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Regional commuting networks are shaped by the distribution of population and employment as well as a host of other socioeconomic and demographic factors. A commuting network type of particular interest consists of residential origins and work destinations as nodes, with the desire lines between them functioning as links. A residential origin has links not only to adjacent towns and the main city, but to work destinations in many other towns as well. Although it is expected that highly connected towns are spatially clustered around the urban core, reflected in positive spatial autocorrelation (PSA), this pattern can be interrupted by origins with seemingly low demonstrated connectivity, reflecting negative spatial autocorrelation (NSA). Principal components analysis leading to regression analysis combined with Moran eigenvector spatial filtering provide an approach for achieving deeper insight into these varied patterns of connectivity in the Pittsburgh, Pennsylvania, region, while taking the role of PSA and NSA into account. It also highlights the role of NSA, which reveals spatial patterns that can at least appear to challenge the notion of Tobler's law that closer things are more related, and a deeper analysis suggests that PSA and NSA jointly characterize connectivity, but not in equal measure. It is argued that actors such as population age, wealth, occupation type, household car ownership, distance from the core, and so on would offer refinement to the predictive ability of density or accessibility in modeling connectivity as represented by degree of node. [ABSTRACT FROM AUTHOR]

Theoretical, methodological, and empirical contributions regarding networks within the context of graph theory constitute a valuable interface between geography and mathematics. Seeking to assess mathematical network geography's past, present, and future, this article addresses such research and literature by discussing new knowledge produced from networked geographic phenomena—especially Erdös collaboration graphs depicting mentorships or authorships among scholars; outlining a brief history of networks in geographical analysis; and couching spatial autocorrelation within its geographic network links. General commentary transitions into examples of Erdös graphs and their implications for collaborations. The narrative also speaks to networked space challenges of established geographic thought (e.g., Tobler's first law of geography), with special reference to contributions by Boots and his coauthors. This article concludes with a treatment of graph theory, networks, and spatial autocorrelation. [ABSTRACT FROM AUTHOR]

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The aim of this paper is to address the levels of segregation and homogeneity in the spatial distribution experienced by households affected by Multidimensional Poverty in Bogotá, at different scales: on the one hand, the entire capital agglomeration, and, on the other, the 19 localities that comprise it. Additionally, for those localities where levels of segregation are higher, we will identify the presence of statistically significant clusters with high and low concentrations of poor households. This is a purely quantitative investigation, and the necessary information to carry it out has been obtained from the 2018 Population Census, at block scale. Data have been analyzed using a variety of statistical instruments aimed at accounting for different aspects of segregation: Theil and Segregation Index, Location Quotient, and spatial autocorrelation (Moran's I, and LISA clusters). The results indicate, on one hand, that the levels of homogeneity in the spatial distributions of households with Multidimensional Poverty differ among the localities comprising the capital agglomeration; on the other hand, that in those where homogeneity is higher, poor households are affected by higher levels of residential segregation, with non-random spatial distributions showing a clear spatial separation between statistically significant high-high and low-low clusters. [ABSTRACT FROM AUTHOR]

Objective. To estimate the prevalence of anemia in children under five in districts with small or null sample size, and to construct an anemia map at the district level in Peru. Materials and methods. An ecological study was conducted utilizing the data from the Encuesta Demográfica y de Salud Familiar 2022 and the National Census 2017. The association between the prevalence of anemia and auxiliary variables was determined using the spatial Fay-Herriot model. Results. The national prevalence of anemia is 33.6% (95%CI: 32.8-34.4). Departments with severe anemia clusters are Puno, Madre de Dios, Ucayali and Loreto. There is a significant spatial correlation between districts, being stronger in the case of the poorer districts. Higher-altitude districts have higher prevalence of anemia. Districts where the predominant language is Spanish have a lower percentage of anemic children. The variables associated with a good district's infrastructure and access to healthcare services have a negative impact. Conclusions. The spatial Fay-Herriot model is a tool that provides a full perspective on the prevalence of anemia at district level in Peru. Anemia among children under five is an important public health problem, especially in rural areas of the mountainous regions of the central and southern parts of Peru, as well as the Peruvian Amazonia. [ABSTRACT FROM AUTHOR]

En esta investigación se analiza la autocorrelación espacial del precio del suelo en Santiago de Chile para comprobar la existencia de un distrito de alta renta, propio de los modelos de ciudades latinoamericanas. Para ello se aplica el Índice de Moran a un conjunto de 206 zonas de mercado dispuestas en una serie de 131 trimestres entre 1983-2016. Los resultados revelan una alta y estable autocorrelación espacial del precio del suelo, lo que confirma un distrito de alta renta, identificado como Cono de Alta Renta (CAR), localizado en las comunas de mayor ingreso de Santiago.

La lógica de acumulación del actual modelo de desarrollo ha favorecido la aparición y consolidación de procesos sociales de expresión espacial, como la segregación. Este fenómeno describe la disponibilidad y el acceso diferenciado a los bienes y servicios urbanos entre grupos sociales debido a su condición social, étnica o socioeconómica, lo que influye en niveles de empleo, desempeño educativo, deterioro urbanístico y degradación ambiental. En este contexto, el objetivo del artículo fue analizar la segregación socioespacial en el acceso a los bienes socioambientales proporcionados por los espacios verdes públicos (EVP) en una ciudad de tamaño medio, como es el caso de la ciudad de Durango, México. El análisis se basó en el uso de métodos de análisis y estadística espacial que involucraron cinco variables asociadas con los EVP: superficie, porcentaje, número, densidad y nivel socioeconómico de la población. A través de estas variables, se identificó un patrón espacial de segregación que se manifestó en cuatro agrupaciones que influyen en la forma en que se habita, se vive, se produce, se reproduce y se construye la ciudad de Durango.

