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Arctic-boreal lakes emit methane (CH4), a powerful greenhouse gas. Recent studies suggest ebullition might be a dominant methane emission pathway in lakes but its drivers are poorly understood. Various predictors of lake methane ebullition have been proposed but are challenging to evaluate owing to different geographical characteristics, field locations, and sample densities. Here we compare large geospatial data sets of lake area, lake perimeter, permafrost, land cover, temperature, soil organic carbon content, depth, and greenness with remotely sensed methane ebullition estimates for 5,143 Alaskan lakes. We find that lake wetland fraction (LWF), a measure of lake wetland and littoral zone area, is a leading predictor of methane ebullition (adj. R2 = 0.211), followed by lake surface area (adj. R2 = 0.201). LWF is inversely correlated with lake area, thus higher wetland fraction in smaller lakes might explain a commonly cited inverse relationship between lake area and methane ebullition. Lake perimeter (adj. R2 = 0.176) and temperature (adj. R2 = 0.157) are moderate predictors of lake ebullition, and soil organic carbon content, permafrost, lake depth, and greenness are weak predictors. The low adjusted R2 values are typical and informative for methane attribution studies. Our leading model, which uses lake area, temperature, and LWF (adj. R2 = 0.325, n = 5,130) performs slightly better than leading multivariate models from similar studies. Our results suggest landscape-scale geospatial analyses can complement smaller field studies, for attributing Arctic-boreal lake methane emissions to readily available environmental variables. [ABSTRACT FROM AUTHOR]

Colombia por sus características geofísicas y ubicación en la zona tropical es propensa a fenómenos de inundación, que sumados a la vulnerabilidad de la red vial y la presencia permanente de población contiguamente a la vía, acrecientan la fragilidad social y económica en los corredores viales. Esta situación se evidencia cuando se presentan colapsos de transitabilidad por inundación, pues el país moviliza la mayoría de sus mercancías por tierra. El conocimiento y sistematización de las condiciones, sociales y económicas en el trazado vial nacional, y la incorporación de estos datos a un modelo espacial replicable, podría ser una alternativa para tomar decisiones orientadas a prevenir el riesgo. En este artículo se presenta el diseño conceptual y metodológico de una propuesta para involucrar los factores socio económicos requeridos en una evaluación del riesgo por inundación en vías utilizando herramientas de análisis espacial en el tramo piloto Ruta 6008 Chiquinquirá-Sáchica (36 km). Se cuantifica un índice global de aspectos socioeconómicos que se relaciona con la vulnerabilidad en tres niveles: local, zonal y regional. Como resultado principal se encuentra que el corredor vial presenta un nivel de vulnerabilidad media-alta, debido a los aspectos de exposición y fragilidad en las condiciones de vivienda y medios de vida.

Geospatial data provides a window to explore traditional statistical modeling and investigate the geographic distribution of data, revealing patterns, connections, and relationships. These spatial analyses play a crucial role in understanding complex problems at the intraurban scale, allowing one or more variables to be associated with the study. In this context, this research examined the spatial correlation between two socioeconomic indicators in Salvador, Bahia: The UrbanEnvironmental Quality Index (IQUASalvador) and the Urban Property and Land Tax (IPTU), focusing on the Barra/Pituba Borough. In univariate and bivariate analyses, exploratory geospatial data techniques were employed to identify the spatial dependence between these variables, including the Global Moran's Index, the Local Indicators of Spatial Association (LISA), and the Moran scatterplot. The results revealed a positive and significant autocorrelation, with confidence levels of 95% and 99%, and specific geospatial patterns in the studied area were identified. This study highlights the role of geospatial analyses as an essential complement to the traditional statistical analysis of municipal socioeconomic data, offering valuable insights for urban planning and public policies. [ABSTRACT FROM AUTHOR]

Copyright of Investigaciones Geograficas is the property of Universidad de Alicante, Instituto Universitario de Geografia 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.)

