Hook Hua

Rapid Damage Mapping for the 2015 Mw 7.8 Gorkha Earthquake Using Synthetic Aperture Radar Data from COSMO–SkyMed and ALOS-2 Satellites

The 25 April 2015 M_w 7.8 Gorkha earthquake caused more than 8000 fatalities and widespread building damage in central Nepal. The Italian Space Agency’s COSMO–SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area four days after the earthquake and the Japan Aerospace Exploration Agency’s Advanced Land Observing Satellite-2 SAR satellite for larger area nine days after the mainshock. We used these radar observations and rapidly produced damage proxy maps (DPMs) derived from temporal changes in Interferometric SAR coherence. Our DPMs were qualitatively validated through comparison with independent damage analyses by the National Geospatial-Intelligence Agency and the United Nations Institute for Training and Research’s United Nations Operational Satellite Applications Programme, and based on our own visual inspection of DigitalGlobe’s WorldView optical pre- versus postevent imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

Evolutionary computing for spacecraft power subsystem design search and optimization

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance simulation in a parallel processing environment. Using this method, engineers can trade off subsystem goals of mass, cost and performance then automatically size power elements based on their anticipated performance. Our results show that this approach has the potential to improve the space system trade study process.

Temporal investment strategy to enable JPL future space missions

The Jet Propulsion Laboratory (JPL) formulates and conducts deep space missions for NASA (the National Aeronautics and Space Administration). The chief technologist of JPL has the responsibility for strategic planning of the laboratorys advanced technology program to assure that the required technological capabilities to enable future JPL deep space missions are ready as needed; as such he is responsible for the development of a Strategic Plan. As part of the planning effort, he has supported the development of a structured approach to technology prioritization based upon the work of the START (Strategic Assessment of Risk and Technology) team. A major innovation reported here is the addition of a temporal model that supports scheduling of technology development as a function of time. The JPL Strategic Technology Plan divides the required capabilities into 13 strategic themes. The results reported here represent the analysis of an initial seven

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-Based Example

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Therefore, so-called Highly Influential Scientific Assessments HISA such as the U.S. Third National Climate Assessment NCA3 undergo a very rigorous process to ensure transparency and credibility. As an activity to support the transparency of such reports, the U.S. Global Change Research Program has developed the Global Change Information System GCIS. Specifically related to the transparency of NCA3, a recent activity was carried out to trace the provenance as completely as possible for all figures in the NCA3 report that predominantly used NASA data. This paper discusses lessons learned from this activity that traces the provenance of NASA figures in a major HISA-class pdf report.

Recent rapid disaster response products derived from COSMO-Skymed synthetic aperture radar data

The April 25, 2015 M7.8 Gorkha earthquake caused more than 8,000 fatalities and widespread building damage in central Nepal. Four days after the earthquake, the Italian Space Agencys (ASIs) COSMO-SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area. Nine days after the earthquake, the Japan Aerospace Exploration Agencys (JAXAs) ALOS-2 SAR satellite covered larger area. Using these radar observations, we rapidly produced damage proxy maps derived from temporal changes in Interferometric SAR (InSAR) coherence. These maps were qualitatively validated through comparison with independent damage analyses by National Geospatial-Intelligence Agency (NGA) and the UNITARs (United Nations Institute for Training and Researchs) Operational Satellite Applications Programme (UNOSAT), and based on our own visual inspection of DigitalGlobes WorldView optical pre- vs. post-event imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

Custom on-demand and data access services for news merged A-Train data

To simplify access to large and complex satellite data sets for climate analysis and model verification, we developed a web service tool that is used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. A related NASA Energy and Water Cycle Study (NEWS) task has created a merged NEWS Level 2 data from multiple instruments in NASAs A-Train constellation of satellites. We used this data to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for simple and well-designed distributed services so that users can perform analysis in their own familiar computing environments. A Federated OpenSearch capability with full text + space + time search of data products also facilitated interoperability with other data systems.

Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation

With the goal of facilitating communication and cooperation between NASA’s scientific and engineering/design communities, a tool (in the form of a table) is developed which displays the majority of the architectural-parameter trade space under consideration for a given mission, enabling all interested parties to see which sets of constraints would be acceptable for a desired level of science or any other objective. A combination of computer optimization runs and interpolation is employed to enable calculation of the table within a reasonable period of time. Three alternative interpolation methods (radial basis function (RBF), kriging, and regression) are investigated. A hypothetical mission to the Moon’s Schrodinger crater serves as a test case. Kriging, with the lowest average error rate, is judged to be the best interpolation method for this case study, but the more consistent results of the regression method may be preferable in certain other circumstances.

Web services for multiplatform exploratory analysis of level 2 and 3 NEWS merged A-Train data

To simplify access to large and complex satellite data sets for climate analysis and model verification, a service-oriented architecture-based tool was developed to help study long-term and global-scale trends in climate, water and energy cycle, and weather variability. NASAs A-Train satellite constellation set of Level 2 data can be used to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. However, the volume and inhomogeneity of Level 2 data have typically been difficult or time consuming to search and acquire. This tends to result in small-scale or short-term analysis. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for well-designed distributed services so that users can perform analysis in their own familiar computing environments. Voluminous merged Level 2 data containing the various instrument data from the A-Train have recently been generated. Scientists next want to efficiently access selected sets of this merged data and perform their analysis. Server-side capabilities were developed to off-load processing and reduce the amount of data to be transferred to the client. Correspondingly, client-side processing APIs were developed to enable scientists to perform analysis of voluminous server-side data from within their own familiar computing environment (Java, Python, Matlab, IDL, C/C++, and Fortran90).

Mobility productivity impacts on selection of lunar exploration architectures

The productivity of scientific exploration of the Moon and Mars has been significantly improved through the mobility of roving vehicles (rovers) since these vehicles allow scientists to conduct operations well beyond the immediate vicinity of the landing area. This paper reports on a quantitative approach developed to evaluate the productivity of alternative human and robot work-system alternatives for a lunar science mission. A graph-search approach for task planning was used for assigning human and robotic work systems to scientific tasks in order to evaluate the productivity of different mobility options. The results were used to identify the benefits and costs of alternative rover combinations in order to establish guidelines for the roles of the different vehicle types. Pressurized rovers displayed advantages over unpressurized rovers due to enhanced range and duration yielding more science productivity. Multiple pressurized rovers were found to be more productive than multiple unpressurized rovers.