La Sierra de Guadalupe es el último reducto forestal al norte de la Ciudad de México. Para restaurar su cubierta vegetal, o al menos manejarla, es necesario conocer su desarrollo. Es un sistema con unidad por donde transita la energía en formas diferentes según la vegetación, que es el resultado más evidente de condiciones litológicas, edafológicas, climáticas, geográficas e históricas con intervención humana de diferentes tipos. Se describe el comportamiento de cubierta vegetal en la Sierra de Guadalupe en las últimas décadas a partir de la comparación del área y el perímetro de los mosaicos. También se aplicaron cuatro índices paisajísticos: un enfoque matriz-parche-corredor (Puyravaud, 2003), que expresa el cambio de la cobertura vegetal a partir de la ecuación del interés compuesto (Mikels, 2003), la detección de la fragmentación por la cercanía entre los centros de los mosaicos de cada tipo de vegetación; la relación de la disección de un paisaje, a partir de la similitud de los mosaicos, con círculos de la misma área (Bowen y Burgess, 1981), expresada por la posibilidad de que un organismo se encuentre a otro de su especie estando en sitios aleatorios del paisaje (Jaeger, 2000). Con el análisis de la matriz de transición de Markov se observa la sucesión ecológica de algunos mosaicos y también el cambio de uso de suelo forestal a urbano en la mayor parte de la Sierra. El índice de autocorrelación de Moran permite evaluar qué tan agrupados están los parches, o, dicho de otra manera, qué tan constante es el flujo de energía a través del paisaje. Para determinar los mosaicos se compraron imágenes de 1994 y 2019 de la Sierra de Guadalupe, trazando a mano alzada el perímetro de cada mosaico. Se hicieron visitas de campo a la zona de estudio para relacionar la textura y posición de cada mosaico. Se definió la Sierra de Guadalupe como un conjunto de microcuencas con una extensión de 16 813 ha. En 1994, estaban urbanizadas 8698 ha, para 2019 el concreto había cubierto 1741 ha más. Se han establecido 540 ha de bosque y plantaciones, además de las que 1670 ha que ya existían. El bosque de encino se ha extendido por las cañadas sobre 74 ha. La comunidad vegetal más importante en cuanto a extensión hacia 1994 era el matorral xerófilo, cuando representaba 16.8% de la Sierra. En 2019, el matorral xerófilo con pastizal tenía una extensión de 12.7% del total. El encinar cerrado o abierto, ecosistema más conservado y de crecimiento maduro, cubría 334 ha en 1994 y para 2019 alcanzó 410 ha. En cuanto a las masas forestales artificiales, las plantaciones de eucalipto han sido las más extendidas, pues en 1994 representaban 3.7% y 5.2% en 2019. El índice de Puyvaraud (2003) reveló un incremento de la masa forestal de 1.05% por año. Por supuesto, el dosel de la masa forestal no aumenta realmente a ese ritmo, más bien dichas masas se establecieron hasta que fueron visibles en imagen satelital como un dosel establecido. El índice de cohesión de Jaeger (2000) indica nula probabilidad (tanto en 1994 como en 2019) del encuentro de dos organismos de la misma especie hipotéticamente dispuestos al azar en el paisaje. El índice de disección (Bowen y Burgess, 1981) arroja un valor de 5.84% en 1994 y de 8.42% en 2019, lo que indica que el paisaje se ha vuelto más disperso en 3.42% con respecto a la similitud de un círculo de la misma área que todos los parches, es decir, se ha vuelto de un grano más fino. La matriz de Márkov revela las transiciones más representativas (descartando las transiciones a urbanización). Los pastizales se volvieron matorral xerófilo; los matorrales se convirtieron en bosque heterogéneo y encinar; el matorral xerófilo en plantaciones de eucalipto, los matorrales y pastizales en masas de pirul, y los matorrales y pastizales en bosquetes artificiales de pino, casuarina y cedro blanco. Se encontró una correlación de 0.5 para 1994 y de 0.06 para 2019. En general, la cubierta vegetal se ha visto afectada casi en su totalidad por causas humanas, sea con impacto ambiental negativo, como la construcción de colonias, o impacto positivo, como las reforestaciones. Los índices paisajísticos indican que, salvo las plantaciones de eucalipto, la mayoría de las comunidades forestales se han vuelto mosaicos pequeños, dispersos, y con poca área núcleo, configurando un paisaje de grano fino; asimismo, la retracción de la frontera forestal ha promovido mayor fragmentación.

The current development model's accumulation logic has resulted in the emergence and consolidation of social processes like segregation, leading to di!erentiated access and availability of urban goods and services among social groups based on socioeconomic, ethnic, or societal standing. The current development model's accumulation logic has resulted in the emergence and consolidation of social processes like segregation, leading to di!erentiated access and availability of urban goods and services among social groups based on socioeconomic, ethnic, or societal standing. This disparity impacts employment levels, educational performance, urban decay, and environmental degradation. In this context, the article aims to examine the socio-spatial segregation in the access to socio-environmental amenities provided by public green spaces (EVP) in a medium-sized city, specifically Durango, Mexico. The analysis utilizes spatial analysis and statistical methods that involve five variables associated with EVPs: surface area, percentage, number, density, and the socioeconomic level of the population. A spatial pattern of segregation was identified through these variables, resulting in four clusters that impact how the city of Durango is inhabited, produced, reproduced, lived, and constructed. [ABSTRACT FROM AUTHOR]

