Logistic groups in the Republic of Panama

Abstract

A map of the logistic groups in the Republic of Panama and complementary maps of the distribution of the population density, GDP density, the economic activity 'transport, storage and communications', and the primary and secondary road network are presented. The clusters of territorial groups on each map were analyzed and created using the 'decision tree' data mining method in order to determine territorial groups with similar characteristics, including logistics infrastructure and nodes, socioeconomics and the environmental situation. At the reference scale of 1:800,000 these maps represent a planning tool to decision makers in land use matters. ARTICLE HISTORY

Spatial Analysis of Territorial Connectivity and Accessibility in the Province of Coclé in Panama

“…The province of Coclé contributed 2.48% to Panama's GDP in 2019, with agriculture, livestock, hunting, forestry, transportation, storage, and communications among its most important sectors, which together accounted for 19.4% of its total contribution. Previous studies also indicate that the province of Coclé shares logistical characteristics in terms of its territorial and socio-economic composition with the provinces of Chiriquí and West Panama [59].…”

“…In particular, the Panama Canal has divided the country into differentiable zones from the point of view of territorial development: The first is the interoceanic zone adjacent to the Canal, located within the provinces of Panama and Colon, where the greatest economic activity related to service activities, Pacific and Atlantic port activities, the country's main international airport, the Panama Canal Railway, and the greatest urban development are concentrated, resulting in these provinces accounting for 76.6% of the GDP [87]. In contrast, the rest of the country, which includes the province of Coclé, shows a logistical dualization [88], where the presence of paved and unpaved roads defines territorial development [59], given the absence of development of other logistical infrastructure such as ports, and where less economic development is observed, contributing 23.4% of the GDP by 2020 [87].…”

Use of Bayesian Networks to Analyze Port Variables in Order to Make Sustainable Planning and Management Decision

“…A similar study is written by Cancelas, Flores, Orive [30], in which naive bayes is used with port traffic as the principal variable. In more recent studies [31], Bayesian Networks are used to find the logistic potential of a country, and, in others [32], main variables are defined and virtual scenarios inferences are determined in Figure 1. Sustainability dimensions: main objectives.…”

“…A similar study is written by Cancelas, Flores, Orive [30], in which naive bayes is used with port traffic as the principal variable. In more recent studies [31], Bayesian Networks are used to find the logistic potential of a country, and, in others [32], main variables are defined and virtual scenarios inferences are determined in order to analyse container terminals scenarios using probabilistic graphical models. Furthermore, a K2 algorithm was created to determine relationships between all of the variables that are involved in decision, using a complete cartography by ArcGIS to obtain scores of each variable in [33].…”

Redes bayesianas para la sostenibilidad marítimo portuaria

“…En la planificación del territorio, se han usado los árboles de decisión en aspectos específicos tales como la clasificación de usos de la tierra y land cover (Prasad, Madhavi, 2012;Friedl, Brodley, 1997;Malczewski, 2004;Quijada-Alarcón, González, Camarero y Soler, 2012) o la planificación de la pesca considerando el consumo de combustible, los costes de funcionamiento y los patrones de pesca, de manera tal de optimizar los recursos (Bastardie, Nielsen, Andersen, Eigaard, 2013).…”