Development of methodology for the detection of slope streaks on Mars surface

• Grant number: 17/03595-6
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2017
• End date: July 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Erivaldo Antonio da Silva
• Grantee: Erivaldo Antonio da Silva
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Associated scholarship(s): 17/16107-0 - Development of methodology for the detection of slope streaks on Mars surface, BP.TT

Abstract

Slope streaks are dark fan-shaped bands that extend along steep slopes on the Martian surface (Sullivan et al., 2001). These features have low albedo and are usually seen along the equatorial region of the planet Mars (Shorghofer et al., 2002). In addition, they appear exclusively in regions with low thermal inertia and where the temperature peaks exceed 275 K (Head et al., 2007). The study of this phenomenon is very important for understanding the planet Mars, as it can provide clues to understanding basic surface properties, such as dust and water cycle and recent climate changes in time scale of hundreds of Years (Kreslavsky and Head, 2009). Although there are a considerable number of researchers who study this phenomenon, the identification of these is currently handled by specialists. The algorithms used for the identification of the Martian surface phenomena in the literature do not include slope streaks (Bandeira et al., 2007; Ding et al., 2010; Sawabe et al., 2006; Molloy e Stepinski, 2007; Statella et al., 2012). In addition, according to Wagstaff et al., (2012) the NASA has a considerable database of images of the planet Mars. The number of these images in the queue for analysis is so great, and continues to grow, that there is an urgent need for the development of automated methods for detecting Martian surface phenomena. Thus, experts can later analyze the data and make inferences. And it is within this scope that this research project fits. The proposal is to contribute to the automation of the process of extracting information about slope streaks in images of the surface of Mars. For this purpose, it is intended to develop a methodology capable of identifying dark slope streaks in MOC and HiRISE images, through image processing techniques with emphasis on Mathematical Morphology. In addition, it is intended to perform edge detection of detected features, to infer the average width of slope streaks and to determine their main directions. At the end of the work, it is expected to have found an automated and efficient method for detecting slope streaks in images of the surface of Mars. The results obtained will greatly aid researchers working with images of the Martian surface, studying the phenomena of slope streaks. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

NEGRI, ROGERIO GALANTE; DA SILVA, ERIVALDO ANTONIO; CASACA, WALLACE. Inducing Contextual Classifications With Kernel Functions Into Support Vector Machines. IEEE Geoscience and Remote Sensing Letters, v. 15, n. 6, p. 962-966, JUN 2018. (13/07375-0, 17/03595-6, 14/08822-2, 14/14830-8)