This research aims to present carbon monoxide (CO) emissions trends from January 2019 to June 2021 in Southeast Asian waters and the South China Sea (SEA-SCS). Using securitization theory, the data obtained from geospatial analysis was the basis for constructing CO as a threat. The results showed high CO density in the region due to economic activities that caused pressure on the marine air environment. Unfortunately, this has not been explicitly discussed in regional maritime cooperation, even though the states and territories bordering these waters are increasingly vulnerable to climate change. This article argues that securitizing CO as a threat represents substantial progress in the environmental- political cooperation in the SCS and surrounding waters. [ABSTRACT FROM AUTHOR]

El principal objetivo de esta investigación es avanzar en la comprensión de las causas que implican a los procesos migratorios producidos en las últimas décadas en el Corredor Seco Mesoamericano. Para ello se analiza una variable estrechamente relacionada como es el cambio de la cobertura del terreno y de los usos del suelo, agudizado por los efectos del cambio climático en esta región, una de las más vulnerables de la Tierra según el último informe del Intergovernmental Panel on Climate Change (IPCC) de 2019. Se han utilizado para ello datos espaciales del Programa Europeo Copernicus y registros históricos de la NASA, y se ha analizado la relación entre la estimación de la población según los modelos GPWv4 y WorldPop y los cambios en la vegetación a partir de datos MODIS para 2015 y 2020. Se discuten los primeros resultados y se exponen conclusiones concordantes con las investigaciones internacionales.

Managing municipal solid waste is one of the most significant challenges for cities in emerging economies, given the increasing level of generation and the low level of recovery. It is a topic of interest for different disciplines, including waste management, logistics, supply chains, Urban Logistics and Circular Economy. The solid waste recovery logistic networks are the ones through which waste is moved, and recovery operations are carried out. The analysis through geographic information systems makes it possible to relate the network operations with the characteristics of the space in which they are developed. A statistical vision also supports this relationship. This article presents the results of an analysis of the recoverable waste recovery logistics network in the Metropolitan Area of the Mexico Valley. The recovery network is made up of enterprises whose activities are the collection and sale of recoverable waste. Thousands of tons of waste are moved through the recovery network: the nodes are micro-enterprises that employ thousands of workers. The network operates under geospatial conditions that characterize its operation, including distribution, spatial concentration, and growth patterns. The analysis with geographic information systems provides a vision of the complexity of the network, for example, the operation of the network at different levels and scales, regularities that denote self-organization, and the presence of nodes that influence the network's structure. [ABSTRACT FROM AUTHOR]

This study analyzes and compares the academic and social segregation by socioeconomic status among the districts of the Metropolitan Lima area, with respect to the student achievement in mathematics, reading and science tests applied during the 2019 School Census in the second grade of secondary education. To measure segregation, it uses the Dissimilarity index, which highlights the importance of private schools, the Mutual Information index that reports on inter-school and intra-school segregation, and the Isolation index that measures the probability of distinguishing students belonging to the same social category. Likewise, Moran's autocorrelation index is presented, which visualizes the existence of socially and academically differentiated conglomerates according to the territorial location of the schools. These indices reveal a heterogeneous structure of segregation whose intensity varies according to the social composition of public and private schools in each district of the area. Geographic location patterns help to understand the effects of proximity and differentiation of social, school and residential profiles, and propose more geospatial interest to better monitor the functioning of schools and promote equality of learning. [ABSTRACT FROM AUTHOR]

Copyright of Migraciones is the property of Universidad Pontificia Comillas, Instituto Universitario de Estudios sobre Migraciones 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.)

Background. Huanglongbing is a lethal disease for citrus, affecting all citrus species, causing young plants that become infected fail to produce and adult plants become unproductive for a period of two to five years. Objective. The objective of this study was to determine the potential areas for the establishment of huanglongbing in Tabasco. Methodology. In order to achieve this objective, the model of maximum entropy (MaxEnt) was used, which is a general purpose machine learning method. For its validation, the Receiver Operating Characteristic (ROC) technique applied in presence-only distribution models was applied. To generate the model, 19 climatic variables taken from Worldclim were used, a soil variable taken from Jiménez et al., (2013) and 195 records of the presence of Candidatus Liberibacter asiaticus detected in plant material were used. Results. The results show that the municipalities of Huimanguillo and Balancán are the areas with the greatest potential distribution of the disease with values greater than 0.7. According to the area under the curve (AUC), the model has a high ability to predict correctly by presenting values of 0.936 in the training data. Implications. The present study could contribute to the planning of surveillance areas for the detection and control of huanglongbing disease. Conclusion. The model obtained is a good approximation of the potential presence of the disease in the state of Tabasco, giving clarity when choosing the surveillance areas for the pathogen and its vector.

