Bollettino di Geofisica Teorica e Applicata
OGS Website
About the Journal
Contacts
To Authors
On-line Submission
Subscriptions
Forthcoming
On-line First
The Historical First Issue
Issues

2022 Vol. 63
1

2021 Vol. 62
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2 / Suppl. 3

2020 Vol. 61
1 / 2 / 3 / 4 / Suppl. 1

2019 Vol. 60
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2 / Suppl. 3

2018 Vol. 59
1 / 2 / 3 / 4 / Suppl. 1

2017 Vol. 58
1 / 2 / 3 / 4

2016 Vol. 57
1 / 2 / 3 / 4 / Suppl. 1

2015 Vol. 56
1 / 2 / 3 / 4

2014 Vol. 55
1 / 2 / 3 / 4

2013 Vol. 54
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2

2012 Vol. 53
1 / 2 / 3 / 4

2011 Vol. 52
1 / 2 / 3 / 4 / Suppl. 1

2010 Vol. 51
1 / 2-3 / 4 / Suppl. 1

2009 Vol. 50
1 / 2 / 3 / 4

2008 Vol. 49
1 / 2 / 3-4 / Suppl. 1

2007 Vol. 48
1 / 2 / 3 / 4

2006 Vol. 47
1-2 / 3 / 4

2005 Vol. 46
1 / 2-3 / 4

2004 Vol. 45
1-2 / 3 / 4 / Suppl. 1 / Suppl. 2

2003 Vol. 44
1 / 2 / 3-4

2002 Vol. 43
1-2 / 3-4

2001 Vol. 42
1-2 / 3-4

2000 Vol. 41
1 / 2 / 3-4

1999 Vol. 40
1 / 2 / 3-4

1998 Vol. 39
1 / 2 / 3 / 4

1997 Vol. 38
1-2 / 3-4

1995 Vol. 37
145 / 146 / 147 / 148 / Suppl. 1

1994 Vol. 36
141-144 / Suppl. 1

1993 Vol. 35
137-138 / 139 / 140

1992 Vol. 34
133 / 134-135 / 136

1991 Vol. 33
129 / 130-131 / 132

 
 

Vol. 63, n.1, March 2022
pp. 87-98

Trend surface fitting of airborne gamma-ray spectrum based on 2D-AsLS

K. Sun, L.Q. Ge, Q.X. Zhang, Q.H. Yang, Y. Gu and W.C. Lai

Received: 5 January 2021; accepted: 31 May 2021; published online: 28 October 2021

Abstract

The trend surface analysis is one of the important methods for processing radioactive element concentration data of airborne gamma-ray spectrum. At present, the fitting of trend surface is mainly based on the polynomial least-squares method. Due to the degree of limitation of polynomial functions, the polynomial least-squares method is imprecise in describing the trend surface. Therefore, as an alternative approach, we considered the 2D asymmetric least squares (2D-AsLS) developed under 2D tensor product of a P-spline. 2D-AsLS can make full use of the spatial characteristics of radioactive element concentration data to fit trend surfaces. 2D-AsLS can adjust the fitting effect of the trend surface by modifying smoothness, and can evaluate the fitting effect through the parameters (i.e. fitting coefficient, error variance, coefficient of variation, and degree of deviation). Gamma-ray spectrum data acquired by an unmanned aerial vehicle was used in the experiment. The results showed that 2D-AsLS can completely distinguish regional trend and residual values. Moreover, the trend surface fitted by 2D-AsLS can describe the regional radioactive background in detail.



Download PDF complete


back to table of contents