This thesis examines if a protocol can be created using satellite and existing ground-based time series data recorded at Mexico’s most active volcano, Volcán de Colima, over an extended time period (five years), to identify past patterns in the behaviour of the volcano. Thermally anomalous pixels due to volcanic activity are identified on MODIS and GOES satellite images by customizing thresholds in the hybrid approach algorithm to locate pixels with radiance values that exceed the normal background radiance and natural variance at Volcán de Colima. Visual comparison of the resulting thermal anomaly time series with RSEM, mean temperature, and precipitation time series data, and volcanic activity reports yield four common observation types. Furthermore, inspection and comparison of the data sets reveal that additional data requirements and advanced statistical analysis are required to fully characterize past volcanic behaviour for use as a tool to forecast future activity.
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Thesis advisor: Williams-Jones, Glyn
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