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In the western Andes of southern Ecuador, remnants of Andean montane tropical forests (BTMA) deserve to be studied ecologically for their value and conservation purposes. This research aimed to describe the difference in taxonomic and functional parameters of arboreal vegetation and explain its relationship with predictor variables. Predictors of climate, soils and spatial correlation were used to explain the difference in composition, diversity, tree density, biomass and functional traits between two types of BTMA: evergreen montane forest (BSM) and highline evergreen montane forest (BSMA). The difference in species composition was described with ANOSIM and NMDS. Differences in diversity, density, biomass and functional traits were evaluated using mean tests with Student t. The relationship between species composition and predictor variables was analyzed with variance partitioning (VARPART), while tree density, above-ground biomass, and functional traits were analyzed with generalized linear models (MLG). The composition was different between the two types and was explained by climate and spatial correlation. Tree density and above-ground biomass were higher in the BSMA. The weighted average of the leaf area (AF) was higher in BSM, while the specific leaf area (AFE) was higher in the BSMA. The mean annual precipitation (PMA) and mean annual temperature (TMA) explained the composition of the species. The density was explained by the TMA, apparent density (DA) and MO. The aboveground biomass was explained by TMA. The AF was explained by the TMA and DA and the AFE was explained by the PMA. We concluded that the parameters of the vegetation vary in small altitudinal gradients, where there is environmental heterogeneity conditioned by the climate and certain soil variables. [ABSTRACT FROM AUTHOR]

En este artículo se muestran los resultados de medir una de las dimensiones de la segregación socioespacial, la aglomeración. Se analiza la distribución espacial de seis estratos socioeconómicos en 1990, 2000 y 2010. Se utilizaron el índice de Autocorrelación Global de Moran (IGM) para la ciudad y el índice de Autoco-rrelación Local de Moran (LISA) para la agrupación intraurbana de los estratos a nivel de manzana urbana y Áreas Geostadísticas Básicas (AGEB). Se parte de la hipótesis de que el agrupamiento en gran escala de los estratos alto y bajo es una nueva tendencia social y urbana de la ciudad.

Desde un enfoque espacial, se indaga sobre los efectos productivos de las políticas públicas orientadas a promover el desarrollo rural en México en el contexto de la liberalización económica, mediante la combinación de dos métodos cuantitativos: análisis de componentes principales y autocorrelación espacial. Se identificó, durante el periodo 1980-2015, un proceso de reconfiguración productiva, resultado de la reconversión hacia cultivos agrícolas de mayor rentabilidad, dicho proceso se refleja en dos expresiones espaciales: 1) la existencia de aglomeraciones espaciales orientadas en cacao y plantas ornamentales, y 2) la fragmentación espacial del conglomerado agrícola dedicado a la producción de granos básicos.

Objective. To analyze the spatial distribution and temporal trend of hospital discharges associated with ischemic heart disease (IHD) in Chile for the period 2002-2020. Materials and methods. Mixed ecological study. Cases of IHD >=18 years registered in Chile between 2002 and 2020 were included. Cartographic representation at the communal level according to sex and residence. Spatial autocorrelation was used applying local Moran’s I. univariate by sex. Time trend was evaluated using the segmented Poisson (JP) model. Results. 434 061 total cases. The minimum hospitalization rates were 53 x 100 000 inhabitants for males and 32 x 100 000 inhabitants for females. The maximum rates determined correspond to 638 x 100 000 inhabitants for males and 364 x 100 000 inhabitants for females. Counties register Moran’s I. values for men that tend to disperse as the analyzed period progresses (0.247 to 0.334) and in the case of women they tend to cluster (0.244 to 0.223). Trend reflects increasing behavior in the age ranges from 18 to 24 years and from 25 to 34 years for females. Conclusion. There is a transition from low to high rates during the period studied. It is possible to group communes with high values in the central and southern zone of Chile, and low values in the northern zone of the country. The existence of a hospital, on average, affects utilization rates for both genders. [ABSTRACT FROM AUTHOR]

In this article we describe and apply the Fay-Herriot model with spatially correlated random area effects (Pratesi, M., & Salvati, N. (2008)), in order to predict the prevalence of anemia and childhood stunting in Peruvian districts, based on the data from the Demographic and Family Health Survey of the year 2019, which collects data about anemia and childhood stunting for children under the age of 12 years, and the National Census carried out in 2017. Our main objective is to produce reliable predictions for the districts, where sample sizes are too small to provide good direct estimates, and for the districts, which were not included in the sample. The basic Fay-Herriot model (Fay & Herriot, 1979) tackles this problem by incorporating auxiliary information, which is generally available from administrative or census records. The Fay-Herriot model with spatially correlated random area effects, in addition to auxiliary information, incorporates geographic information about the areas, such as latitude and longitude. This permits modeling spatial autocorrelations, which are not unusual in socioeconomic and health surveys. To evaluate the mean square error of the above-mentioned predictors, we use the parametric bootstrap procedure, developed in Molina et al. (2009). [ABSTRACT FROM AUTHOR]

Copyright of Economía, Sociedad y Territorio is the property of El Colegio Mexiquense and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Economía, Sociedad y Territorio is the property of El Colegio Mexiquense and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

