion type) affect the optimal trajectory.

Effects of Spatial System Design on Spatial Interaction Models. 1: The Spatial System Definition Problem

1989 ◽  
Vol 21 (1) ◽  
pp. 27-46 ◽  
Author(s):  
S H Putman ◽  
S-H Chung
Keyword(s):  
Goodness Of Fit ◽  
Spatial Interaction ◽  
Interaction Model ◽  
Spatial Aggregation ◽  
Model Parameters ◽  
Interaction Models ◽  
Spatial Interaction Models ◽  
Aggregation Methods ◽  
Future Paper ◽  
Spatial System

Rather little has been published about systematic empirical research on the problem of spatial aggregation and its effects on spatial interaction models. Of the work which has been published, all of it has dealt almost exclusively with single-parameter spatial interaction models. In this article five different aggregation procedures are examined. The experiments were based on the use of a multivariate multiparametric spatial interaction model. A first set of hypotheses tests was performed with respect to the sensitivity of model parameters to spatial aggregation methods. A second set was performed with respect to the sensitivity of model goodness-of-fit to the five spatial aggregation methods. Although questions remain, the results clearly show that the multiparametric model responds well to different aggregation algorithms. Some parameters showed substantial response, as they should, to different zonal aggregations, whereas others are shown to be much less responsive. Further, the results clearly indicate that systematic aggregation procedures generally produce better results than do random procedures. A future paper will continue with a discussion of zone definition criteria, and recommendations will be made with regard to aggregation algorithms.

scholarly journals Cluster Assembly in Hierarchically Collapsing Clouds

2015 ◽  
Vol 12 (S316) ◽  
pp. 196-201
Author(s):  
Enrique Vázquez-Semadeni ◽  
Alejandro González-Samaniego ◽  
Manuel Zamora-Avilés ◽  
Pedro Colín
Keyword(s):  
Molecular Clouds ◽  
Large Scale ◽  
Fractal Structure ◽  
Cluster Formation ◽  
Formation Rate ◽  
Structural Features ◽  
Open Clusters ◽  
Small Scale ◽  
Cluster Assembly ◽  
Scale Free

AbstractWe discuss the mechanism of cluster formation in hierarchically collapsing molecular clouds. Recent evidence, both observational and numerical, suggests that molecular clouds (MCs) may be undergoing global, hierarchical gravitational collapse. The “hierarchical” regime consists of small-scale collapses within larger-scale ones. The latter implies that the star formation rate increases systematically during the early stages of evolution, and occurs via filamentary flows onto “hubs” of higher density, mass, and velocity dispersion, and culminates a few Myr after than the small-scale collapses have started to form stars. In turn, the small-scale collapses occur in clumps embedded in the filaments, and are themselves falling into the larger potential well of the still-ongoing large-scale collapse. The stars formed in the early, small-scale collapses share the infall motion of their parent clumps towards the larger potential trough, so that the filaments feed both gaseous and stellar material to the hubs. This leads to the presence of older stars in a region where new protostars are still forming, to a scale-free or fractal structure of the clusters, in which each unit is composed of smaller-scale ones, and to the eventual merging of the subunits, explaining the observed structural features of open clusters.

scholarly journals Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI

2020 ◽  
Vol 13 (12) ◽  
pp. 6407-6426
Author(s):  
Maurits L. Kooreman ◽  
Piet Stammes ◽  
Victor Trees ◽  
Maarten Sneep ◽  
L. Gijsbert Tilstra ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Effects ◽  
Cloud Model ◽  
Structural Features ◽  
Homogeneous Distribution ◽  
Small Scale ◽  
Retrieval Models ◽  
Cloud Models ◽  
Absorbing Aerosols ◽  
Aerosol Index

