Continuous Monitoring of Environmental Disturbances by Cumulative Sums of Dense SAR Satellite Timeseries

Ruiz-Ramos, Javier (2023). Continuous Monitoring of Environmental Disturbances by Cumulative Sums of Dense SAR Satellite Timeseries. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.00015d6b

Abstract

Climate change together with growing socio-economic pressures are leading to a significant increase in alterations to natural ecosystems. The alteration of natural cycles and dynamics through the direct destruction or continuous degradation, are threatening the conservation of these natural spaces on a global scale. Satellite remote sensing is a suitable solution for large-scale monitoring and evaluation of natural landscapes under threat, as it provides a consistent source of information for both historical and updated environmental studies. However, most current remote sensing-based environmental monitoring tools still present certain limitations which hinder access to continuous and real-time information. The design and development of new methods and approaches to environmental remote sensing is required to mitigate the current environmental degradation trends.

This thesis analyses the current challenges associated with environmental monitoring to focus on the development of new change detection methods applied to the study of environmental disturbances in highly dynamic natural ecosystems. By exploiting the frequent monitoring capabilities of Synthetic Aperture Radar (SAR) dense timeseries, this research introduces new approaches based on Cumulative Sum (CuSum) strategies for continuous and near-real-time investigation. These approaches have been applied to monitor permanent and cyclical disturbances in highly threatened forest and wetland ecosystems.

The main scientific contribution of this thesis is the introduction of three novel SAR-based change detection approaches capable of exploiting dense satellite imagery time series for continuous and near-real-time monitoring. The outcome of this research provides environmental managers with a fully operational alternative tool capable of rapid and continuous monitoring of environmental dynamics.

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