9 research outputs found
Method for landslides detection with semi-automatic procedures: The case in the zone center-east of Cauca department, Colombia
Landslides are a common natural hazard that causes human casualties, but also infrastructure damage and land-use degradation. Therefore, a quantitative assessment of their presence is required by means of detecting and recognizing the potentially unstable areas. This research aims to develop a method supported on semiautomatic methods to detect potential mass movements at a regional scale. Five techniques were studied: Morphometry, SAR interferometry (InSAR), Persistent Scatterer InSAR (PS-InSAR), SAR polarimetry (PolSAR) and NDVI composites of Landsat 5, Landsat 7, and Landsat 8. The case study was chosen within the mid-eastern area of the Cauca state, which is characterised by its mountainous terrain and the presence of slope instabilities, officially registered in the CGS-SIMMA landslide inventory. This inventory revealed that the type `slide' occurred with 77.4% from the entire registries, `fall' with 16.5%, followed by `creeps' with 3%, flows with 2.6%, and `lateral spread' with 0.43%. As a result, we obtained the morphometric variables: slope, CONVI, TWI, landform, which were highly associated with landslides. The effect of a DEM in the processing flow of the InSAR method was similar for the InSAR coherence variable using the DEMs ASTER, PALSAR RTC, Topo-map, and SRTM. Then, a multiInSAR analysis gave displacement velocities in the LOS direction between -10 and 10 mm/year. With the dual-PolSAR analysis (Sentinel-1), VH and VV C-band polarised radar energy emitted median values of backscatters, for landslides, about of -14.5 dB for VH polarisation and -8.5 dB for VV polarisation. Also, L-band fully polarimetric NASA-UAVSAR data allowed to nd the mechanism of dispersion of CGS landslide inventory: 39% for surface scattering, 46.4% for volume dispersion, and 14.6% for double-bounce scattering. The optical remote sensing provided NDVI composites derived from Landsat series between 2012 and 2016, showing that NDVI values between 0.40 and 0.70 had a high correlation to landslides. In summary, we found the highest categories related to landslides by Weight of Evidence method (WofE) for each spaceborne technique applied. Finally, these results were merged to generate the landslide detection model by using the supervised machine learning method of Random Forest. By taking training and test samples, the precision of the detection model was of about 70% for the rotational and translational types.Los deslizamientos son una amenaza natural que causa pérdidas humanas, daños a la infraestructura y degradación del suelo. Una evaluación cuantitativa de su presencia se requiere mediante la detección y el reconocimiento de potenciales áreas inestables. Esta investigación tuvo como alcance desarrollar un método soportado en métodos semi-automáticos para detectar potenciales movimientos en masa a escala regional. Cinco técnicas fueron estudiadas: MorfometrÃa, InterferometrÃa radar, InterferometrÃa con Persistent Scatterers, PolarimetrÃa radar y composiciones del NDVI con los satélites Landsat 5, Landsat 7 y Landsat 8. El caso de estudio se seleccionó dentro de la región intermedia al este del departamento del Cauca, la cual se caracteriza por terreno montañoso y la presencia de inestabilidades de la pendiente oficialmente registrados en el servicio SIMMA del Servicio Geológico Colombiano. Este inventario reveló que el tipo de movimiento deslizamiento ocurrió con una frecuencia relativa de 77.4%, caidos con el 16.5% de los casos y reptaciones con 3%, flujos con 2.6% y propagación lateral con 0.43%. Como resultado, se obtuvo las variables morfométricas: pendiente, convergencia, Ãndice topográfico de humedad y forma del terreno altamente asociados con los deslizamientos. El efecto de un DEM en el procesamiento del método InSAR fue similar para la variable coherencia usando los DEMs: ASTER, PAlSAR RTC, Topo-map y SRTM. Un análisis Multi-InSAR estimó velocidades de desplazamiento en dirección de vista del radar entre -10 y 10 mm/año. El análisis de polarimetrÃa dual del Sentinel-1 arrojó valores de retrodispersión promedio de -14.5 dB en la banda VH y -8.5dB en la banda VV. Las cuatro polarimetrÃas del sensor aéreo UAVSAR permitió caracterizar el mecanismo de dispersión del Inventario de Deslizamiento asÃ: 39% en el mecanismo de superficie, 46.4% en el mecanismo de volumen y 14.6% en el mecanismo de doble rebote. La información generada en el rango óptico permitió obtener composiciones de NDVI derivados de la plataforma Landsat entre los años 2012 y 2016, mostrando que el rango entre 0.4 y 0.7 tuvieron una alta asociación con los deslizamientos. En esta investigación se determinaron las categorÃas de las variables de Teledetección más altamente relacionadas con los movimientos en masa mediante el método de Pesos de Evidencias (WofE). Finalmente, estos resultados se fusionaron para generar el modelo de detección de deslizamientos usando el método supervisado de aprendizaje de máquina Random Forest. Tomando muestras aleatorias para entrenar y validar el modelo en una proporción 70:30, el modelo de detección, especialmente los movimientos de tipo rotacional y traslacional fueron clasificados con una tasa general de éxito del 70%.Ministerio de CienciasConvocatoria 647 de 2014Research line: Geotechnics and Geoenvironmental HazardDoctorad