Abstract. The ultraviolet (UV) Absorbing Aerosol Index (AAI) is widely used as an indicator for the presence of absorbing aerosols in the atmosphere. Here we consider the TROPOMI AAI based on the 340 nm/380 nm wavelength pair. We investigate the effects of clouds on the AAI observed at small and large scales. The large-scale effects are studied using an aggregate of TROPOMI measurements over an area mostly devoid of absorbing aerosols (Pacific Ocean). The study reveals that several structural features can be distinguished in the AAI, such as the cloud bow, viewing zenith angle dependence, sunglint, and a previously unexplained increase in AAI values at extreme viewing and solar geometries. We explain these features in terms of the bidirectional reflectance distribution function (BRDF) of the scene in combination with the different ratios of diffuse and direct illumination of the surface at 340 and 380 nm. To reduce the dependency on the BRDF and homogenize the AAI distribution across the orbit, we present three different AAI retrieval models: the traditional Lambertian scene model (LSM), a Lambertian cloud model (LCM), and a scattering cloud model (SCM). We perform a model study to assess the propagation of errors in auxiliary databases used in the cloud models. The three models are then applied to the same low-aerosol region. Results show that using the LCM and SCM gives on average a higher AAI than the LSM. Additionally, a more homogeneous distribution is retrieved across the orbit. At the small scale, related to the high spatial resolution of TROPOMI, strong local increases and decreases in AAI are observed in the presence of clouds. The BRDF effect presented here is a first step – more research is needed to explain the small-scale cloud effects on the AAI.

scholarly journals Cooperation in large-scale human societies -- What, if anything, makes it unique, and how did it evolve?

2019 ◽  
Author(s):  
Simon T. Powers ◽  
Carel P. van Schaik ◽  
Laurent Lehmann
Keyword(s):  
Decision Making ◽  
Social Interaction ◽  
Collective Action ◽  
Social Interactions ◽  
Large Scale ◽  
Prosocial Behaviors ◽  
Small Scale ◽  
Individual Decision ◽  
Individual Decision Making ◽  
Self Interest

To resolve the major controversy about why prosocial behaviors persist in large-scale human societies, we propose that two questions need to be answered. First, how do social interactions in small-scale and large-scale societies differ? By reviewing the exchange and collective-action dilemmas in both small-scale and large-scale societies, we show they are not different. Second, are individual decision-making mechanisms driven by self-interest? We extract from the literature three types of individual decision-making mechanism, which differ in their social influence and sensitivity to self-interest, to conclude that humans interacting with non-relatives are largely driven by self-interest. We then ask: what was the key mechanism that allowed prosocial behaviors to continue as societies grew? We show the key role played by new social interaction mechanisms -- change in the rules of exchange and collective-action dilemmas -- devised by the interacting individuals, which allow for self-interested individuals to remain prosocial as societies grow.

scholarly journals Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI

2020 ◽  
Author(s):  
Maurits L. Kooreman ◽  
Piet Stammes ◽  
Victor Trees ◽  
Maarten Sneep ◽  
L. Gijsbert Tilstra ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Effects ◽  
Cloud Model ◽  
Structural Features ◽  
Homogeneous Distribution ◽  
Small Scale ◽  
Retrieval Models ◽  
Cloud Models ◽  
Absorbing Aerosols ◽  
Aerosol Index

Abstract. The ultraviolet (UV) Absorbing Aerosol Index (AAI) is widely used as an indicator for the presence of absorbing aerosols in the atmosphere. Here we consider the TROPOMI AAI based on the 340/380 nm wavelength pair. We investigate the effects of clouds on the AAI observed at small and large scales. The large scale effects are studied using an aggregate of TROPOMI measurements over an area mostly devoid of absorbing aerosols (Pacific Ocean). The study reveals that several structural features can be distinguished in the AAI, such as the cloud bow, viewing zenith angle dependence, sunglint, and a previously unexplained increase in AAI values at extreme viewing and solar geometries. We explain these features in terms of the Bidirectional Reflectance Distribution Function (BRDF) of the scene in combination with the different ratio of diffuse and direct illumination of the surface at 340 and 380 nm. To reduce the dependency on the BRDF and homogenize the AAI distribution across the orbit, we present three different AAI retrieval models: the traditional Lambertian Scene Model (LSM), a Lambertian Cloud Model (LCM), and a Scattering Cloud Model (SCM). We perform a model study to assess the propagation of errors in auxiliary databases used in the cloud models. The three models are then applied to the same low-aerosol region. Results show that using the LCM and SCM gives on average a higher AAI than the LSM. Additionally, a more homogeneous distribution is retrieved across the orbit. At the small scale, related to the high spatial resolution of TROPOMI, strong local increases and decreases in AAI are observed in the presence of clouds. This effect was not observed in previous instruments with larger ground pixels such as GOME-2 and OMI. More research is needed to explain these small scale effects.

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