En los Andes occidentales del sur del Ecuador existen remanentes de bosques tropicales montanos andinos, BTMA, que merecen ser estudiados ecológicamente para valorarlos y conservarlos. El objetivo de esta investigación fue describir la diferencia de parámetros taxonómicos y funcionales de la vegetación arbórea y, además, explicar su relación con variables predictoras. Se utilizaron predictoras de clima, de suelos y una autocorrelación espacial para explicar las diferencias en la composición, diversidad, densidad arbórea, biomasa y rasgos funcionales entre dos tipos de BTMA: bosque siempreverde montano (BSM) y bosque siempreverde montano alto (BSMA). La diferencia en la composición de especies fue descrita con análisis de similitudes y escalamiento multidimensional no métrico. Las diferencias en la diversidad, densidad, biomasa y rasgos funcionales se evaluaron mediante pruebas de medias con t de Student. La relación entre la composición de especies y variables predictoras fue analizada con partición de varianza, y la densidad arbórea, biomasa aérea y rasgos funcionales, con modelos lineales generalizados. La composición de especies fue diferente entre los dos tipos de bosques. Estas diferencias fueron explicadas por el clima y la autocorrelación espacial. La densidad arbórea y la biomasa aérea fueron superiores en el BSMA. El promedio ponderado del área foliar (AF) fue superior en el BSM, y el área foliar específica (AFE) fue mayor en el BSMA. La composición de especies fue explicada por la precipitación media anual (PMA) y la temperatura media anual (TMA); la densidad arbórea, por la TMA, la densidad aparente (DA) y la materia orgánica; la biomasa arbórea aérea, por la TMA; el AF, por la TMA y la DA, y el AFE, por la PMA. Se concluye que los parámetros de la vegetación varían en gradientes altitudinales pequeños, donde existe heterogeneidad ambiental condicionada por el clima y ciertas variables de los suelos.

La disponibilidad de atributos espaciales hace posible la cuantificación del grado de agrupación o aleatoriedad de una variable en el espacio, ofreciendo así útiles aportes en el análisis exploratorio. En particular, el uso de los índices de autocorrelación espacial permite ahondar en la distribución de una variable tanto a escala global (índice de Moran) como local (LISA), así como la identificación de patrones entre unidades espaciales con nexos de vecindad. Sin embargo, pese a la vasta utilización de dichos índices en campos como ecología y epidemiología, el empleo de estas técnicas en el análisis de variables en contextos inmobiliarios ha sido limitada, aunque cabe señalar que ayuda a definir la importancia del componente espacial en el valor de un inmueble y si existe una relación clara con los inmuebles del entorno. En el contexto del mercado inmobiliario nacional, y dada la importancia del comercio minorista en la ciudad de Madrid, uno de los principales núcleos productivos, es de importancia el uso de dichos índices. Por ello, en este trabajo, se ofrece un análisis exploratorio espacial correspondiente a datos de locales comerciales en venta y alquiler en 2020, período caracterizado por el cierre obligatorio del comercio no esencial y limitaciones posteriores en términos aforo, horario de apertura y cierre. Los resultados muestran patrones entre los 21 distritos que conforman la ciudad, base para el estudio de las rentabilidades brutas de los locales comerciales, que a su vez han sido de los productos inmobiliarios con evolución más favorable en el último año.

The analysis of social inequality in Spanish metropolitan areas is proposed (case studies: Barcelona, Madrid, Seville, Valencia) assuming the limitations of this concept and seeking, from the data offered by official statistical sources, correlations between the demographic structure, income inequality and some booming territorial phenomena such as gentrification and touristification of cities. Likewise, the methodological challenge of combining indicators such as the Gini coefficient and the Quantile ratio is assumed, while at the level of territorial relations the application of the concept of spatial autocorrelation is tested to explain inequality, which implies the resource to the SARAR models. The results are shown in tables and discussed based on the hypotheses, ending with the conclusions and the cited bibliography. This research is expected to advance in the knowledge of inequality in metropolitan contexts and its spatial components. [ABSTRACT FROM AUTHOR]

Inter-state economic and social convergence was analyzed in Mexico’s 32 states during the period 2005-2019. Absolute economic convergence was tested through real income and average real labor income and average hourly real labor income. The variables of life expectancy, survival rate, child survival rate and educational level of workers were used to test for absolute social convergence. In addition, using the spatial dependence technique, Moran’s I, it was found that economic variables related to labor income present a high level of spatial correlation. In contrast, only social variables such as life expectancy and the educational level of workers are spatially correlated. [ABSTRACT FROM AUTHOR]

Do any of the known synergies existing between either geography and art or mathematics and art bridge all three of these disciplines? The geo-humanities and the math-humanities literatures describe only these two individual synergies. A new quantitative geography methodology exploits a sophisticated mathematical concept to analyze remotely sensed satellite images, which, when extended to artistic paintings, indeed spans all three disciplines. The organizing concept is spatial autocorrelation, or the tendency for dis/similar colors and their intensities to cluster in paintings. This article summarizes demonstrations of this contention, with specific applications to da Vinci, Monet, and Rembrandt paintings. Its principal contribution is that, for high geographic resolution digital versions of paintings, a replication constructed with judiciously selected and combined spatial autocorrelation components remarkably closely corresponds with a digital copy of its original source, further generalizing certain recent findings reported in the literature. [ABSTRACT FROM AUTHOR]

The research describes and explains the patterns, costs and limits of daily mobility caused by the urban structure of Ciudad Juarez. The concatenation of classical and contemporary theories of location, urban structure and mobility underpinned the analysis processes and results of this study. Methodologically, Moran's I and Getis-Ord's G spatial autocorrelation techniques were implemented for the analysis of INEGI's economic censuses, which spatially identified the subcenters of total, manufacturing and tertiary employment in the periods 1993, 2004, 2009 and 2014. On the other hand, a two-stage data survey was conducted throughout the city by means of origin-destination surveys, which showed, from a macro scale, mobility patterns in terms of time, distance, origins, destinations, number of trips, transportation preferences, motives, ages and economic costs. At a micro scale, graph theory and network analysis allowed spatial modeling of each intra-urban trip, the results of which are detailed in a Mobility Atlas that includes each of the 64 territorial units into which the city was divided. The research proposes a replicable methodology and provides relevant and current information about the city, useful for other studies, decision making and public policies on urban structuring and mobility. [ABSTRACT FROM AUTHOR]

