Evaluación de métodos de correcciones atmosféricas y sombreado topográfico en imagen Landsat 8 OLI sobre un área montañosa semiárida: Assessment of atmospheric and topographic correction methods in Landsat 8 OLI imagery on a semi-arid mountainous area

Various atmospheric and topographic shading corrections applied to a Landsat 8 OLI satellite image were visually and statistically evaluated, in order to find the best combination of both, to improve its visual quality and thus enable a better interpretation analysis and digital processing a posteriori. The results for the first corrections showed that the LaSCR image is a good option, possibly due to its consideration of the zenith and azimuthal angles of each of the pixels, in contrast to the other methods developed (MODTRAN and QUAC), in addition to this, your choice means saving time in the execution of some other correction process of this type. Regarding the second corrections, the method that showed the best result was that of Minnaert, as it better preserved the reflectance values ​​and decreased the deviation with respect to the images with only atmospheric corrections used in the initial comparisons (excluding QUAC), which was confirmed by the low underestimation or overestimation shown in the visual analysis. Finally, C-Correction applied to QUAC, denoted the worst result by presenting a high mean value and a high variance, making such a combination discarded.Se evaluaron visual y estadísticamente diversas correcciones atmosféricas y de sombreado topográfico aplicadas a una imagen satelital Landsat 8 OLI con el fin de encontrar la mejor combinación de ambas, para mejorar su calidad visual y con ello, posibilitar mejores análisis de interpretación y procesamientos digitales a posteriori. Los resultados para las primeras correcciones mostraron que la imagen con LaSCR resulta una buena opción, dado posiblemente a su consideración de los ángulos cenitales y azimutales de cada uno de los pixeles, en contraste a los otros métodos desarrollados (MODTRAN y QUAC), aunado a ello, su escogencia significa ahorro de tiempo en la ejecución de algún otro proceso de corrección de este tipo. En cuanto a las segundas correcciones, el método que mostró mejor resultado fue Minnaert al preservar mejor los valores de reflectancia y disminuir la desviación estándar con respecto a las imágenes con solo correcciones atmosféricas usadas como referencia de partida (excluyendo QUAC), lo que fue confirmado por la baja infraestimación o sobrestimación mostrada en el análisis visual. Finalmente, C-Correction aplicado sobre QUAC, denotó el peor resultado al presentar un elevado valor de media y una elevada varianza, por lo que hace a dicha combinación, descartable

Determinación del uso de la tierra en la microcuenca torrencial Quebrada Seca, Estado Táchira, Venezuela 2013

The aim of this research was to determinate the land uses presents in the Quebrada Seca torrential micro-watershed, Táchira state, of 2013. Criteria defined by the International Geographic Union (IGU) were used on an image captured by the Miranda satellite (VRSS-1). Through visual interpretation technics, using the TerraAmazon system and the Global Positioning System (GPS) in field visits, 92.46% global precision and 0.8616 kappa index could be obtained from the map. Of this cartography was determined that micro watershed have 62.97% of high tree cover located mainly in the areas with the steepest slope, 18.67% of grasslands, developed in the low slope areas, a 6.49% of agriculture mixed or associated, a 5.10% of sugar cane, and 7.3% conformed by water bodies, concentrated and linear settlement, a land fill, recreational and touristic areas and communication repeater antennas.El objetivo de esta investigación fue determinarlos usos de la tierra presentes en la microcuenca torrencial Quebrada Seca, estado Táchira, en el año 2013. Se emplearon criterios definidos por la Unión Geográfica Internacional (UGI)sobre una imagen del satélite Miranda (VRSS-1).A través de interpretación visual, el sistema TerraAmazon, y el Sistema de Posicionamiento Global (GPS) en visitas a campo, se pudo obtener una cartografía con un92.46% de precisión global y 0.8616de índice de kappa del mapa. De esta cartografía se determinó que la microcuenca posee 62.97% de cobertura vegetal arbórea media y alta ubicada mayoritariamente en las áreas de mayor pendiente, 18.67% de herbazales, desarrolladas en las áreas de pendiente baja, un 6.49% de agricultura mixta o asociada, 5.10% de caña de azúcar y 7.3% conformado por cuerpos de agua, poblamiento concentrado o lineal, un relleno sanitario, áreas de uso recreacional y turístico y antenas repetidoras de comunicación