Método para la caracterización de las formas del terreno en zonas de montaña utilizando Modelos Digitales de Elevación. Caso: Departamento del Cauca
Se desarrolló un método para diferenciar, delimitar, caracterizar y representar cartográfiamente las formas del terreno en zonas de montaña. Se evaluaron los DEMs SRTM de resoluciones espaciales aproximadas de 31 m y 92 m, y el DEM-ASTER de 31 m de resolución, éste último en el área de estudio mostró datos locales erróneos por lo que el análisis de exactitud vertical con enfoque geoestadÃstico, comparación con curvas de nivel a 1:25000 y 1:10000 y puntos de control GPS indicó que el DEM-SRTM de 31 m, era el que mejor cumplÃa la tolerancia máxima de exactitud vertical. Se analizaron criterios y metodologÃas con sus algoritmos para extraer automáticamente las formas del terreno, desde la obtención de elementos básicos del terreno, el análisis del elemento en el contexto paisajÃstico, superposición de parámetros mediante álgebra de mapas y clasificación no supervisada mediante agrupación k-means; algunos implementados en software propietario y otros en software libre. Se calcularon parámetros del terreno locales y regionales, y se analizaron sus distribuciones de manera univariada y multivariada, ésta última permitió seleccionar un conjunto de ellos con la menor redundancia para implementar un método de clasificación no supervisada. La clasificación no supervisada implementada en una zona centro oriental del departamento del Cauca, Colombia, permitió encontrar 12 clases de formas del terreno a partir de parámetros como el Ãndice de convergencia, el Ãndice topográfico de humedad, la profundidad de los valles, la insolación solar y la elevación misma, con un coeficiente de similaridad kappa máxima de 39%, valor bajo pero con un potencial alto para continuar con investigaciones adicionales, de acuerdo con resultados cualitativos encontrados al compararlos con el globo virtual Googleearth y con la leyenda geomorfológica del mapa de suelos oficial para el área de estudio.Abstract.A method was developed to differentiate, define, characterize and represent cartográfiamente landforms in mountain areas. SRTM DEMs were evaluated for approximate spatial resolution of 31 m and 92 m, and the ASTER DEM-31 m resolution, the latter in the study area showed erroneous local data so the vertical accuracy analysis geostatistical approach, compared with contours at 1:25000 and 1:10000 and GPS control points indicated that the DEM-SRTM 31 m, was best served the maximum vertical accuracy tolerance. Criteria and methodologies were analyzed with algorithms to automatically extract landforms, from obtaining basic elements of the terrain, the analysis of the element in the landscape context, overlapping parameters using map algebra and unsupervised classification using k-means clustering and some implemented in proprietary software and other free software. Parameters were calculated from the local and regional area, and their distributions were analyzed as univariate and multivariate latter allowed to select a set of them with less redundancy to implement a method of unsupervised classification. The unsupervised classification implemented in eastern central area of Cauca, Colombia, allowed to find 12 kinds of landforms based on parameters such as the rate of convergence, the topographic wetness index, the depth of the valleys, solar insolation and the same elevation, with a kappa coefficient of similarity of 39% maximum, low value but with a high potential for additional investigations continue, according to qualitative results found when compared to the virtual globe with GoogleEarth and geomorphological map legend official soil survey area.MaestrÃ
The Potential of Remote Sensing to Assess Conditioning Factors for Landslide Detection at a Regional Scale: The Case in Southeastern Colombia
This landslide detection research applied remote sensing techniques. Morphometry to derive both DEM terrain parameters and land use variables. SAR interferometry (InSAR) for showing that InSAR coherence and InSAR displacement obtained with SRTM DEM 30 m resolution were strongly related to landslides. InSAR coherence values from 0.43 to 0.66 had a high association with landslides. PS-InSAR allowed to estimate terrain velocities in the satellite line-of-sight (LOS) in the range − 10 to 10 mm/year concerning extremely slow landslide displacement rates. SAR polarimetry (PolSAR) was used over L-band UAVSAR quad-pol data, obtaining the scattering mechanism of volume and surface retrodispersion more associated with landslides. The optical remote sensing with a multitemporal approach for change detection by multi-year Landsat (5, 7 and 8)-NDVI, showed that NDVI related to landslides had values between 0.42 and 0.72. All the information was combined into a multidimensional grid product and crossed with training data containing a Colombian Geologic Service (CGS) landslide inventory. A detection model was implemented using the Random Forest supervised method relating the training sample of landslides with multidimensional explanatory variables. A test sample with a proportion of 70:30 allowed to find the accuracy of detection of about 70.8% for slides type
