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Mapping without the sun
Zhang, Jixian

Mu H. Wang ab , Hai T. Li a , Ji.X Zhang 3 ,Jing H.Yang 3
a) Chinese Academy of Surveying and Mapping,Beijing,l 00039,China-(lhtao,zhangjx,)@casm.ac.cn
b) Liaoning Technical University ,School of Geomaticas,Fuxin, 123000,China- amudc@126.com
Commission VII Working Group VII/6
KEYWORDS: SAR, Optical images, Fusion, Segmentation, Change Detection, Object-Specific
Although SAR images have been widely used in the field of change detection because of the capability of SAR sensors to acquire
images during day and night as well as all weather conditions, the information provided by SAR data alone may not sufficient for
detailed object analysis.We explore an approach based on fusion of SAR and optical images to detect object-specific changes.The
assumption of the proposed method is that we can acquire SAR data and corresponding optical data respectively at different
periods.The approach in this paper consists of three steps:images pre-processing, SAR and optical images fusion, change detection
based on region features.Specifically speaking, geometric or radiometric calibration and precise registration between SAR and
optical images are included in the first phase. In the second step,we adopt wavelet transform-based fusion method.Multiscale image
segmentation approach is separately applied to the two fused image for obtaining object region. Then we compare the corresponding
region features extracted from the two segmented images using distance distinguishing function. The experiment results illustrate that
the approach can make use of the complemental characteristics of SAR and optical images to acquire more information and
effectively detect object changes.
Remote sensing technique has been widely used in the field of
change detection because of the advantage of macroscopy, high
speed and short interval of acquiring resources, ample
information and effective usability (Massonnet et al.,
1993).While Synthetic Aperture Radar (SAR) has the capability
to obtain information during day and night as well as all
weather conditions, which supplies a gap of optical images. The
information extracting from fusion of SAR and optical images
is complementary for detailed object analysis.
In recent years, many change detection techniques have been
developed. They can broadly group into three categories (Baud
ouinet ah, 2006): visual interpretation, pixel-based approaches,
and object-based methods. Specifically, visual interpretation
requires human experience (computer-assisted or not) to label
zones that are considered as changed, which can make full use
of analysts’ experience and knowledge but is time-consuming.
Digital pixel-based approaches compare the spectral features
between pixels on low or middle resolution remote sensing
images. There are many kinds of methods in this category,
which performances are rarely compared to each other because
these techniques are considered scene-dependent(Lyon et
ah, 1998, Rogan et ah,2003).The main drawback of pixel-based
methods are the “salt and pepper” effect in the resulting map.
Moreover, the spatial or contextual information between
proximate pixels is most often ignored(Atkinson et al.,2000,
Townshend et ah,2000).Object-based methods combine the
advantage of visual interpretation and pixel-based approaches
and incorporate spatial, texture and structure information of
pixel groups, which are spatially continuous and homogeneous
regions(named objects) dividing by image segmentation
techniques on satellite images. Object-based methods make full
use of contextural information (Flanders et ah,2003) between
super- and sub-objects as well as neighbor objects. However,
many of these methods suffered of low detection performance.
This research aims to develop a new region-based method to
detect symbolic buildings’ changes collapsed during the Bam
earthquake, taking advantage of multi-resolution
segmentation Baatz et ah, 1999),region features extraction,
associated regions search and features similarity comparison.
Furthermore, the approach proposed in this paper is tested on a
multi-temporal fusion SAR and optical images and compared its
performance to visual interpretation method and a pixel-based
method in ENVI 4.3.
The study site is located in Bam,Iran and the epicenter suitates
at 29.002°N, 58.325° E.In the test we adopt ENVISAT ASAR
data and multi-spectral QuickBird satellite images. Table 1 lists
the information of high-resolution QuickBird imagery of Bam.
Figure 1 shows the time sequence and track number of seven
breadthes of ASAR data.Considering the epicenter location and
happen time of Bam earthquake,we choose two breadthes which
track numbers are 9192 and 9693.
Acquisition Date
Spatial Resolution
Image Size
Image pre-processing