This study presents a methodology to estimate the seven indicators of the Setting and Infrastructure criterion of the UI GreenMetric World University Ranking based on three-dimensional data from a point cloud taken from an unmanned aerial vehicle (UAV). This study also estimated the potential aerial biomass, C and CO2, stored in the green spaces of a university campus using photogrammetric data analyzed in a Geographic Information System (GIS). The method was based on isolating classified point clouds using digital surface models (DSMs) and ground control points (GCPs) considering the canopy height model (CHM), the allometric equation (DBH, p, h), the biomass conversion factor, and carbon dioxide equivalents (CO2-e). The results confirmed that the national models for estimating the potential C reserves in natural forests are very close to reality and that the open space and green areas available to people on campus are adequate. The use of photogrammetric data facilitated the estimation of UI GreenMetric indicators from a highly detailed, low-cost three-dimensional model. The results of a case study revealed that the campus assimilates the CO2 emissions it produces and generates a surplus.
Buenaventura on the Colombian Pacific coast has experienced a wide range of threats, mainly due to the effects of coastal erosion and flooding. Globally, millions of people will experience increased vulnerability in the coming decades due to climate change. The change in the coastline (1986–2020) over time was analyzed with remote sensors and the Digital Shoreline Analysis System (DSAS) in conjunction with GIS. A total of 16 indicators were selected to quantitatively evaluate exposure, sensitivity, and adaptive capacity to construct a composite vulnerability index (COVI). The endpoint rate (EPR) of the change in the coastline was estimated. The results showed that 35% of the study area was stable, 18% of the coastline experienced erosion processes, and 47% experienced accretion. The COVI analysis revealed that coastal watersheds show great spatial heterogeneity; 31.4% of the area had moderate vulnerability levels, 26.5% had low vulnerability levels, and 41.9% had high vulnerability levels. This analysis revealed that the watersheds located in the northern (Málaga Bay) and central (Anchicaya, Cajambre, and Rapposo basins) parts of the coastal zone were more vulnerable than the other areas.
Introducción: La sífilis gestacional (SG) es una enfermedad infecciosa causada por Treponema pallidum, se trasmite de madre a hijo a través de la vía transplacentaria o canal del parto y genera serias consecuencias en la salud del feto/neonato, incluso la muerte. El comportamiento temporo espacial de la transmisión en centros urbanos se determina por la asociación de variables demográficas y sociales. Objetivo: Describir la distribución temporo espacial del riesgo de la SG y los factores asociados a la presencia de conglomerados. Métodos: Estudio combinado de corte transversal y ecológico. Resultados: Se analizaron 1.463 registros notificados al SIVIGILA que pudieron ser geocodificados y se reporto que 41,6 (284%) pertenecían al estrato Bajo – Bajo, 488 (33,4%) al Bajo, 438 (29,9%) medio Bajo, 74 (5,1%) al Medio, 35 (2,4%) Medio Alto y 12 (0,8%) al Alto. Tambien fueron identificados 17 conglomerados en zonas socialmente deprimidas de la ciudad. Conclusiones: determinantes como hacinamiento, consumo de sustancias psicoactivas, desnutrición, población en situación de desplazamiento, pobreza y alcoholismo explicaron la presencia de conglomerados, los cuales tambien estaban condicionados por determinantes sociales como inicio tardío de control prenatal, no diagnóstico oportuno del evento, barreras administrativas y sociales para el inicio del tratamiento.
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