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Doggett, T.

Publications and source records attributed to Doggett, T..

Global Geologic Map of Europa

Europa, with its indications of a sub-ice ocean, is of keen interest to astrobiology and planetary geology. Knowledge of the global distribution and timing of Europan geologic units is a key step for the synthesis of data from the Galileo mission, and for the planning of future missions to the satellite. The first geologic map of Europa was produced at a hemisphere scale with low resolution Voyager data. Following the acquisition of higher resolution data by the Galileo mission, researchers have identified surface units and determined sequences of events in relatively small areas of Europa through geologic mapping using images at various resolutions acquired by Galileo's Solid State Imaging camera. These works provided a local to subregional perspective and employed different criteria for the determination and naming of units. Unified guidelines for the identification, mapping and naming of Europan geologic units were put forth by and employed in regional-to-hemispheric scale mapping which is now being expanded into a global geologic map. A global photomosaic of Galileo and Voyager data was used as a basemap for mapping in ArcGIS, following suggested methodology of all-stratigraphy for planetary mapping. The following units have been defined in global mapping and are listed in stratigraphic order from oldest to youngest: ridged plains material, Argadnel Regio unit, dark plains material, lineaments, disrupted plains material, lenticulated plains material and Chaos material.

Doggett, T.↗

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe↗

ASE Floodwater Classifier Development for EO-1 Hyperion Imagery

The objective of this investigation is to develop a prototype floodwater detection algorithm for Hyperion imagery. It will be run autonomously onboard the EO-1 spacecraft under the Autonomous Sciencecraft Experiment (ASE). This effort resulted in the development of two classifiers for floodwater, one of several classifier types that have been developed and will be uploaded to EO-1 in early 2004 in order to detect change related to transient processes such as volcanism, flooding, and ice formation and retreat.

Ip, Felipe↗

Autonomous Sciencecraft Experiment (ASE) Operations on EO-1 in 2004

The Autonomous Sciencecraft Experiment (ASE) has been selected for flight demonstration by NASAs New Millennium Program (NMP) as part of the Space Technology 6 (ST6) mission. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control software, image formation software, and science processing software will be uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 to detect surface modification related to volcanism, ice formation and retreat, and flooding.

Davies, A. G.↗

Autonomous Science on the EO-1 Mission

In mid-2003, we will fly software to detect science events that will drive autonomous scene selectionon board the New Millennium Earth Observing 1 (EO-1) spacecraft. This software will demonstrate the potential for future space missions to use onboard decision-making to detect science events and respond autonomously to capture short-lived science events and to downlink only the highest value science data.

autonomous systems robust execution↗

Autonomous Sciencecraft Experiment (ASE) Test Operations in 2003

NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The Autonomous Sciencecraft Experiment (ASE) has been selected for flight demonstration by NASA s New Millennium Program (NMP) as part of the Space Technology 6 (ST6) mission. ASE is scheduled to fly on the US Air Force Research Laboratory (AFRL) Techsat-21 constellation in 2006. Tech- Sat-21 consists of three satellites flying in a variable-geometry formation in Earth orbit. Each satellite is equipped with X-band Synthetic Aperture Radar, yielding high spatial resolution images (approx. 3 m) of the Earth s surface. The constellation will fly at an altitude of 550 km, in a 35.4 inclination circular orbit, yielding exact repeat-track observations every 13 days. Prior to full deployment, elements of the versatile ASE spacecraft command and control software, image formation software and science processing software will be utilized and tested on two very different platforms in 2003: AirSAR and EO-1 (described below). Advantages of Autonomous Operations: ASE will demonstrate advanced autonomous science data acquisition, processing, and product downlink prioritization, as well as autonomous spacecraft command and control, and fault detection. The advantages of spacecraft autonomy are to future missions include: (a) making the best use of reduced downlink; (b) the overcoming of communication delays through decisionmaking in situ, enabling fast reaction to dynamic events; (c) an increase of science content per byte of returned data; and (d) an avoidance of return of null (no-change/no feature) datasets: if there is no change detectable between two scenes of the same target, there is no need to return the second dataset.

Chien, S.↗