Canagliflozin and renal outcomes in type 2 diabetes and nephropathy
BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years
Precision and accuracy of the static GNSS system for surveying networks used in Civil Engineering
A field check was implemented for calibrating surveying equipment. It was geo-referenced with a Total Station Theodolite and by implementing procedures concerning repeatability and reproducibility. We carried out GNSS (Global Navigation Satellite System) static positioning with double frequency equipment, sensitizing occupation times, day times, uncorrected coordinates subjected to a differential correction procedure and type of coordinates obtained. This facilitated an evaluation of precision and accuracy for the GNSS positioning with the static method, which gave a global RMSE (root mean square error) of 1 cm for conditions with no multipath effect and 4 cm for field calibration points close to buildings. Additionally, optimal results for occupation times of 30 minutes were found, and the need to use planar Cartesian coordinates to ensure compatibility with the surveys using electronic measurement of distances, which allows the use of the static GNSS positioning for geo-referencing precise surveying networks, and can be used in different applications in Civil Engineering.Se implementó un campo patrón de verificación de equipos topográficos. Este fue geo-referenciado con un instrumento de estación total y mediante procedimientos de repetibilidad y reproducibilidad. Se realizaron posicionamientos estáticos GNSS (por las siglas en inglés de Global Navigation Satellite System) con equipo doble-frecuencia, sensibilizando el tiempo de ocupación, la hora del dÃa, las coordenadas sin corregir y sometidas al procedimiento de corrección diferencial y el tipo de coordenadas obtenidos. Lo anterior permitió una evaluación de la precisión y exactitud del posicionamiento GNSS con el método estático, encontrándose un error medio cuadrático global de 1 cm para condiciones sin efecto de multi-trayectoria y de 4 cm para los puntos del campo de verificación cercanos a edificios. Adicionalmente se encontraron resultados óptimos para tiempos de ocupación de 30 minutos y la necesidad de utilizar coordenadas planas cartesianas para garantizar la compatibilidad con los levantamientos utilizando la medición electrónica de distancias, lo cual permite utilizar el posicionamiento GNSS estático para georreferenciar redes topográficas de precisión y pueden ser usadas para diferentes aplicaciones en ingenierÃa civil
Determination of landslide susceptibility in linear infrastructure. Case: aqueduct network in Palacé, Popayan (Colombia)
This research aimed to predict the occurrence of mass movements in the aqueduct network of Palacé, in the municipality of Popayan (Colombia). We evaluated the quality of SRTM and ASTER digital terrain models by comparing them with contour lines using a map scale of 1: 25000. The landscape parameters derived from the SRTM-DEM were analyzed with a multivariate procedure using algorithms implemented in free software, along with thematic information of the study area (coverage, distance to faults, rivers and precipitation). We selected non-redundant variables with the non-parametric ACP technique, and obtained a susceptibility prediction model using logistic regression, with two types of variables: dependent (landslides inventory from field observation) and independent (slope, slope length factor, topographic wetness index, flow path length, soil units and rate of convergence) resulting in a susceptibility map, reclassified into categories according to the values of probability. The prediction model could not be quantitatively assessed because of the absence of studies with a semi-detailed scale, but the estimation of the mean square error of elevation, from which the terrain parameters were derived, the level of detail and the performance of the classifier with ROC curve, yielded a zoning consistent with the findings of the field visits.Esta investigación busca predecir la ocurrencia de movimientos en masa en la red de acueducto Palacé, en el municipio de Popayan (Cauca). Se evaluó la calidad de los modelos digitales del terreno SRTM y ASTER, comparándolos con curvas de nivel a escala 1:25000. Los parámetros del terreno, derivados del modelo DEM-SRTM, fueron analizados de forma multivariada mediante algoritmos implementados en software libre, junto con información temática de la zona de estudio (cobertura, distancia a fallas, a los rÃos y la precipitación). Mediante la técnica no paramétrica del ACP se seleccionaron variables no redundantes, y se obtuvo un modelo de predicción de susceptibilidad mediante regresión logÃstica utilizando variables dependientes (inventario de deslizamiento a partir del recorrido de campo) e independientes, correspondientes al terreno: la pendiente, el factor longitud de pendiente, el Ãndice topográfico de humedad, la longitud de ruta de flujo, los suelos y el Ãndice de convergencia. Esto permitió la obtención de un mapa de susceptibilidad que se reclasificó en categorÃas de acuerdo con valores de probabilidad obtenidos. El modelo de predicción no pudo evaluarse cuantitativamente al no haber estudios a escala semi-detallada, pero la estimación del error cuadrático medio de la elevación, desde la cual se derivaron los parámetros del terreno, el nivel de detalle obtenido y el desempeño del clasificador con la curva ROC, arrojó una zonificación concordante con lo encontrado en las visitas de campo realizadas
