R. Lutz

Bio: R. Lutz is an academic researcher from Goddard Space Flight Center. The author has contributed to research in topics: Sensor web & Moderate-resolution imaging spectroradiometer. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Application of real time dynamic Sensor Web measurement techniques to maximize Aura/TES useful science return

Abstract: The Sensor Web characterizes a future observing system concept that has the potential to significantly increase useful science data return. It accomplishes this by intelligently and dynamically reconfiguring the measurement and information processing states of its constituent sensor, computing, and storage nodes. To explore the potential benefits of Sensor Web observing strategies for the Earth science community, the Goddard Space Flight Center is developing software to demonstrate the value of real-time, collaborative, "intelligent data collection" between two formation flying spacecraft that comprise NASA's EOS ''A-Train" constellation: Aqua and Aura. After its planned Summer 2004 launch, Aura, with its Troposphere Emission Spectrometer (TES), is to be inserted into the constellation's orbital plane and "follow" 15 minutes behind Aqua with its Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. MODIS is a nadir pointing multispectral imager, it is always "ON", and its 36 bands can be used to detect clouds. TES is a high-resolution infrared-imaging Fourier transform spectrometer designed primarily to study ozone in the lower atmosphere. Providing spectral coverage in the mid- to thermal IR bands, it is undesirable for TES to make measurements within cloud obscured fields of view. Of particular significance, TES is a pointable instrument: it can be commanded to image any target within 45deg of the local vertical. In this paper, we describe a high performance prototype software system to acquire and process direct readout MODIS data to a Level 2 cloud mask product in real time. Using a predefined list of desired targets, in conjunction with the real time MODIS cloud mask information, the software generates simulated commands and "point" TES to only those targets that are cloud free to demonstrate the value of intelligent data collection measurement techniques. To further refine where within the cloud free regions TES should point, we are also assessing the potential use of atmospheric chemistry models whose outputs may provide an additional set of criteria for high science value target selection. Similar "event-driven" and "model-driven" adaptive observation strategies and dynamic measurement techniques may be applied to future sensor Web Earth- and space-science missions

Method and apparatus for imaging a target using cloud obscuration prediction and detection

Abstract: A method is provided for imaging targets using an unmanned air vehicle. The method comprises the steps of making a determination of cloud obscuration of a target, selecting an imaging sensor based on the cloud obscuration determination, and using the selected imaging sensor to produce an image of the target. An apparatus that performs the method is also provided.

Coordination Through Geospatial Web Service Workflow in the Sensor Web Environment

Abstract: The Sensor Web connects live sensors and Earth Science models (ESM). A workflow is one approach for designing, implementing, and constructing a live link between sensors and ESM. The Sensor Web consists of many individual Web services. A workflow coordinates them to enable bi-directional connectivity between sensors and ESMs. This study uses Business Process Execution Language as the base scripting language to design, author, deploy, and execute workflows. Message-level coordination mechanisms are developed, implemented, and demonstrated in two scenarios-bird migratory modeling and georeferenceable imagery workflow. The advantage of message-level coordination is short-cutting the data flow.

Intelligent Archives in the Context of Knowledge Building Systems: Concepts for the Future

Abstract: The technical objectives are: 1. Formulate concepts and architectures that support data archiving for NASA science research and applications in the 10 to 20 year time frame. 2. Focus on architectural strategies that will support intelligent processes and functions. 3. Identify and characterize science and applications scenarios that drive intelligent archive requirements. 4. Assess technologies and research that will need the development of an intelligent archive. 5. Identify and characterize potential research projects that will be needed to develop and create an intelligent archive.