Un argumento ampliamente difundido en la academia y en la discusión pública es que las elecciones presidenciales peruanas muestran un patrón geográfico de voto claramente definido que contrapone el sur del país a Lima y la costa norte. La presente investigación busca problematizar este argumento a partir de la aplicación de indicadores de autocorrelación espacial y el uso de mapas LISA para analizar las elecciones de 2021 (a nivel provincial y distrital). Los principales hallazgos no descartan del todo las ideas preexistentes, pero añaden una necesaria capa de complejidad al descubrir diferentes tipos de patrones geográficos, cuestionar la existencia de zonas totalmente coherentes e internamente homogéneas en el territorio y, en cierto sentido, añadir a la Amazonía en la discusión.

La investigación describe y explica los patrones, costos y límites de la movilidad cotidiana causados por la estructura urbana de Ciudad Juárez. La concatenación de las teorías clásicas y contemporáneas de localización, estructura urbana y movilidad fundamentaron los procesos de análisis y resultados de este estudio. Metodológicamente se implementaron las técnicas de autocorrelación espacial I de Moran y G de Getis-Ord para el análisis de los censos económicos del INEGI, que identificaron espacialmente los subcentros de empleo total, manufactura y terciario en los periodos 1993, 2004, 2009 y 2014. Por otro lado, se realizó un levantamiento bietápico de datos en toda la ciudad por medio de encuestas origen-destino, las cuales mostraron, desde una escala macro, los patrones de movilidad en términos de tiempo, distancia, orígenes, destinos, cantidad de viajes, preferencias de transporte, motivos, edades y costos económicos. En una escala micro, la teoría de grafos y el análisis de redes permitieron modelar espacialmente cada viaje intraurbano, los resultados se detallan en un Atlas de Movilidad que incluye cada una de las 64 unidades territoriales en que se dividió la ciudad. La investigación propone una metodología replicable, además provee información relevante y actual de la ciudad, útiles para otros estudios, toma de decisiones y políticas públicas de estructuración y movilidad urbana.

Objective. Evaluate spatially and temporally simultaneous presence of clusters of dengue and Zika clinical cases and their relationship with expected dengue transmission risk. Materials and methods. A classification of dengue risk transmission was carried out for whole country, and spatial autocorrelation analyses to identify clusters of confirmed clinical cases of dengue and Zika from 2015 to 2018 was conducted using Moran's Index statistics. Results. Clusters of both diseases were identified in dengue-high risk municipalities at the beginning of the outbreak, but, at the end of the outbreak, Zika clusters occurred in dengue low-risk municipalities. Conclusion. This study identified Zika clusters in low-risk dengue areas suggesting participation of several factors that favor virus introduction and dissemination, such as differences in entomological and control interventions, and the possibility of cross-immunity in the population. [ABSTRACT FROM AUTHOR]

A partir de un conjunto de datos del mercado de la vivienda se desarrolla una evaluación empírica con enfoque econométrico sobre cuál es la significancia estadística de los aspectos críticos mencionados por la literatura sobre la financierización de la vivienda, para así evaluar su impacto sobre su precio para el Gran Santiago entre 2009 y 2019. Los resultados indican que sí existe significancia estadística entre la formación de precios de la vivienda y elementos financieros, como tasas de interés hipotecario, créditos de la vivienda o acciones en bolsa de empresas inmobiliarias. Estos resultados son interpretados espacialmente en cartografías que buscan identificar los lugares de la ciudad donde mejor se expresan estos hallazgos y se identifican los barrios con mayor representatividad espacial de las variables. Se identifica un corredor norte-sur de financierización asociado a infraestructura hospitalaria, desarrollo de retail e infraestructura vial de gran envergadura. Mediante el método de mínimos cuadrados ordinarios y autocorrelación espacial, el artículo visualiza los sectores de la ciudad donde la financierización tiene mayor impacto.

Considering forced displacement as the historical event with the highest number of victims in the Colombian armed conflict, a spatial characterisation of this phenomenon was conducted for the period 1984 - 2016. Official data from the Registro Único de Víctimas and the Centro Nacional de Memoria Histórica were analysed by applying spatial analysis methods namely spatial autocorrelation (Moran's I, Geary's c) and weighted mean centre (centre of gravity). The identified spatial patterns have shown that the phenomenon mainly responds to disputes amongst different armed actors because of territorial control of areas considered geostrategic within the framework of the Colombian armed conflict. In addition, the results of the correlation analysis suggest that forced displacement is motivated by victimising events as forced disappearance, threats, crimes against liberty and sexual integrity, homicide, and massacres. The spatial analysis results are linked to historical and social milestones as well as documented victimising events that contextualise the identified patterns. This article shows through spatial statistics that forced displacement is not a random phenomenon; in contrast it follows a cluster-like spatial pattern that reveals how such phenomenon has affected different areas of Colombia in a more localized way, depending on the period analysed. The analysis identifies as the primary nuclei of displacement the region of Magdalena Medio; the sub-regions of Urabá, Alto Sinú, San Jorge, and Montes de María; the Sierra Nevada de Santa Marta; the Pacific Coast (Litoral Pacífico); and the former zone of détente. Forced displacement is a permanent phenomenon in the Colombian national territory. [ABSTRACT FROM AUTHOR]