Precision and accuracy of the static GNSS system for surveying networks used in Civil Engineering
A field check was implemented for calibrating surveying equipment. It was geo-referenced with a Total Station Theodolite and by implementing procedures concerning repeatability and reproducibility. We carried out GNSS (Global Navigation Satellite System) static positioning with double frequency equipment, sensitizing occupation times, day times, uncorrected coordinates subjected to a differential correction procedure and type of coordinates obtained. This facilitated an evaluation of precision and accuracy for the GNSS positioning with the static method, which gave a global RMSE (root mean square error) of 1 cm for conditions with no multipath effect and 4 cm for field calibration points close to buildings. Additionally, optimal results for occupation times of 30 minutes were found, and the need to use planar Cartesian coordinates to ensure compatibility with the surveys using electronic measurement of distances, which allows the use of the static GNSS positioning for geo-referencing precise surveying networks, and can be used in different applications in Civil Engineering
Determination of landslide susceptibility in linear infrastructure. Case: aqueduct network in Palacé, Popayan (Colombia)
This research aimed to predict the occurrence of mass movements in the aqueduct network of Palacé, in the municipality of Popayan (Colombia). We evaluated the quality of SRTM and ASTER digital terrain models by comparing them with contour lines using a map scale of 1: 25000. The landscape parameters derived from the SRTM-DEM were analyzed with a multivariate procedure using algorithms implemented in free software, along with thematic information of the study area (coverage, distance to faults, rivers and precipitation). We selected non-redundant variables with the non-parametric ACP technique, and obtained a susceptibility prediction model using logistic regression, with two types of variables: dependent (landslides inventory from field observation) and independent (slope, slope length factor, topographic wetness index, flow path length, soil units and rate of convergence) resulting in a susceptibility map, reclassified into categories according to the values of probability. The prediction model could not be quantitatively assessed because of the absence of studies with a semi-detailed scale, but the estimation of the mean square error of elevation, from which the terrain parameters were derived, the level of detail and the performance of the classifier with ROC curve, yielded a zoning consistent with the findings of the field visits
Precision and accuracy of the static GNSS system for surveying networks used in Civil Engineering
A field check was implemented for calibrating surveying equipment. It was geo-referenced with a Total Station Theodolite and by implementing procedures concerning repeatability and reproducibility. We carried out GNSS (Global Navigation Satellite System) static positioning with double frequency equipment, sensitizing occupation times, day times, uncorrected coordinates subjected to a differential correction procedure and type of coordinates obtained. This facilitated an evaluation of precision and accuracy for the GNSS positioning with the static method, which gave a global RMSE (root mean square error) of 1 cm for conditions with no multipath effect and 4 cm for field calibration points close to buildings. Additionally, optimal results for occupation times of 30 minutes were found, and the need to use planar Cartesian coordinates to ensure compatibility with the surveys using electronic measurement of distances, which allows the use of the static GNSS positioning for geo-referencing precise surveying networks, and can be used in different applications in Civil Engineering.Se implementó un campo patrón de verificación de equipos topográficos. Este fue geo-referenciado con un instrumento de estación total y mediante procedimientos de repetibilidad y reproducibilidad. Se realizaron posicionamientos estáticos GNSS (por las siglas en inglés de Global Navigation Satellite System) con equipo doble-frecuencia, sensibilizando el tiempo de ocupación, la hora del dÃa, las coordenadas sin corregir y sometidas al procedimiento de corrección diferencial y el tipo de coordenadas obtenidos. Lo anterior permitió una evaluación de la precisión y exactitud del posicionamiento GNSS con el método estático, encontrándose un error medio cuadrático global de 1 cm para condiciones sin efecto de multi-trayectoria y de 4 cm para los puntos del campo de verificación cercanos a edificios. Adicionalmente se encontraron resultados óptimos para tiempos de ocupación de 30 minutos y la necesidad de utilizar coordenadas planas cartesianas para garantizar la compatibilidad con los levantamientos utilizando la medición electrónica de distancias, lo cual permite utilizar el posicionamiento GNSS estático para georreferenciar redes topográficas de precisión y pueden ser usadas para diferentes aplicaciones en ingenierÃa civil