tanbul 2004
xisting data
xisting data,
the method
isting data
0 buildings.
model were
ficult to tell
of existing
red method
May 1997.
nents were
| a different
ts that the
//1997 and
indicating
tion of new
site.
isting data
a university
the method
ng data did.
s opened in
of 1991 or
onsistency"
se data.
nt) and
Inter. national Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
Air photograph as S reference data(2000)
SAR Original Image (1992.9)
A
i ©
a
= x
Nonstationary Change Area (1992-1998)
Figure 6. Extraction of nonstationary change area by developed method
Ne
Vegetation Data (1994)
n >
3
Land Use Change Area (1991-1997)
Au
Vegetation Change Area (1994-1999)
r
Figure 7. Land use data and vegetation data
In this case, analysis or research on campus conditions (e.g.
land use surrounding the campus, environmental assessment,
etc.) cannot be performed accurately until updating of the data
(Le. land use data of 1997 and vegetation data of 1999) has
occurred. This means that real-time evaluation is impracticable.
This problem is referred to in problem (iii) in the Introduction.
The method developed in this study can solve these problems to
some extent, and improve the data accuracy over time, as noted
in 3.1 above.
3.3 Areas where change was detected only by the method
developed in this study
ea C is a group of paddy fields. The method developed in this
study evaluated the change occurring after 1997 as a
nonstationary change. However, the change in Area C went
back into stationary change again after 1998. It is highly likely
that Area C was a fallow paddy field. This does not mean that
the detection was a failure, for it is still a nonstationary change
in the land surface; although it is not a change of land use or
change of vegetation. Although, there may be applicable uses in
many policy making areas for utilizing such detection of
nonstationary change among the land use.
