Combining space-based and in-situ measurements to track flooding in Thailand

Chien, Steve; Doubleday, Joshua; McLaren, David; Tran, Daniel; Tanpipat, Veerachai; Leelapatra, Watis; Plermkamon, Vichian; Raghavendra, C.S.; Mandl, Daniel

doi:10.1109/igarss.2011.6050092

Cited by 8 publications

(8 citation statements)

References 3 publications

(1 reference statement)

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“…The availability of sequences of flood extent provided by these methods are now allowing the validation of hydraulic models through a wider dynamic range of an event (Bates et al, 2006;Schumann et al, 2011), rather than just at a single point in the event, as well as being used in near real time to monitor floods (Chien et al, 2011;Auynirundronkool et al, 2012;McLaren et al, 2012). There are many potentially important flow processes active on a floodplain, such as floodplain channels and ditches providing flow connections (Nicholas and Mitchell, 2003) as well as barriers such as embankments, floodplain channel levees and woody debris blocking flow connections (Jeffiries et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Surface water connectivity dynamics of a large scale extreme flood

Trigg

Michaelides

Neal

et al. 2013

Journal of Hydrology

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During flood inundation, river water passes from the main channel into the floodplain through floodplain channels and diffusive overbank flow. This flood water is then distributed within the floodplain depending upon internal connections, barriers and storage, and finally returns back to the river through drainage connections. This surface water connectivity can be complex and is important to many aspects of floodplain functioning, including ecology, sediment movement and flood risk. However, there is currently no accepted way of quantifying this connectivity objectively. We quantify surface water connectivity geostatistically as an objectively measurable characteristic of an observed flood event using a time series of MODIS (Moderate Resolution Imaging Spectroradiometer) surface water product for an extreme large scale flood event (11,000 km 2 flooded area and 6 month duration) during 2011 in Bangkok, Thailand. We develop and apply a new gap filling method that better preserves the dynamic information of the event than simple aggregation methods. Comparison of MODIS results with the higher resolution Earth Observer 1 shows fundamental differences in the resolved connectivity with scale despite similar flooded area. The effect of the passage of the flood wave is directly observable in the river reach, as out-of-bank flooding progresses and increases connectivity along the river during rising water. Around peak flow, there is an increase in connectivity of the floodplain adjacent to the river as low lying areas fill. A step increase in connectivity is correlated with a major levee breach. During recession there is a rapid reduction in along river connectivity in the first week after the peak. This rapid reduction contrasted with a slow decrease in the floodplain connectivity as flooded depressions gradually drained reducing depth, while flood extent remained static for long periods. The connectivity analysis of the threshold in floodplain draining indicates that although spatial flood extent changes are small at this time, there is a reorganisation of the internal surface water connectivity within the flooded area. Thus through this measure of connectivity, we can see a clear structure to the event progression with new insights into flood dynamics that were not anticipated a priori.

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Section: Introductionmentioning

confidence: 99%

Surface water connectivity dynamics of a large scale extreme flood

Trigg

Michaelides

Neal

et al. 2013

Journal of Hydrology

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“…To train the team of rovers using the difference evaluation (in experiments that are completely independent from those in which the team is trained using the global evaluation), we directly apply Eqs. (1)(2)(3)(4), resulting in…”

Section: Rover Evaluation Functionsmentioning

confidence: 99%

“…It also provides new capabilities: temporally synchronized, but spatially separated measurements can be taken to measure ephemeral phenomena that simply could not be captured by a single monolithic rover [1]. Cooperating surface and orbital vehicles can even observe the same phenomena simultaneously [2]. Multiple rovers can cooperate on complex tasks, like construction, surpassing even the most capable single rover.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Multiagent Space Exploration with High-Level Human Feedback

Colby

Yliniemi

Tumer

2016

Journal of Aerospace Information Systems

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Robotic space-exploration missions have always pushed the limits of science and technology, and will continue to do so by their very nature. Such missions are particularly challenging, as they operate in environments with high uncertainty, light-time delays, and high mission costs. Artificial-intelligence-based multiagent systems can alleviate these concerns by 1) creating autonomous multirobot teams that can function in uncertain environments, 2) navigating and operating without time-sensitive commands from Earth-bound scientists, and 3) spreading the mission cost across multiple platforms that will eliminate the danger of total mission loss in the case of a malfunctioning robot. In this work, a novel human in-the-loop cooperative coevolutionary algorithm is presented to train a multirobot system exploring an unknown environment. Autonomous robots learn to make low-level control decisions to maximize scientific data acquisition, whereas human scientists on Earth learn the changing mission profiles and provide highlevel objectives to the robots. Results demonstrate that the algorithm reduces the number of robots needed for a particular performance level tenfold compared to traditional cooperative coevolutionary algorithms for configurations of 10 or more rovers, resulting in significantly lower mission costs. Further, the trained multirobot system is extremely robust to noise, and 10% sensor and actuator noise (with and without sensor bias) has no statistically significant impact on system performance. Finally, the system is extremely robust to robot failures; for any percentage of robot failures between 10 and 90%, the percentage loss in performance is less than the percentage of failed robots.

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“…The solutions developed for single platforms are not necessarily transplantable in this distributed context. A number of studies have recently shown interest for the disaster management, focusing on sensorweb [1] or just on Earth Observation constellations [2], [3], [4], [5]. Most of them faced the problem with classic techniques such as greedy [5], [2], backtracking [3] or simple heuristics.…”

Section: Introductionmentioning

confidence: 99%

EO constellation MPS based on ant colony optimization algorithms

Iacopino

Palmer

Brewer

et al. 2013

2013 6th International Conference on Recent Advances in Space Technologies (RAST)

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Missions involving multiple spacecraft can offer a number of benefits over single platforms. Earth Observation (EO) constellations have the potential to offer critical services for the society such as global monitoring and disaster management. This trend is opening new challenges to the automated Mission Planning & Scheduling (MPS) systems aiming at gaining maximum value from the constellations, by increasing the overall efficiency and the system responsiveness.In this paper, we describe an innovative ground-based automated planning & scheduling system for multiple platforms. The mission used as target for our design is the Disaster Monitoring Constellation, the first Earth Observation constellation of low cost small satellites. The novelty of this project is in designing an MPS as self-organizing multi agent architecture, inspired by Ant Colony Optimization algorithms, offering a system adaptable to the problem changes and able to synchronize the satellites' plans in order to avoid duplications.

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Combining space-based and in-situ measurements to track flooding in Thailand

Cited by 8 publications

References 3 publications

Surface water connectivity dynamics of a large scale extreme flood

Surface water connectivity dynamics of a large scale extreme flood

Autonomous Multiagent Space Exploration with High-Level Human Feedback

EO constellation MPS based on ant colony optimization algorithms

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