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Análisis de la deforestación en Venezuela: bases para el establecimiento de una estrategia REDD+

Los bosques a lo largo del tiempo han proporcionado servicios a los seres humanos, desde el suministro de alimentos, fibras, medicamentos, y similares, hasta elementos menos evidentes en nuestras vidas como las influencias culturales y recreativas. Estas actividades han generado tanto procesos de deforestación donde las tierras forestales han pasado a ser superficies no forestales como de degradación, donde los bosques se deterioran por el establecimiento de carreteras rurales, caída de árboles, incendios forestales ó usos locales de la madera. Estos procesos han ocasionado problemas ambientales como el cambio climático, la pérdida de biodiversidad, la sostenibilidad de la agricultura, el sumidero de agua potable ó las alteraciones en el ciclo de carbono. Los impactos de dichos problemas son globales y están siendo considerados por la comunidad científica internacional, mediante el establecimiento de políticas que mitiguen el efecto de dichos impactos. En tal sentido, la Convención Marco de las Naciones Unidas sobre el Cambio Climático (UNFCCC), considerando que los bosques son sumideros importantes de carbono y que su deforestación y degradación producen emisiones considerables de carbono a la atmosfera, ha puesto en marcha el programa de Reducción de Emisiones por Deforestación y Degradación (REDD+), con el objetivo de investigar los elementos técnicos capaces de minimizar estas emisiones, en los países en vía de desarrollo. Venezuela es uno de los diez países tropicales que según la FAO ha poseído mayor tasa de deforestación en las última dos décadas. Situación esta preocupante ya que más del 50% de su territorio está cubierto por bosque, de estos más del 90% se encuentran en la Amazonía venezolana, que representa un 5,6% del total de la Amazonía. Estos datos hacen que Venezuela sea considerada como uno de los 17 países con mayor índice de biodiversidad de la Tierra. Es por ello, que en esta tesis doctoral se planteó como objetivo realizar un análisis de la deforestación en Venezuela, con el fin de generar las bases para el establecimiento de una estrategia REDD+, en el marco de la UNFCCC. Para esto se establecieron cinco capítulos: en el Capítulo I, se identificaron las causas de la deforestación en Venezuela, mediante un estudio retrospectivo, desde la época precolombina hasta nuestros días; en el Capítulo II, se realiza una reconstrucción histórica para evaluar la dinámica de los bosques en Venezuela desde 1920 hasta 2008; en el Capítulo III, se identificaron, las áreas "hot spot" de deforestación en los bosques de Venezuela, áreas que representaron un cambio rápido en la cobertura del bosque en los últimos 5 años (2005-2010); en el Capítulo IV, se determinó cuál de las metodologías disponibles para el monitoreo de pérdidas de bosques tropicales, se adapta mejor a las características de los Llanos venezolanos; y en el Capítulo V, se realizó dentro del marco metodológico del IPCC, un análisis de la deforestación y degradación del bosque, así como una estimación de la cantidad de emisiones de CO2 procedentes de la pérdida de bosques

Identificación de las áreas “hot spot” de deforestación en Venezuela

In this study, remote sensing data and expert opinion were synthesized in order to ascertain the extent of change in Venezuelan forest cover in recent years (2005-2010) and to predict change for the next five years. Using data from the MODIS sensor, two maps were generated for areas of rapid forest cover change. One map was created using automated techniques, whilst the other was based on direct visual interpretation techniques. Both were then validated with Landsat ETM+ images before analysing them to determine the causes behind the changes. This approach enabled us to determine the pattern of deforestation in Venezuela, distributed in patches in different locations. Deforestation was primarily concentrated in the north of the Orinoco River (8.63% of forest), with mean annual rates of 0.72% and 2.95% in the two validation area, higher than the national average of -0.6% for the country as a whole. The main cause during the period studied was farming (47.85%), specifically mixed family farms and extensive livestock production, practiced in 94% of the areas identified. Similarly, the study enabled us to confirm that moderate resolution imaging is a valuable tool at national scale for countries which do not have current vegetation maps.Pages: 2779-278

