Hydrogen Mapping of the Lunar South Pole Using the LRO Neutron Detector Experiment LEND

Science ◽  
2010 ◽  
Vol 330 (6003) ◽  
pp. 483-486 ◽  
Author(s):  
I. G. Mitrofanov ◽  
A. B. Sanin ◽  
W. V. Boynton ◽  
G. Chin ◽  
J. B. Garvin ◽  
...  
Keyword(s):  
Neutron Detector ◽  
South Pole ◽  
Detector Experiment ◽  
Lunar South Pole

scholarly journals Response to Comment on "Hydrogen Mapping of the Lunar South Pole Using the LRO Neutron Detector Experiment LEND"

Science ◽  
2011 ◽  
Vol 334 (6059) ◽  
pp. 1058-1058 ◽  
Author(s):  
I. G. Mitrofanov ◽  
W. V. Boynton ◽  
M. L. Litvak ◽  
A. B. Sanin ◽  
R. D. Starr
Keyword(s):  
Neutron Detector ◽  
South Pole ◽  
Detector Experiment ◽  
Lunar South Pole

scholarly journals Technical Comment on "Hydrogen Mapping of the Lunar South Pole Using the LRO Neutron Detector Experiment LEND"

Science ◽  
2011 ◽  
Vol 334 (6059) ◽  
pp. 1058-1058 ◽  
Author(s):  
D. J. Lawrence ◽  
V. R. Eke ◽  
R. C. Elphic ◽  
W. C. Feldman ◽  
H. O. Funsten ◽  
...  
Keyword(s):  
Neutron Detector ◽  
South Pole ◽  
Detector Experiment ◽  
Lunar South Pole

A Concept for Robotic Lunar South Pole Exploration

Space 98 ◽  
1998 ◽  
Author(s):  
Matthew Deans ◽  
Stewart Moorehead ◽  
Ben Shamah ◽  
Kimberly Shillcutt ◽  
William "Red" Whittaker
Keyword(s):  
South Pole ◽  
Lunar South Pole

Accessing, Drill and Operating at the Lunar South Pole: Status of European Plans and Activities

2016 ◽  
Author(s):  
Richard Fisackerly ◽  
James Carpenter ◽  
Berengere Houdou ◽  
Gianfranco Visentin ◽  
Francesco Rizzi ◽  
...  
Keyword(s):  
South Pole ◽  
Lunar South Pole

Machine Learning applied to Lunar Data to Characterize Potential Sites for Future Science, Mobile Exploration, Utilization, lunar Bases and Moon Villages.

2021 ◽  
Author(s):  
Daniël den Heijer ◽  
Bernard Foing
Keyword(s):  
Machine Learning ◽  
Regions Of Interest ◽  
Machine Learning Techniques ◽  
Identification Algorithm ◽  
South Pole ◽  
Lava Tubes ◽  
Crater Detection ◽  
Lunar South Pole ◽  
Areas Of Interest ◽  
Human Exploration

<p>The lunar south pole is of particular interest to researchers because of its unique geographical features. It contains craters where the near-constant sunlight does not reach the interior. These craters are of enormous importance in the process of human exploration of the moon.This research aims to develop an identification algorithm applied to LROC data to characterize and identify potential regions of interest on the lunar south pole. Such areas of interest include (surroundings of) lava tubes, skylights, crater detection for age estimation, and planning traverses for the Artemis successive missions.Identifying these regions will be done using machine learning techniques such as a deep convolutional neural network that will be trained on labeled data and are then used to identify and characterize new regions of interest.</p>

scholarly journals Numerical modeling of the formation of Shackleton crater at the lunar south pole

Icarus ◽  
2021 ◽  
Vol 354 ◽  
pp. 113992
Author(s):  
Samuel H. Halim ◽  
Natasha Barrett ◽  
Sarah J. Boazman ◽  
Aleksandra J. Gawronska ◽  
Cosette M. Gilmour ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
South Pole ◽  
Lunar South Pole

Deep Structure of the Lunar South Pole‐Aitken Basin

2019 ◽  
Vol 46 (10) ◽  
pp. 5100-5106 ◽  
Author(s):  
Peter B. James ◽  
David E. Smith ◽  
Paul K. Byrne ◽  
Jordan D. Kendall ◽  
H. Jay Melosh ◽  
...  
Keyword(s):  
Deep Structure ◽  
South Pole ◽  
Lunar South Pole
Sign in / Sign up

Export Citation Format

Share Document