Landslide Susceptibility Analysis Based on Citizen Reports to a 311 system
Abstract
Landslide susceptibility estimates are essential for reducing the risk posed by landslides to social and economic well-being. However, estimates of landslide susceptibility depend on reliable landslide inventories whose production requires extensive field or remote sensing efforts. Inventories are typically not updated through time and thus may not capture the influence of changes in climate and land use. An inventory that may overcome these limitations can be produced from citizen-reports to a nationwide 311 phone and online system that records the location and timing of landslide reports. While there is potential for 311-data to be a tool in guiding landslide susceptibility estimates in areas where the system exists, the associated spatial uncertainties and reporting biases were not yet explored. In this study, we explore the use of a 311-based landslide inventory for landslide susceptibility estimates in Pittsburgh, PA, where landslide risk is among the highest in the nation. To do so, we compare the 311-based inventory to field validated inventories through a multi-pronged approach that combines field validation of 311-reported landslides, probabilistic analysis of the association between landslides and the underlying topographic and environmental factors, and spatial filtering. Our results show that: (a) Approximately 70% of the 311-reported landslides are associated with an identifiable landslide in the field; (b) The spatial uncertainty of the 311-reported landslides is 104 ± 25 meters; (c) 311-reported landslides differ from other landslide inventories in that they are primarily associated with proximity to roads; however, field-correction of 311-reported locations fixes this anomaly; (d) A simple spatial filter, scaled by the uncertainty in landslide location as determined from a subset of the 311 data, can increase the consistency between the 311-reported landslide inventory and field validated inventories. These results suggest that 311-based landslide inventories can improve susceptibility estimates at a relatively low cost and high temporal resolution.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMNH031..07R
- Keywords:
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- 4306 Multihazards;
- NATURAL HAZARDS;
- 4315 Monitoring;
- forecasting;
- prediction;
- NATURAL HAZARDS;
- 4316 Physical modeling;
- NATURAL HAZARDS;
- 4333 Disaster risk analysis and assessment;
- NATURAL HAZARDS