This document diagnoses the effects of the Modifiable Areal Unit Problem (MAUP) in the study of the demand for urban freight transport, by means of a comparison of different analysis scales to determine the relevance of working with different levels of detail. It is recommended to analyze the number of retail businesses, because they are the ones that mainly attract urban freight transport, and other variables of a socio-territorial type, considering three different spatial units: basic geostatistical area, electoral section, and regular 500-by-500-meter grids. For each scale, descriptive statistics parameters, correlation between variables, as well as global and local spatial autocorrelation (Moran-LISA's I) were obtained to determine the impact of the MAUP. The results obtained show that the electoral sections do not result in an adequate scale, unless it is used as a complementary scale, since the statistical results indicate a greater variation. However, its cartographic representation allows seeing spatial groupings that are not observed in the other scales, which can be a valuable contribution. In the case of the Basic Geostatistical Area (BGA) scale and the 500-by-500-meter grids, data show less dispersion. The variables analyzed show a greater correlation and present a greater global spatial autocorrelation, which is why it is determined that they may be the most appropriate scales to model the transport of merchandise in the study area. The site that had no discrepancy, regardless of the scale of analysis, was the historic downtown of the city of Toluca, so it can be considered a priority site based on its demand for merchandise and territorial characteristics, where regulation and transport control alternatives can be incorporated, as well as the creation of infrastructure to make deliv-eries more efficient and to mitigate its negative impacts. [ABSTRACT FROM AUTHOR]

Al considerar el desplazamiento forzado como el hecho histórico con mayor número de víctimas en el conflicto armado colombiano, este artículo presenta la caracterización espacial de este fenómeno durante el periodo 1984-2016. Se analizaron principalmente los datos oficiales del Registro Único de Víctimas y del Centro Nacional de Memoria Histórica mediante la aplicación de métodos como la autocorrelación espacial (índice de Moran, coeficiente de Geary) y la media central ponderada (centro de gravedad). Se identificaron patrones espaciales que indican que el fenómeno analizado responde principalmente a la disputa entre diferentes actores armados por el control territorial de áreas valoradas como geoestratégicas en el marco del conflicto armado colombiano. Además, los resultados del análisis de correlación sugieren que el desplazamiento forzado está principalmente motivado por hechos victimizantes como la desaparición forzada, las amenazas, los delitos contra la libertad y la integridad sexual, el homicidio y las masacres. Se vinculan los resultados del análisis espacial con hitos histórico-sociales y hechos victimizantes documentados que contextualizan los patrones identificados. Este artículo muestra a través de la estadística espacial que el desplazamiento forzado no es un fenómeno aleatorio, por el contrario, sigue un patrón espacial tipo clúster que revela cómo ha afectado de forma localizada a diversas zonas de Colombia según el periodo estudiado. Mediante los análisis se determinaron como principales núcleos de afectación la región del Magdalena Medio; las subregiones de Urabá, Alto Sinú, San Jorge y los Montes de María; la Sierra Nevada de Santa Marta; el Litoral Pacífico y la antigua zona de distensión. El desplazamiento forzado es un fenómeno permanente en el territorio colombiano.

Social disadvantage is thought to correlate with and might indeed be compounded by insufficient transport infrastructure. Additionally, the prevalence of pedestrian mode choice for trips is shown to be affected by levels of social disadvantage and vulnerability. For elementary school-age children and their guardians, these relationships could complicate daily mode choice and travel with respect to getting to school. This research explores the spatial dependence of socioeconomic and pedestrian network service indicators through a comparative spatial analysis of pedestrian level of service (LOS; Landis et al. 2001) and social deprivation index (SDI; Butler et al. 2013) across suburban census tracts comprising the Putnam City School District in Oklahoma City, Oklahoma. Results indicate statistically significant clusters where substandard pedestrian LOS and challenging socioeconomic conditions colocate at specific census tracts in the study area, along with significant effects demonstrated under spatial lag regression modeling. Implications for planning and public health are discussed, inclusive of both social (public awareness initiatives, walking school buses) and physical (improvements to the pedestrian environment) intervention. [ABSTRACT FROM AUTHOR]

The main objective of the present study was to examine the spatial association between COVID-19 cases and condensable particulate matter (PM10 and PM2.5) and to assess the impact of population density, the green index, and the number of health care institutions in Bogotá (Colombia). The global (MI) and local (LISA) Moran indices were applied to conduct spatial association analyses. The SHAP-value method was applied to assess impact. The results revealed a moderate positive spatial autocorrelation (MI = 0.303) for PM10 and a weak correlation (MI = 0.159) for PM2.5. The LISA index showed that high-high associations between PMs and COVID-19 cases occurred in the southwest of Bogota while low-low associations occurred in the northeast. The variables that had the most impact were, in order, population density, number of health care institutions, and PM10. It is concluded that there is evidence of a spatial autocorrelation between both PM10 and PM2.5 and COVID-19 cases, especially for PM10. [ABSTRACT FROM AUTHOR]

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade‐offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting. [ABSTRACT FROM AUTHOR]

El objetivo de este artículo es analizar la relación entre la vulnerabilidad ambiental y la mortalidad por causas asociadas a las condiciones medioambientales entre la población de los municipios de Campeche, Chiapas y Tabasco que forman parte de la cuenca del río Usumacinta. Se utilizó un modelo de autocorrelación espacial que permite observar la relación entre el índice de vulnerabilidad ambiental durante 2016, y la tasa de mortalidad por causas asociadas a condiciones medioambientales, variables que interrelacionadas permiten reconocer los efectos del cambio climático en la salud (SSA/INEGI). Se identificó un clúster de municipios con un elevado registro de causas de mortalidad que a su vez se encuentran correlacionados con una elevada vulnerabilidad ambiental a la que está expuesta la población.

