Nonlinear spectral mixture modeling to estimate water-ice abundance of martian regolith

Icarus ◽  
2019 ◽  
Vol 329 ◽  
pp. 79-87 ◽  
Author(s):  
Szilárd Gyalay ◽  
Eldar Z. Noe Dobrea ◽  
Kathryn Chu ◽  
Karly M. Pitman
Keyword(s):  
Mixture Modeling ◽  
Water Ice ◽  
Martian Regolith ◽  
Spectral Mixture

Surface temperature of Martian regolith with polygonal features: influence of the subsurface water ice

2003 ◽  
Vol 51 (9-10) ◽  
pp. 569-580 ◽  
Author(s):  
Konrad J. Kossacki ◽  
Wojciech J. Markiewicz ◽  
Michael D. Smith
Keyword(s):  
Surface Temperature ◽  
Subsurface Water ◽  
Water Ice ◽  
Martian Regolith

Chemistry and accretion history of Mars

1994 ◽  
Vol 349 (1690) ◽  
pp. 285-293 ◽  
Keyword(s):  
Bulk Composition ◽  
Volcanic Gases ◽  
Martian Surface ◽  
Volatile Elements ◽  
Water Ice ◽  
The Earth ◽  
History Of ◽  
The Mean ◽  
Wet Climate ◽  
Martian Regolith

Using element correlations observed in SNC meteorites and general cosmochemical constraints, Wänke & Dreibus (1988) have estimated the bulk composition of Mars. The mean abundance value for moderately volatile elements Na, P, K, F, and Rb and most of the volatile elements like Cl, Br, and I in the Martian mantle exceed the terrestrial values by about a factor of two. The striking depletion of all elements with chalcophile character (Cu, Co, Ni, etc.) indicates that Mars, contrary to the Earth, accreted homogeneously, which also explains the obvious low abundance of water and carbon. SNC meteorites and especially the shergottites are very dry rocks, they also contain very little carbon, while the concentrations of chlorine and especially sulphur are higher than those in terrestrial rocks. As a consequence we should expect SO 2 and HC1 to be the most abundant compounds in Martian volcanic gases. This might explain the dominance of sulphur and chlorine in the Viking soils. In turn SO 2 , being an excellent greenhouse gas, may have been of major importance for the warm and wet period in the ancient Martian history. Episodic release of larger quantities of SO 2 stored in liquid or solid SO 2 tables in the Martian regolith triggered by volcanic intrusions as suggested here could lead to a large number of warm and wet climate periods of the order of a hundred years, interrupted by much longer cold periods characterized by water ice and liquid of solid SO 2 . Sulphur (FeS) probably also governs the oxygen fugacity of the Martian surface rocks.

scholarly journals Mapping alpine snow using a spectral mixture modeling technique

1993 ◽  
Vol 17 ◽  
pp. 121-124 ◽  
Author(s):  
Anne W. Nolin ◽  
Jeff Dozier ◽  
Leal A. K. Mertes
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Land Surface ◽  
Mixture Modeling ◽  
Modeling Technique ◽  
Imaging Spectrometer ◽  
Snow Covered Area ◽  
Covered Area ◽  
Spectral Mixture ◽  
Spectrometer Data

Remote sensing has provided a means of obtaining estimates of snow-covered area, yet traditional methods have had difficulty mapping snow in shaded and vegetated areas. Spectral mixture analysis is a linear mixture modeling technique that shows promise for mapping land surface covers, particularly when imaging spectrometer data are used. Applying this technique to AVIRIS data collected over the Sierra Nevada, California, we have estimated the fraction of snow cover in each pixel, even in areas that are shaded or forested. This modeling technique enables us to map snow cover at the sub-pixel level and provides a means of estimating the errors associated with the calculation.

scholarly journals Mapping alpine snow using a spectral mixture modeling technique

1993 ◽  
Vol 17 ◽  
pp. 121-124 ◽  
Author(s):  
Anne W. Nolin ◽  
Jeff Dozier ◽  
Leal A. K. Mertes
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Land Surface ◽  
Mixture Modeling ◽  
Modeling Technique ◽  
Imaging Spectrometer ◽  
Snow Covered Area ◽  
Covered Area ◽  
Spectral Mixture ◽  
Spectrometer Data

Remote sensing has provided a means of obtaining estimates of snow-covered area, yet traditional methods have had difficulty mapping snow in shaded and vegetated areas. Spectral mixture analysis is a linear mixture modeling technique that shows promise for mapping land surface covers, particularly when imaging spectrometer data are used. Applying this technique to AVIRIS data collected over the Sierra Nevada, California, we have estimated the fraction of snow cover in each pixel, even in areas that are shaded or forested. This modeling technique enables us to map snow cover at the sub-pixel level and provides a means of estimating the errors associated with the calculation.

Die Identifikation früher Veränderungsmuster in der ambulanten Psychotherapie

2007 ◽  
Vol 36 (2) ◽  
pp. 93-104 ◽  
Author(s):  
Wolfgang Lutz ◽  
Niklaus Stulz ◽  
David W. Smart ◽  
Michael J. Lambert
Keyword(s):  
Growth Mixture Modeling ◽  
Mixture Modeling ◽  
Growth Mixture

Zusammenfassung. Theoretischer Hintergrund: Im Rahmen einer patientenorientierten Psychotherapieforschung werden Patientenausgangsmerkmale und Veränderungsmuster in einer frühen Therapiephase genutzt, um Behandlungsergebnisse und Behandlungsdauer vorherzusagen. Fragestellung: Lassen sich in frühen Therapiephasen verschiedene Muster der Veränderung (Verlaufscluster) identifizieren und durch Patientencharakteristika vorhersagen? Erlauben diese Verlaufscluster eine Vorhersage bezüglich Therapieergebnis und -dauer? Methode: Anhand des Growth Mixture Modeling Ansatzes wurden in einer Stichprobe von N = 2206 ambulanten Patienten einer US-amerikanischen Psychotherapieambulanz verschiedene latente Klassen des frühen Therapieverlaufs ermittelt und unter Berücksichtigung unterschiedlicher Patientenausgangscharakteristika als Prädiktoren der frühen Veränderungen mit dem Therapieergebnis und der Therapiedauer in Beziehung gesetzt. Ergebnisse: Für leicht, mittelschwer und schwer beeinträchtigte Patienten konnten je vier unterschiedliche Verlaufscluster mit jeweils spezifischen Prädiktoren identifiziert werden. Die Identifikation der frühen Verlaufsmuster ermöglichte weiterhin eine spezifische Vorhersage für die unterschiedlichen Verlaufscluster bezüglich des Therapieergebnisses und der Therapiedauer. Schlussfolgerungen: Frühe Psychotherapieverlaufsmuster können einen Beitrag zu einer frühzeitigen Identifikation günstiger sowie ungünstiger Therapieverläufe leisten.

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