s for
while
area
s are
Index,
) ha),
npson
ortant,
tics of
indard
anded
in the
d from
s they
of the
In the table 1 the uncorrelated and scale invariant indices
are written in italic underlined letters.
For the description of amount and size of single areas
TRAUB 1997 suggested the use of the "Largest Patch
Index (LPI)* or the “Patch density (PD)", because they are
uncorrelated and scale independent. The LPI is
calculating the largest single area in relation to the total
area of investigation. In contrast to LPI the PD is
calculating the number of patches per 100 ha.
The complexity of landscape structures especially of
border lines will be calculated by the "Landscape Shape
Index (LSI)' and the "Mean Shape Index (MSI)". Both
indices are uncorrelated and scale independent. They are
calculating a value of 1 for an area with a squared border
line. LSI and MSI increases without limit as the object
areas become more irregular.
For the characterisation of structures the “Double Log
Fractal Dimension (DLFD)" is useful. But this index needs
a minimum of three objects in the data set. The DLFD is
scale independent. DLFD approaches 1 for shapes with
very simple perimeters such as squares and approaches
2 for shapes with highly convoluted, plane-filling
perimeters.
The homogeneity of the distribution of object classes in
the analysed area can be described by the scale
independent and uncorrelated index of "Interspersion and
Juxtaposition (IJI). Values near O are describing the
neighbourhood with only one other adjacent object class.
If the regarded object is surrounded from all other object
classes available in the area of investigation than the
index will reach the value 100.
The above mentioned calculations have been applied.
First results showed that a characteristic description of
the observed landscape structure seems possible using
hight resolution satellite data.
Conclusion
The research shows that the use of high resolution
satellite data in combination with common multispectral
data can provide a detailled and objective view of the
landscape unit observed. Additionally Landscape metrics
describing the structure and topology of objects in the
landscape offers a additional possibility to described and
evaluate the landscape unit in comparison with other
geographic regions.
References:
Chavez, P.S.; 1975:
Atmospheric, Solar, and M.T.F.Corrections for
ERTS Digital Imagery, Proc.of the American
Society of Photogrammetry, p. 69f
Crippen, R.E; 1989
A Simple Spatial Filtering Routine for the
Cosmetic Removal of Scan-Line Noise from
Landsat TM P-Tape Imagery
Photogrammetric Engineering and Remote
Sensing, Vol.55,No.3,1989, p. 327-331
de Bethune,St.;Muller, F;Donnay,J.P. 1997 :
Fusion of multispectral and panchromatic images
by local mean and variance matching filtering
techniques. Fusion of Earth Data, Sophia
Antipolis, France, 28-30.January 1998 !
Lavreau, J.; 1991 :
De-Hazing Landsat Thematic Mapper Images.,
Photogrammetric Engineering & Remote
Sensing, Vol.57, No.10, 1991, p. 1297-1302
McGarigal,K.; Marks,B.; 1994:
FRAGSTATS- Spatial Pattern Analysis Program
for Quantifying Landscape Structure, Version 2,
Forest Science Department, Oregon State
University, Corvallis, OR 97331
P.O.Box 606, Dolores, Colorado 81323-9998
O'NEill,R.V.; Krummel,J.R.;Gardner, R.H. et al., 1988 :
Indices of landscape pattern,
Landscape Ecologiy, Vol.1,No.3,p.153-162
Pohl, Christine, 1996 :
Geometric Aspects of Multisensor Image Fusion
for Topographic Map Updating in the Humid
Tropics; ITC;ITC Publication No.39,
ISBN 90-6164-121-7
Stuart Nixon, 1995 :
Publication of Internet:
http://listserv.cesnet.cz/Iwgate/IMAGRSL/
archives/imagrs-l.log9507/date/article-35.html
Steinnocher, K.;1997
Application of Adaptive Filters for Multisensoral
Image Fusion, IEEE Intern.Geoscience and
Remote Sensing Symposium Proceedings,,
3-8.August 1997, Singapore, p.910-912
Traub, B.; 1997:
Methoden zur quantitativen Charakterisierung
von Waldflächenstrukturen
Diss., Univ.Freiburg i.Br.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998 375
