Comparison of roving-window and search-window techniques for characterising landscape morphometry
Computers & Geosciences (2009)
- ISSN: 00983004
- DOI: 10.1016/j.cageo.2008.12.014
Available from linkinghub.elsevier.com
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Page 1
Comparison of roving-window and search-window techniques for characterising landscape morphometry
www.elsevier.com/locate/cageo
Author s Accepted Manuscript
Comparison of roving-window and search-window
techniques for characterising landscapemorphometry
Carlos H. Grohmann, Claudio Riccomini
PII: S0098-3004(09)00138-1
DOI: doi:10.1016/j.cageo.2008.12.014
Reference: CAGEO2192
To appear in: Computers & Geosciences
Received date: 5 September 2008
Revised date: 5 December 2008
Accepted date: 16 December 2008
Cite this article as: Carlos H. Grohmann and Claudio Riccomini, Comparison of roving-
window and search-window techniques for characterising landscape morphometry, Com-
puters & Geosciences, doi:10.1016/j.cageo.2008.12.014
This is a PDF le of an unedited manuscript that has been accepted for publication. As
a service to our customers we are providing this early version of the manuscript. The
manuscript will undergo copyediting, typesetting, and review of the resulting galley proof
before it is published in its nal citable form. Please note that during the production process
errors may be discoveredwhich could affect the content, and all legal disclaimers that apply
to the journal pertain.
Author s Accepted Manuscript
Comparison of roving-window and search-window
techniques for characterising landscapemorphometry
Carlos H. Grohmann, Claudio Riccomini
PII: S0098-3004(09)00138-1
DOI: doi:10.1016/j.cageo.2008.12.014
Reference: CAGEO2192
To appear in: Computers & Geosciences
Received date: 5 September 2008
Revised date: 5 December 2008
Accepted date: 16 December 2008
Cite this article as: Carlos H. Grohmann and Claudio Riccomini, Comparison of roving-
window and search-window techniques for characterising landscape morphometry, Com-
puters & Geosciences, doi:10.1016/j.cageo.2008.12.014
This is a PDF le of an unedited manuscript that has been accepted for publication. As
a service to our customers we are providing this early version of the manuscript. The
manuscript will undergo copyediting, typesetting, and review of the resulting galley proof
before it is published in its nal citable form. Please note that during the production process
errors may be discoveredwhich could affect the content, and all legal disclaimers that apply
to the journal pertain.
Page 2
Ac
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Comparison of roving-window and1
search-window techniques for characterising2
landscape morphometry3
Carlos H. Grohmann
∗,1
Claudio Riccomini
1
4
1 Introduction5
Neighbourhood analysis in a Geographical Information System (GIS) calcu-6
lates the value of a given raster cell from the values of its neighboring cells.7
Common operations include filtering (high-pass, low-pass, etc) and smooth-8
ing (mean, mode) of data, operations that can be done by means of roving -9
windows or search-windows. Digital terrain analysis (or geomorphometry) re-10
lies on neighbourhood operations to calculate morphometric variables such as11
slope, aspect, local relief or surface roughness (among many others) at scales12
ranging from local (i.e., single landforms) to regional (entire mountain chains).13
∗
Corresponding Author. Instituto de Geocieˆncias – USP, Rua do Lago, 562, Cidade
Universita´ria, Sa˜o Paulo, SP, CEP 05508-080, Tel. +55-11-3091-4216
Email addresses: guano@usp.br (Carlos H. Grohmann), riccomin@usp.br
(Claudio Riccomini).
URLs: http://www.igc.usp.br (Carlos H. Grohmann),
http://www.igc.usp.br (Claudio Riccomini).
1
Instituto de Geocieˆncias, Universidade de Sa˜o Paulo, Sa˜o Paulo, Brazil
Preprint submitted to Elsevier Science 4 May 2009
c
e
p
t
e
d
m
a
n
u
s
c
r
i
p
t
Comparison of roving-window and1
search-window techniques for characterising2
landscape morphometry3
Carlos H. Grohmann
∗,1
Claudio Riccomini
1
4
1 Introduction5
Neighbourhood analysis in a Geographical Information System (GIS) calcu-6
lates the value of a given raster cell from the values of its neighboring cells.7
Common operations include filtering (high-pass, low-pass, etc) and smooth-8
ing (mean, mode) of data, operations that can be done by means of roving -9
windows or search-windows. Digital terrain analysis (or geomorphometry) re-10
lies on neighbourhood operations to calculate morphometric variables such as11
slope, aspect, local relief or surface roughness (among many others) at scales12
ranging from local (i.e., single landforms) to regional (entire mountain chains).13
∗
Corresponding Author. Instituto de Geocieˆncias – USP, Rua do Lago, 562, Cidade
Universita´ria, Sa˜o Paulo, SP, CEP 05508-080, Tel. +55-11-3091-4216
Email addresses: guano@usp.br (Carlos H. Grohmann), riccomin@usp.br
(Claudio Riccomini).
URLs: http://www.igc.usp.br (Carlos H. Grohmann),
http://www.igc.usp.br (Claudio Riccomini).
1
Instituto de Geocieˆncias, Universidade de Sa˜o Paulo, Sa˜o Paulo, Brazil
Preprint submitted to Elsevier Science 4 May 2009
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