David Mclaren

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

We describe efforts to integrate in-situ sensing, space-borne sensing, hydrological modeling, active control of sensing, and automatic data product generation to enhance monitoring and management of flooding. In our approach, broad coverage sensors and missions such as MODIS, TRMM, and weather satellite information and in-situ weather and river gauging information are all inputs to track flooding via river basin and sub-basin hydrological models. While these inputs can provide significant information as to the major flooding, targetable space measurements can provide better spatial resolution measurements of flooding extent. In order to leverage such assets we automatically task observations in response to automated analysis indications of major flooding. These new measurements are automatically processed and assimilated with the other flooding data. We describe our ongoing efforts to deploy this system to track major flooding events in Thailand.

Space-based Sensorweb monitoring of wildfires in Thailand

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties. We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

Onboard Product Generation on Earth Observing One: A Pathfinder for the Proposed Hyspiri Mission Intelligent Payload Module

The proposed HyspIRI mission is evaluating a X-band Direct Broadcast capability that would enable data to be delivered to ground stations virtually as it is acquired. However the HyspIRI VSWIR and TIR instruments are expected to produce over 800 × 106 bits per second of data while the Direct Broadcast capability is approximately 10 × 106 bits per second for a ~ 80x oversubscription. In order to address this data throughput mismatch a Direct Broadcast concept called the Intelligent Payload Module (IPM) has been developed to determine which data to downlink based on both the type of surface the spacecraft is overlying and onboard processing of the data to detect events. For example, when the spacecraft is overlying polar regions it might downlink a snow/ice product. Additionally the onboard software would search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected. Earth Observing One (EO-1) has served as a test bed and pathfinder for this type of onboard product generation. As part of the Autonomous Sciencecraft (ASE), EO-1 implemented in ίight software the ability to analyze and develop products for a limited swath of the Hyperion hyperspectral instrument onboard the spacecraft. In a series of technology demonstrations that became part of the operational EO-1 system over 5000 science products have been generated onboard EO-1 and down linked via engineering S-band contacts, a routine automated process that continues to this day. We describe the onboard products demonstrated in EO-1 operations and show how they have paved the way for the HyspIRI Intelligent Payload Module concept.

Monitoring Flooding in Thailand Using Earth Observing One in a Sensorweb

The Earth Observing One (EO-1) mission has been a pathfinder in demonstrating autonomous operations paradigms. In 2010-2012 (and continuing), EO-1 has been supporting sensorweb operations to enable autonomous tracking of flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) is used to perform broad-scale monitoring to track flooding at the regional level (500 m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30 m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to relevant authorities in Thailand for use in damage estimation, relief efforts, and damage mitigation. EO-1 has served as a testbed and pathfinder to this type of sensorweb operations. Beginning with EO-1, these techniques for monitoring are being extended to other space sensors (such as Radarsat-2, Landsat, Worldview-2, TRMM) and integrated with hydrological models, and integration with in-situ sensors.

Onboard instrument processing concepts for the HyspIRI mission

Future NASA missions will have instruments that generate enormous amounts of data. We describe an onboard processing mission concept for a possible Direct Broadcast capability for the HyspIRI mission — a mission under consideration for launch in the next decade carrying visible to short wave infrared (VSWIR) and thermal infrared (TIR) instruments. The VSWIR and TIR instruments will produce over 800 × 106 bits per second of data however the Direct Broadcast downlink rate will be approximately 10×106 bits per second, allowing only 1/80th of the data to be rapidly downlinked. Our onboard processing concept under development spectrally and spatially subsamples the data as well as generates science products onboard to enable return of key rapid response science and applications information despite limited downlink bandwidth. This rapid data delivery concept focuses on wildfires and volcanoes as primary applications but also has applications to vegetation, coastal, flooding, dust, and snow/ice applications.

Tractable Goal Selection for Embedded Systems with Oversubscribed Resources

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the replanning that must be performed in a timely manner on the embedded system where computational resources are limited (as in many aerospace systems). In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that can oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a “justin-time” fashion allowing requests to be changed or added at the last minute. This enables shorterresponsecyclesandgreaterautonomyforthesystemundercontrol.Weshowthatthe averagecasecomplexityforupdatingthegoalssetisO(N lgN)andruntimeexecutionisO(N). We perform an empirical analysis on both synthetic data and space operations mission-like scenarios that confirm these performance characteristics. Finally, we show that scaling these performance figures to existing, very limited onboard spacecraft embedded environments (a Mars Reconnaissance Orbiter like environment) appears feasible.