Using Taskable Remote Sensing in a Sensor Web for Thailand Flood Monitoring

Abstract

Space-based assets have been integrated into a sensor web to monitor flooding in Thailand. In this approach, the moderate resolution imaging spectrometer data from the Terra and Aqua satellites are used to perform broad-scale monitoring for flood tracking at the regional level ($250\mathrm{m}/\mathrm{pixel}$) to generate flood detections/alerts. Based on these alerts, the Earth Observing-1 (EO-1) mission is autonomously tasked to acquire higher-resolution ($10–30\mathrm{m}/\mathrm{pixel}$) advanced land imager data, and a number of other assets have imagery automatically requested, with yet further assets requested only in a semiautomated fashion. Based on these alerts, these data are then automatically processed to derive products such as surface water extent and volumetric water estimates in shapefile formats to enable interpretation in geographic information systems. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. To date, Terra, Aqua, EO-1, Landsat, Ikonos, WorldView-1, WorldView-2, GeoEye-1, and Radarsat-2 have been used in some fashion in the sensor web. The overall autonomous detection, tasking, data acquisition, and processing sensor web framework are described, as well as ongoing work to extend to in situ sensor networks. How the automatic triggering of targeted higher-resolution observations enables higher temporal and spatial resolution tracking of flooding events is also documented.