ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001
CONSTRUCTION OF 3D MODELS FOR ELEVATED OBJECTS IN URBAN AREAS USING AIRBORNE SAR
POLARIMETRIC DATA
Yalkun YUSUF 1) , Masashl MATSUOKA 1) , Fumio YAMAZAKI 1)
Seiho URATSUKA 2 ’, Tatsuharu KOBAYASHI 2) , Makoto SATAKE 2)
Earthquake Disaster Mitigation Research Center
National Research Institute for Earth Science and Disaster Prevention (NIED) 1)
2465-1 Mikiyama, Miki, Hyogo 673-0433, Japan.
Tel: +81-794-83-6632, Fax: +81-794-83-6695
Email: yalkun@edm bosai.ao.ip 1)
Communications Research Laboratory (CRL) 2)
Ministry of Public Management, Home Affairs, Posts and Telecommunications
4-2-1 Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan
Tel: +81-423-27-7465, Fax: +81-423-27-6665
Keywords: airborne SAR, Synthetic Aperture Radar, 3D construction, polarization, segmentation, classification, GIS, speckle noise
filtering
ABSTRACT
Airborne survey methods can be an effective solution since they can provide spatial information with a large-scale area quickly and easily.
Using remote sensing data to construct 3D urban area is very useful for urban planning. This paper presents the elevation extraction in an
urban area using airborne SAR (Synthetic Aperture Radar) polarimetric data. Simple trigonometric models and the SAR geometry
parameters were used to derive relative heights of elevated objects from the shadow of the elevated objects (Kirscht and Carsten, 1998).
A Lee polarimetric filter was applied to reduce speckle level while preserving the polarimetrtic properties and is given to be useful to
improve the classification accuracy (Lee et al., 1999). In classification of SAR image, Bayes maximum likelihood classification algorithm is
applied to SAR filtered data, which is based on the complex Wishart distribution of the multilook covariance matrix (Lee et al., 1994).
Finally a contour map and VRML image were given using the result of the constructed 3D elevated object of the study areas.
1.INTRODUCTION
Imaging radars are rapidly becoming one of the major tools for
observing the earth’s surface and its cover. SAR is an active radar
system due to its capability to image in all weather, day and night,
and independence of sun illumination. It can provide spatial
information with a large-scale area quickly and easily. Airborne
SAR provides high-resolution images, which can be used for
identifying individual buildings. Therefore the applications of a
SAR embrace a wide range of fields including geology, natural
disasters, agriculture, detection of snow and ice, and
oceanography.
Using remote sensing data to construct 3D urban area is very
useful for landscape planning. As an attempt, in this paper we
presented construction of 3D elevated objects in urban area using
airborne SAR polarimetric imagery data.
Radar images area composed of many dots, or picture elements.
Each pixel (picture elements) in the radar image represents the
radar backscatter for the area on the ground, dark areas in the
image represent low backscatter, bright areas represent high
backscatter. Backscatter for a target area at a particular
wavelength will vary for a variety of conditions: size of the scatters
in the target area, moisture content of the target area, polarization
of the pulse, and observation angles. Flat surfaces that reflect
little or no microwave energy back towards the radar will always
appear dark in radar images. Surfaces inclined towards the radar
will have a stronger backscatter than which slope away from the
radar and will appear brighter in a radar image. Some areas are
not illuminated by the radar, like the back of building, are in
shadows, and will appear dark. The shadows of the objects are
very helpful to judge the size and shape of objects by providing an
impression of convexity and concavity. Since the shadows are
assigned to suitable elevated objects, then relative heights of
elevated objects from SAR data image can be derived from the
shadow using trigonometric models and parameters of the SAR
geometry (Kirscht and Carsten, 1998).
In most case, images produced by radar have noisy in
appearance than comparable pictures produced optically due to a
phenomenon called speckle. The radar echoes reflected from
individual scatters within a pixel either randomly reinforce one
another if they happen to be in-phase or reduce the return signal
if they are out-of-phase (fading). Speckle complicates the image
interpretation problem by reducing the accuracy of the image
segmentation and classification. In this study, to reduce the
speckle noise of SAR polarimetric imagery and improve the
classification accuracy, a Lee polarimetric filter was applied to
reduce speckle level, which has the feature of smoothing the
image data without removing edges or sharp features in the
images (Lee et al., 1999).
To construct 3D image from SAR polarimetric data needs
classification and segmentation of SAR data. A classification
algorithm was applied to the filtered SAR data based on the
complex Wishart distribution of the multilook covariance matrix
(Lee et al., 1994).
After filtering speckle noise, segmentation and classification of
SAR images, elevated objects and shadow regions are
segmented in the SAR image. Since the shadows are assigned to
suitable elevated objects, then relative heights of elevated
objects from SAR data image can be derived from the shadow
using trigonometric models and parameters of the SAR geometry.
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