Comparación de los métodos utilizados en el monitoreo de la deforestación tropical, para la implementación de estrategias REDD+, caso de estudio los Llanos Occidentales Venezolanos

In this research, a comparative analysis of the methods used nowadays to monitor deforestation nationally, regionally, and globally has been done. The goal is to know which one of them adapts better to the tropical environments of Venezuela, and recommend its use in this ecosystem both in the assessment of forest cover loss and the estimation of CO2 emissions, framed into REDD+ strategies. For this study, Caparo Forest Reserve has been selected. This is a low land forests area, with a high dynamic of loss processes. The comparative analysis used multispectral data from Landsat ETM+ 2007 and 2009, and was validated using panchromatic data from SPOT 4 and 5. The results show that forest mapping in 2007 and 2009 was better classified using FRA-RSS - TREES 3 method (Global Precision (GP) of 87.7% and kappa index of 0.72). The second best was CLASlite method (GP 85.3% and kappa 0.70), then PRODES (GP 84.9% and 0.69 kappa), and FSI (GP 84.5% and 0.67 kappa). However, in the validation of deforestation mapping PRODES method gave the best results both in the confusion matrix, and in the linear regression analysis (GP 88.82% and kappa 0.32, 0.49 R2).Pages: 2817-282

Determinación del uso de la tierra en la microcuenca torrencial Quebrada Seca, Estado Táchira, Venezuela 2013

The aim of this research was to determinate the land uses presents in the Quebrada Seca torrential micro-watershed, Táchira state, of 2013. Criteria defined by the International Geographic Union (IGU) were used on an image captured by the Miranda satellite (VRSS-1). Through visual interpretation technics, using the TerraAmazon system and the Global Positioning System (GPS) in field visits, 92.46% global precision and 0.8616 kappa index could be obtained from the map. Of this cartography was determined that micro watershed have 62.97% of high tree cover located mainly in the areas with the steepest slope, 18.67% of grasslands, developed in the low slope areas, a 6.49% of agriculture mixed or associated, a 5.10% of sugar cane, and 7.3% conformed by water bodies, concentrated and linear settlement, a land fill, recreational and touristic areas and communication repeater antennas.El objetivo de esta investigación fue determinarlos usos de la tierra presentes en la microcuenca torrencial Quebrada Seca, estado Táchira, en el año 2013. Se emplearon criterios definidos por la Unión Geográfica Internacional (UGI)sobre una imagen del satélite Miranda (VRSS-1).A través de interpretación visual, el sistema TerraAmazon, y el Sistema de Posicionamiento Global (GPS) en visitas a campo, se pudo obtener una cartografía con un92.46% de precisión global y 0.8616de índice de kappa del mapa. De esta cartografía se determinó que la microcuenca posee 62.97% de cobertura vegetal arbórea media y alta ubicada mayoritariamente en las áreas de mayor pendiente, 18.67% de herbazales, desarrolladas en las áreas de pendiente baja, un 6.49% de agricultura mixta o asociada, 5.10% de caña de azúcar y 7.3% conformado por cuerpos de agua, poblamiento concentrado o lineal, un relleno sanitario, áreas de uso recreacional y turístico y antenas repetidoras de comunicación