En la Baja Edad Media el límite noroccidental del alfoz de Sevilla conformaba una encrucijada de fronteras interiores y exteriores al reino de Castilla. En este espacio en disputa, la Orden del Temple erigiría hacia 1283 la fortaleza de Frexenal (Fregenal de la Sierra) disponiendo en los caminos conducentes a las tierras de realengo afectas al concejo hispalense sendas atalayas satelitales. La detección de la torre de La Figuera o Higuera de Frexenal inserta en las fábricas de la Iglesia Parroquial de Santa Catalina Mártir de Higuera la Real y el análisis geoespacial de visibilidad conjunta con la Atalaya de Don Pedro permiten parametrizar con precisión la complementariedad de sus cuencas visuales respecto de la de Frexenal, conformando un subespacio castral coherente inserto en las demarcaciones meridionales del bailiato templario de Xerez de Badaioz-El Ventoso. Asimismo la localización de los castillos de Cumbres de Enmedio y de Hinojales insertos en las fábricas de sendas Iglesias Parroquiales de San Pedro y de Ntra. Sra. de la Consolación respectivamente, erigidas sobre sus ruinas, permite realizar nuevas aportaciones al conocimiento de las mismas, arrojando luz sobre ciertas incertidumbres historiográficas concernientes a la red castrametal de la «Banda Gallega».

To control the HIV epidemic at the population level, a 90–90–90 target has been proposed for sub-Saharan Africa, whereby 90 percent of people living with HIV (PLH) should know their HIV status, 90 percent of those diagnosed should be receiving antiretroviral therapy (ART), and 90 percent of those on ART should achieve viral suppression (VS). VS occurs when ART reduces the viral load of PLH to an undetectable level with minimal risk of new infections. We present a two-pronged interdisciplinary analysis, combining geospatial and HIV care continuum techniques, to guide treatment interventions toward achieving the 90–90–90 target in Uganda. We conducted spatiotemporal analysis of VS and constructed HIV care continuums for districts using publicly available data from a centralized laboratory of the Ministry of Health, Uganda. Spatial patterns of VS revealed a distinct east–west pattern of low rates and a north–south pattern of high rates with statistically significant clusters of districts with high and low rates in southwestern and eastern Uganda, respectively. VS rates, calculated in a sequential care continuum framework, revealed local variability as well as a significant gap from the 90–90–90 target by districts. Such evident local variability of VS might indicate the importance of regionally targeted interventions for bringing the HIV epidemic to an end. [ABSTRACT FROM AUTHOR]

