Variabilidad espaciotemporal de parámetros biofísicos de calidad del agua integrando datos in-situ y teledetección: caso Laguna Grande San Pedro de la Paz.
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Date
2023
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Universidad de Concepción
Abstract
Este estudio tiene como objetivo desarrollar e implementar una metodología para la estimación de parámetros bio-ópticos en una laguna ubicada en la región del Biobío, en el centro-sur de Chile, mediante el análisis de series temporales de imágenes satelitales Landsat-8, específicamente utilizando el sensor multiespectral OLI. Los parámetros bio-ópticos, es decir, la clorofila-a (mg·m-3) y la turbidez (NTU) también se midieron in-situ sincronizados con los pases del satélite para minimizar el impacto de las distorsiones atmosféricas. Para calibrar las imágenes de satélite, se evaluaron varios métodos de corrección atmosférica (incluidos ACOLITE, C2RCC, iCOR y LaSRC) durante la fase de preprocesamiento de las escenas. A continuación, se compararon las firmas espectrales obtenidas de las escenas para cada modelo de corrección atmosférica con las firmas espectrales adquiridas in-situ en la superficie del agua. En resumen, el modelo ACOLITE resultó ser el que mejor se ajustaba al proceso de calibración. Posteriormente, aprovechamos los datos de reflectancia derivados del modelo ACOLITE para establecer correlaciones entre diversos índices espectrales y datos in-situ. Los modelos empíricos de recuperación (basados en combinaciones de bandas) que mostraron un rendimiento superior, como indican los valores R2 más altos, fueron sometidos a una rigurosa validación estadística y optimización mediante la aplicación de un enfoque de bootstrapping. Nuestro análisis abarcó un espectro de fechas, estaciones y años, lo que nos permitió profundizar en la evolución del estado trófico asociado al lago. Identificamos un llamativo periodo de ocho años (2014-2022) caracterizado por un descenso de la concentración de clorofila-a en el lago, posiblemente atribuible a las medidas gubernamentales adoptadas en la región para la protección y conservación del lago. Los resultados de este estudio inicial sirven de base para la creación de un sistema de seguimiento moderno que mejora los métodos tradicionales basados en mediciones puntuales, ofreciendo una visión holística de los procesos en curso dentro del lago.
This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, in south-central Chile by analyzing time series of Landsat-8 satellite images, specifically using the multispectral OLI sensor. The bio-optical parameters, i.e., chlorophyll-a (mg·m-3) and turbidity (NTU) were also measured in-situ synchronizes with the satellite passes to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction model were then compared with spectral signatures acquired in-situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process. Subsequently, we harnessed the reflectance data derived from the ACOLITE model to establish correlations between various spectral indices and the in-situ data. The empirical retrieval models (based on band combinations) that showed superior performance, as indicated by higher R2 values, were subjected to rigorous statistical validation and optimization by applying a bootstrapping approach. Our analysis covered a spectrum of dates, seasons, and years, which allowed us to delve deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014-2022) characterized by a decline in chlorophyll-a concentration in the lake possibly attributable to governmental measures in the region for the protection and conservation of the lake. The results of this initial study serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.
This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, in south-central Chile by analyzing time series of Landsat-8 satellite images, specifically using the multispectral OLI sensor. The bio-optical parameters, i.e., chlorophyll-a (mg·m-3) and turbidity (NTU) were also measured in-situ synchronizes with the satellite passes to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction model were then compared with spectral signatures acquired in-situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process. Subsequently, we harnessed the reflectance data derived from the ACOLITE model to establish correlations between various spectral indices and the in-situ data. The empirical retrieval models (based on band combinations) that showed superior performance, as indicated by higher R2 values, were subjected to rigorous statistical validation and optimization by applying a bootstrapping approach. Our analysis covered a spectrum of dates, seasons, and years, which allowed us to delve deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014-2022) characterized by a decline in chlorophyll-a concentration in the lake possibly attributable to governmental measures in the region for the protection and conservation of the lake. The results of this initial study serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.
Description
Tesis presentada para optar al grado de Magister en Ciencias Forestales