El objetivo de este trabajo es analizar los determinantes de la productividad laboral en México a nivel estatal durante el período 2003-2016 usando datos anuales. La técnica GMM es utilizada para estimar un modelo de regresión espacial de datos panel. La especificación del modelo incluye una matriz espacial (W), el rezago espacial de la variable dependiente (ρ), el rezago espacial de los residuales (λ), y el uso de variables instrumento para reducir la endogenidad de la variable violencia. Los resultados indican que la crímenes asociados con el tráfico de drogas producen un efecto negativo en la productividad laboral. Así también, la violencia en estados contiguos produce efectos spillover en la producción por trabajador en un estado en específico. La inversion pública tiene un efecto positivo y significativo en la productividad laboral mientras que la crisis financiera durante el período 2008-2009 produce un efecto negativo.

In geographical literature, numerous studies have demonstrated the differences that arise if spatial autocorrelation (SAC) is incorporated into a conventional nonspatial modeling procedure, but little is known about when these differences might be magnified. This study addressed this query by conducting two sets of regression modeling for 561 variables representing housing prices, metropolitan industry, health, crime, education, and (un)employment across various parts of the United States: (1) nonspatial ordinary least squares (OLS) using a set of selected independent variables and (2) spatial regression incorporating spatial filters into the nonspatial OLS as additional independent variables. This incorporation generally improved the model outcomes through decreases in residual autocorrelation and Akaike's information criterion (AIC). The degree of improvement correlated positively with the level of SAC inherent in the dependent variables. That is, strongly autocorrelated socioeconomic variables underwent greater decreases in residual autocorrelation and AIC than those variables with weaker SAC. The results imply that spatial modeling outcomes are sensitive to and potentially predictable by the level of SAC possessed by dependent variables. Therefore, the degree of SAC present in a socioeconomic variable can serve as a direct indicator of how much improvement a nonspatial OLS will experience if that SAC is properly accounted for. [ABSTRACT FROM AUTHOR]

This research analyses the factors that could be involved in the insecurity perceived by the inhabitants of 69 neighbourhoods in Barcelona from the possible influence of the adjacent neighbourhoods. A set of variables are constructed from different sources to measure their influence on the insecurity perceived by residents. Ordinary least-squares regression models were replaced by others that consider the spatial dependence of the data. The results show that when controlling for the influence of adjacent neighbourhoods, ethnic heterogeneity, satisfaction with police services, social disorder, and socio-economic status are significantly related with the insecurity perceived in each neighbourhood. However, when spatial autocorrelation is corrected, crime density in the neighbourhood is not related to perceptions of insecurity, nor there is clear evidence that insecurity is affected by crime levels in adjacent neighbourhoods. [ABSTRACT FROM AUTHOR]

The aim of this research is to examine the distribution’s evolution of the industrial sector in the municipalities of Santa Catarina State and its transformations for the years 2002, 2009 and 2016. We used two methodologies to measure the evolution: Principal Component Analysis to build an Industrial Municipal Index (IMI) of Santa Catarina cities, which is used with Spatial Data Analysis. The Moran's I statistics appoint to regions of industrial concentration witch areas are spatially autocorrelated. The results revealed an increase in the IMI average, although in the most industrialized regions there was a reduction, such as in Joinville, Jaraguá do Sul, Blumenau and Brusque. [ABSTRACT FROM AUTHOR]

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The spectacled bear (Ursidae: Tremarctos ornatus) is an emblematic umbrella species and one of the top carnivores in the Andean mountains. It is also listed as vulnerable by IUCN and as endangered by CITES. We analyzed the genetic structure of this species in nine geographical regions representing the three Andean Cordilleras in Colombia. We sequenced six mitochondrial genes in 115 spectacled bears; a subset of these specimens (n = 61) were genotyped at seven nuclear microsatellites. We addressed three objectives: 1) determine the genetic diversity and historical demographic changes of the spectacled bear in Colombia; 2) determine phylogeographic patterns of genetic divergence among spectacled bear populations in Colombia; and 3) estimate the levels of gene flow among different regions of Colombia. Our analyses show evidence of high mitochondrial genetic diversity in spectacled bears, both in Colombia as well as in each of the nine regions, most particularly Norte de Santander, Nariño, and Antioquia-Córdoba. In addition, we detected population expansion in Colombia that occurred around 24,000 years ago, followed by a population decrease during the last 7,000 years, and a sudden expansion in the last 300 years. Phylogenetic analyses showed few well-supported clades, with some haplotypes detected in all the departments and Colombian Andean Cordilleras, and other haplotypes restricted to certain geographical areas (Antioquia, Norte de Santander, Cundinamarca, and Nariño). We detected significant genetic heterogeneity among some departments and among the three Colombian Andean Cordilleras for both mitochondrial and nuclear genes. Nevertheless, the moderate levels of gene flow estimated from F ST statistics suggest that geographical barriers have not been definitive obstacles to the dispersion of the spectacled bear throughout Colombia. Despite these gene flow estimates, significant spatial autocorrelation was detected for spectacled bear in Colombia, where two kinds of spatial patterns were discovered: genetic patches of 144 km of diameter, and isolation by distance among bears separated from 578 to 800 km. The two most northern spectacled bear populations of Colombia (Norte de Santander and Antioquia) also were the two most differentiated. Their distinctiveness may qualify them as distinct Management Units (MUs) in the context of conservation policies for the spectacled bear in Colombia. [ABSTRACT FROM AUTHOR]