RESUMEN El objetivo de la investigación fue tipificar y analizar geoespacialmente los escenarios de producción de ovinos del municipio de las Tunas, Cuba y su periferia, como paso previo a la implementación de un Programa de Transferencia Tecnológica. Se analizaron 68 variables (22 cuantitativas y 46 cualitativas) del comportamiento productivo y reproductivo, del manejo, alimentación, estructurales, sociales y edafoclimáticas de 49 escenarios productivos. Con las variables de mayor poder discrimínate resultantes de los análisis previamente realizados, componentes principales ordinarios y componentes principales categóricos, se ejecutaron de manera iterativa varios análisis de conglomerados jerárquicos hasta llegar a la mejor clasificación posible. Se validaron los resultados del análisis de conglomerados con las pruebas Ji cuadrado de Pearson .para las variables cualitativas y análisis de varianza en las cuantitativas. El proceso de conglomeración rindió los mejores resultados con la formación de cuatro tipos de fincas. La ubicación geoespacial de las fincas, según los resultados del análisis de conglomerado indicó que, la mayoría de estas se encontraron en las zonas suburbanas y rurales. En cuanto a la existencia de cuerpos de aguas superficiales, las imágenes revelaron que cuatro escenarios estuvieron próximos a embalses con alguna importancia. El proceso de investigación que se desarrolló permitió definir cuatro tipologías de fincas en el municipio de las Tunas, Cuba y su periferia, con diferencias notables en la cantidad de animales, indicadores productivos, aspectos de manejo - alimentación y sociales. Por otra parte, el análisis geoespacial facilitó la visualización desde una panorámica diferente y amplia, las características de la zona investigada. Se demostró que la complementación de ambas herramientas constituye una alternativa eficaz en el análisis de sistemas productivos agropecuarios, que puede ser útil como paso previo a la implementación de Programas de Transferencia Tecnológicas ABSTRACT The objective of the research was to typify and analyze geospatially the sheep production scenarios of the Municipality of Las Tunas, Cuba and its periphery, as a previous step to the implementation of a Technology Transfer Program. Sixty eight, variables (22 quantitative and 46 qualitative) of productive and reproductive behavior, management, food, structural, social and edaphoclimatic of 49 productive scenarios were analyzed. With the variables with the highest discriminating power resulting from the previously performed analyzes, ordinary main components and categorical main components, several hierarchical cluster analyzes were iteratively executed until reaching the best possible classification. The results of the cluster analysis were validated with Pearson's Chi-square tests for the qualitative variables and analysis of variance in the quantitative ones. The conglomeration process yielded the best results with the formation of four types of farms. The geospatial location of the farms, according to the results of the cluster analysis indicated that, most of these were found in suburban and rural areas. Regarding the existence of surface water bodies, the images revealed that four scenarios were close to reservoirs of some importance. The research process that was developed allowed to define four types of farms in the Municipality of Las Tunas, Cuba and its periphery, with notable differences in the number of animals, productive indicators, management aspects - food and social. On the other hand, the geospatial analysis facilitated the visualization from a different and wide view, the characteristics of the investigated area. It was demonstrated that the complementation of both tools constitutes an effective alternative in the analysis of agricultural production systems, which can be useful as a previous step to the implementation of Technology Transfer Programs.

El uso de los Sistemas de Información Geográfica ha aumentado considerablemente, fundamentado en las potencialidades que tienen para gestionar información geográfica. A pesar de esto, en la rama de la salud su uso aún es limitado pues presentan insuficiencias para realizar estudios de máximo interés para el sector. Se ha identificado que el empleo de los SIG en estudios sobre la distribución espacial de problemas de salud es limitado, sobre todo por las insuficiencias y dispersión de las herramientas existentes para la incorporación de la componente espacial. También se evidencia poca utilización para la regionalización de servicios que permitan incluir variables para lograr calidad de estos desde su diseño. En este trabajo se presentan cuatro técnicas y su realización en una solución informática para realizar análisis geoespacial en estudios salubristas. Las propuestas incluyen: la georreferenciación y análisis de tumores malignos, la estratificación de territorios, la regionalización de servicios y para la geosimulación. Finalmente se realiza un estudio estratificado de las provincias de Cuba según las diez principales causas de muerte para el año 2016 que evidencia la aplicabilidad de la solución.

Urban empty spaces can be understood as those vacant lands waiting to be built. In legal terms, its regime can vary between public and private. This article analyzes the nature of its geospatial distribution, examining the correlation between this urban phenomenon and the socioeconomic inequality of the population of three border cities in northern Mexico (Mexicali, San Luis Río Colorado, and Nuevo Laredo). A descriptive-comparative methodology was implemented based on statistical techniques and digital and physical surveys of the vacant lands in these cities. The results indicate that poverty levels and the number of empty urban spaces are directly related (positively correlated). In conclusion, a comparative discussion is presented between the three cities is presented. Also, the main differences and coincidences identified are pointed out. [ABSTRACT FROM AUTHOR]

Copyright of Revista Cientifica de la Facultade de Veterinaria is the property of Universidad del Zulia, Facultad de Ciencias Veterinarias 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 Revista Avances: Investigación en Ingeniería is the property of Universidad Libre, Facultad de Ingenieria 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.)