La deforestación y sus factores causales en el estado de Sinaloa, México

The objective of this research was to study deforestation and its causes in the state of Sinaloa, Mexico. Using mapping of land use and vegetation in 1993 and 2011 at a scale of 1: 250 000, deforestation was estimated through a technique of detecting changes, and then characterized by consulting experts. Finally, a matrix of change was applied to analyze the losses, gains and transitions and to corroborate cartographically the results obtained by the experts and the detection of changes. The results indicate a deforestation of 126.50 km2/year and an average annual rate of 0.41%. The consultation of experts determined that the main causes of these processes are agricultural expansion and extension of infrastructure, with impacts of 49.40% and 18.8%, respectively. The matrix of change showed that the particular category of rainforest lost 2374.19 km2, on the contrary, seasonal agriculture also increased by 3326.62 km2 and human settlements increased from 191.51 km2 to 623.28 km2.El objetivo de esta investigación fue estudiar la deforestación y sus causas en el estado de Sinaloa, México. Para ello, se utilizó la cartografía de Uso de Suelo y Vegetación del año 1993 y 2011 a escala 1:250 000, con esta se estimó la deforestación mediante una técnica de detección de cambios; posteriormente, se caracterizó la deforestación mediante la consulta a expertos. Por último, se aplicó la matriz de cambios para analizar las pérdidas, ganancias y transiciones y corroborar cartográficamente lo obtenido por los expertos y la detección de cambios. Los resultados indican una deforestación de 126.50 km2/año y una tasa media anual de 0.41%. De la consulta a expertos se determinó que las principales causas de estos procesos son la expansión agrícola y la extensión de infraestructura con un impacto de 49.40% y 18.8%, respectivamente. En cuanto a la matriz de cambios, se determinó que especialmente la categoría de selvas perdió 2374.19 km2, por el contrario, la agricultura de temporal también se extendió 3326.62 km2 y la categoría de asentamientos humanos pasó de tener 191.51 km2 a 623.28 km2

Geospatial Simulation Model of Deforestation and Reforestation Using Multicriteria Evaluation

Deforestation is an anthropic phenomenon that negatively affects the environment and therefore the climate, the carbon cycle, biodiversity and the sustainability of agriculture and drinking water sources. Deforestation is counteracted by reforestation processes, which is caused by the natural regeneration of forests or by the establishment of plantations. The present research is focused on generating a simulation model to predict the deforestation and reforestation for 2030 and 2050 using geospatial analysis techniques and multicriteria evaluation. The case study is the North Pacific Basin, which is one of the areas with the greatest loss of forest cover in Mexico. The results of the spatial analysis of forest dynamics determined that the forest area in 2030 would be 98,713.52 km2, while in 2050 would be 101,239.8 km2. The mean annual deforestation and reforestation expected in the study area is 115 and 193.84 km2, for the 2014–2030 period, while mean annual deforestation and reforestation values of 95 and 221.31 km2 are expected for the 2030–2050 period. Therefore, considering the forest cover predicted by the deforestation and reforestation model, a carbon capture of 16,209.67 ton/C was estimated for the 2014–2030 period and 587,596.01 ton/C for the 2030–2050

Proximate and Underlying Deforestation Causes in a Tropical Basin through Specialized Consultation and Spatial Logistic Regression Modeling

The present study focuses on identifying and describing the possible proximate and underlying causes of deforestation and its factors using the combination of two techniques: (1) specialized consultation and (2) spatial logistic regression modeling. These techniques were implemented to characterize the deforestation process qualitatively and quantitatively, and then to graphically represent the deforestation process from a temporal and spatial point of view. The study area is the North Pacific Basin, Mexico, from 2002 to 2014. The map difference technique was used to obtain deforestation using the land-use and vegetation maps. A survey was carried out to identify the possible proximate and underlying causes of deforestation, with the aid of 44 specialized government officials, researchers, and people who live in the surrounding deforested areas. The results indicated total deforestation of 3938.77 km2 in the study area. The most important proximate deforestation causes were agricultural expansion (53.42%), infrastructure extension (20.21%), and wood extraction (16.17%), and the most important underlying causes were demographic factors (34.85%), economics factors (29.26%), and policy and institutional factors (22.59%). Based on the spatial logistic regression model, the factors with the highest statistical significance were forestry productivity, the slope, the altitude, the distance from population centers with fewer than 2500 inhabitants, the distance from farming areas, and the distance from natural protected areas