The awareness of the need for robust impact evaluations in conservation is growing and statistical matching techniques are increasingly being used to assess the impacts of conservation interventions. Used appropriately matching approaches are powerful tools, but they also pose potential pitfalls. We outlined important considerations and best practice when using matching in conservation science. We identified 3 steps in a matching analysis. First, develop a clear theory of change to inform selection of treatment and controls and that accounts for real‐world complexities and potential spillover effects. Second, select the appropriate covariates and matching approach. Third, assess the quality of the matching by carrying out a series of checks. The second and third steps can be repeated and should be finalized before outcomes are explored. Future conservation impact evaluations could be improved by increased planning of evaluations alongside the intervention, better integration of qualitative methods, considering spillover effects at larger spatial scales, and more publication of preanalysis plans. Implementing these improvements will require more serious engagement of conservation scientists, practitioners, and funders to mainstream robust impact evaluations into conservation. We hope this article will improve the quality of evaluations and help direct future research to continue to improve the approaches on offer. Article Impact statement: The article identifies 3 steps in using matching in conservation impact evaluation, highlighting best practice and areas for improvement. [ABSTRACT FROM AUTHOR]

El propósito de este estudio es identificar los factores que afectan el precio de la habitación hotelera en Antalya y crear un modelo de regresión hedónica. Para este propósito, se han seleccionado 1444 hoteles en Antalya. Puesto que estos hoteles están relacionados espacialmente, se ha propuesto un modelo de regresión espacial. Se aplicó la regresión paso a paso (stepwise) a las variables del análisis espacial. El modelo de regresión hedónica se ha construido según el modelo Lag o de retardo espacial (Spatial Lag Model), revelando que es posible utilizar dicho método en estudios similares.

El objetivo de este trabajo es contrastar el efecto de contagio en el fracaso empresarial como consecuencia de la proximidad geográfica entre empresas del mismo sector. Para ello, desarrollamos una aplicación empírica basada en el análisis de los estadísticos espaciales join-count sobre una muestra de empresas del sector servicios en el municipio de Murcia (España). Los resultados muestran un patrón de autocorrelación espacial significativo, de tal forma que la probabilidad de fracaso de una empresa no solo depende de sus características internas sino también de su proximidad a otras empresas fracasadas. Estos resultados pueden ser un interesante punto de partida para el desarrollo de análisis que incluyan los efectos de la proximidad geográfica entre empresas en la literatura de fracaso empresarial. || This paper aims to contrast the spillover effects in business failure derived from the geographic proximity among firms of the same sector. To get this purpose, we develop an empirical application based on the analysis of the join-count statistics on a sample of firms of service sector located in the municipality of Murcia (Spain). Our results show significant spatial autocorrelation pattern, therefore, the probability of failure in a firm not only depends on its internal characteristics, but also on the situation of failure of its vicinity peer companies. These results can be an interesting starting point in the development of papers which consider the interdependence effects among closer peer companies in business failure literature.

O objetivo deste artigo é apresentar o comportamento espacial-temporal da pandemia da COVID-19 no México, com uma abordagem da análise espacial, de 1 a 26 de Abril de 2020, que inclui parte da fase 2 e parte da fase 3 da pandemia. O método utilizado é o índice Moran e a sua parcela de dispersão e os gráficos LISA (Local Indicator of Spatial Association) são utilizados para analisar a dependência espacial local dos casos pela COVID-19. Os resultados indicam que, durante a fase 2 da pandemia, esta se caracteriza principalmente pelo contágio da comunidade, nas principais áreas metropolitanas. Na terceira fase, o contágio é local, expandindo-se exponencialmente para cerca de 800 casos por dia. Nos Estados centrais mexicanos, Baja California (que faz fronteira com os Estados Unidos da América), Tabasco y Quintana Roo, que registam o maior número de casos. As principais conclusões da análise espacial são que existem grupos ou aglomerados de municípios que são pontos críticos porque registam o maior número de casos, rodeados por municípios com valores elevados; municípios com valores elevados rodeados por municípios com valores baixos; municípios com valores baixos encurralados por municípios com valores elevados; bem como os municípios com valores baixos rodeados por baixos, que, consoante o caso, as políticas e medidas de atenuação devem ser diferenciadas e rigorosas, sem descurar nenhum municipio. [ABSTRACT FROM AUTHOR]

Spatial autocorrelation (SA) techniques were applied to analyze the deaths caused by three types of cancer in Ecuador. One of the aims of these methods is to describe the scale over which spatial patterns of mortalities occur, which may provide suggestions concerning the agents bringing about the patterns. The analysis was carried out using data from the 23 provinces of the country. Applying global spatial autocorrelation techniques as well as local ones (Global Moran's I and Anselin's local I statistics), it was found that in certain regions of the country there is an unusual pattern of the geographical distribution of cancer mortality indicating that a similar geographic structure could be associated with some risk factor. The data used for the study correspond to deaths due to the types of cancer studied for the years 2012 to 2015 and are available from the Statistics Institute of Ecuador. The results should stimulate further research on the possible causes underlying these clusters and associations. [ABSTRACT FROM AUTHOR]

Este artículo es un primer acercamiento al análisis exploratorio territorial del crecimiento económico municipal en México durante el periodo 1999-2009. A través del Análisis Exploratorio de Datos Espaciales (ESDA, por sus siglas en inglés) y el uso de técnicas geo-estadísticas se investiga la importancia de la proximidad espacial en la propagación del crecimiento. Por ello, con una perspectiva espaciotemporal se analiza el fenómeno de la autocorrelación espacial en la identificación de patrones y dinámicas territoriales de crecimiento económico. Finalmente, se localizan los municipios con procesos virtuosos y viciosos de crecimiento o estancamiento, así como aquellos con una resiliencia al crecimiento.