Prognosis of TiO2 abundance in lunar soil using a non-linear analysis of Clementine and LSCC data

Autor:	Urs Mall, D. G. Stankevich, Vadym Kaydash, Yuriy Shkuratov, Viktor Korokhin
Rok vydání:	2008
Předmět:	Clementine (nuclear reactor) Nonlinear system Orbiter Space and Planetary Science Abundance (ecology) law Linear regression Environmental science Lunar soil Astronomy and Astrophysics Mineral composition Remote sensing law.invention
Zdroj:	Planetary and Space Science. 56:1063-1078
ISSN:	0032-0633
Popis:	We suggest a technique to determine the chemical and mineral composition of the lunar surface using artificial neural networks (ANNs). We demonstrate this powerful non-linear approach for prognosis of TiO 2 abundance using Clementine UV–VIS mosaics and Lunar Soil Characterization Consortium data. The ANN technique allows one to study correlations between spectral characteristics of lunar soils and composition parameters without any restrictions on the character of these correlations. The advantage of this method in comparison with the traditional linear regression method and the Lucey et al. approaches is shown. The results obtained could be useful for the strategy of analyzing lunar data that will be acquired in incoming lunar missions especially in case of the Chandrayaan-1 and Lunar Reconnaissance Orbiter missions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1a276a5f790c4a3ed239b97f3ab3c484 https://doi.org/10.1016/j.pss.2008.02.001 Zobrazit plný text záznamu Full Text from ScienceDirect