In this study, we analyze the structure of paths within two refugee camps (Calais, France, and Zaatari, Jordan) as a preliminary study examining posttraumatic stress disorder (PTSD) stressors within such camps. We do so through a geospatial analysis of intersections and viewsheds within the camps. Given that anxiety, and the avoidance associated with it, is a primary characteristic of PTSD, refugees might prefer built environments with fewer stressors or anxiety triggers. This study provides a baseline for analyzing basic stressors in a way to test whether design supports anxiety-based avoidance. The planned structure of Zaatari shows a high prevalence of spatial PTSD stressors with lower visibility and a more maze-like structure than that of Calais. This suggests a coping strategy taken by refugees to produce a more suitable and less stressing labyrinth structure. To properly treat PTSD in geographical space, we suggest a need for consideration of this in the planning, function, and very existence of refugee camps and settlements. [ABSTRACT FROM AUTHOR]

Recent headlines highlight disparities in childhood lead poisoning in urban areas yet discourse does not address the lack of primary prevention options. Previous geographic information systems (GIS) approaches, concentrated on census tracts or ZIP codes, miss contextual understanding of lead exposure and make intervention impractical. Through the combination of electronic medical record (EMR) data from an urban children's hospital and spatial video geonarrative (SVG), we show how blood lead level researchers, clinicians, and public health planners can become more proactive in prediction and intervention strategies through the development of an environmental lead index (ELI). Kernel density estimation (KDE) clusters of geocoded locations of children with elevated blood lead (EBL), from 2012 to 2014, were identified using GIS. Analyses identify an increased relative risk for African American and Asian patients compared to white patients and Nepali and non-English-speaking patients compared to English-speaking patients. Fine-scale analyses of EBL clusters reveal nuances of exposure and environmental characteristics that are not identifiable at an aggregate level. Initial testing of the ELI was conducted using identified locations of EBL and non-EBL test results. The mean ELI score was higher among EBL parcels, and comparison proportions of ELI variables between EBL and non-EBL parcels found a statistically significant increase in four variables. Preliminary results support the use of the ELI as a predictive tool; further validation is needed. The technology and the method are translatable to other environments and health conditions. [ABSTRACT FROM AUTHOR]

Surface temperature behavior is related to water evaporation in the hydrological cycle, meaning that the alteration of surface temperature can lead to desertification processes and a decrease in water bodies, and it can affect the health of ecosystems. Studying surface temperature in the DRMI Las Camelias, in eastern Antioquia, sheds light on the transformation of the territory as a result of increased deforestation, intensification of productive activities, the tourism boom and population densification. Given that it is now possible to analyze surface temperature patterns over different land covers over time at different scales, this study evaluates surface temperature at point scale with a pyranometer, at local scale using the UAV Phantom 4 and ANAFI Thermal, and at regional scale using Landsat 8 satellite images. We found that at regional level, the variation of the average surface temperature within the DRMI was less than 1 °C, with no clear differentiation between coverages. A difference was found at local level, highlighting the role of vegetation and water, where forests, bamboo groves and streams have an average temperature of approximately 20 °C, which is up to 3 °C lower than pastures, crops or bare land. The patterns at the point and local level coincide, the temperature under the forest canopy is 5 °C lower than in the pastures, and shallow water outcrops maintain a temperature of 18 °C. Thus, recognizing the role of vegetation and water bodies in regulating surface temperature is vital for climate change mitigation, and detailed planning scales are necessary. This study was carried out with the support of the Institute of Environmental Studies - IDEA, Sede Medellín. [ABSTRACT FROM AUTHOR]

As in many studies involving disparate data and methodologies, environmental health risk assessment research is prone to errors and uncertainties. Unfortunately, uncertainties associated with the research findings can seldom be eliminated, and policy decisions often need to be made based on the uncertain findings. Hence methods that can help reduce uncertainties associated with the research findings would be most useful and need to be developed. This article highlights, through a case study, four major sources of uncertainties, which include uncertainties from data, methods of analysis, interpretations of the findings, and reactions to the findings. Five groups of geospatial methods that can help reduce the uncertainties as a result of combinations of the four sources are identified, including methods for visualization and measurement, cluster detection, exposure modeling, scale analysis, and decision support. The article concludes that future effort should focus more on the development of decision tools to enable decision making based on uncertain findings. [ABSTRACT FROM AUTHOR]