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Mapping without the sun
Zhang, Jixian

2.1 Description of study area
The study area covers about 100 km 2 along both sides of the
Victoria Harbor, Hong Kong and is located within latitude
22.267°N~22.343°N, longitude 114.122°E~114.240°E (Figure
1). It includes Kowloon and Hong Kong Island, which are both
well-known central business districts (CBD). The study area
consists of dense urban area, bared filed, mixed vegetation and
open water. The urban areas along Victoria Harbour are even,
but the bottom and upper left parts in the study area are rolling
piedmont terrain covered with dense and mixed vegetation.
Table 1 the basic parameters of ERS SAR interferometric
pairs in this study
2.2 Datasets and pre-processing
In this study, a pair of ERS-2 C-Band Single Look Complex
(SLC) SAR data were chosen for generating feature images of
interferometric SAR signature (Table 1). This InSAR pair was
characterized with a short spatial perpendicular baseline (-13 m)
and a relatively long-term interval (35 days). Unlike the
Tandem coherence derived from ERS-1/2 images and used in
standard approaches, a long-term coherence image computed
from the considered InSAR pair can improve capacity to
distinguish man-made features with other urban land-
covers(Bruzzone, Marconcini et al. 2004; Liao 2007). This is
due to the fact that coherence of man-made features remains
high even between image pairs separated by a long time interval
(months to years), however, most of natural land surfaces (e.g.
farmland and forest field, etc. ) are significantly influenced by
temporal decorrelation and lose coherence within a few days. In
addition, average amplitude and amplitude ratio were obtained
from the same InSAR pair and an RGB combination of the
three resulted feature images was shown in Figure 2(a).
In addition, a SPOT 5 HRG multi-spectral imagery acquired in
November, 2002 was used in this study. The SPOT 5 image had
three bands in visible and NIR bands (0.50-0.59 um, 0.61-0.68
um, 0.79-0.89 um) with 10 meter spatial resolution and one in
SWIR band (1.58 - 1.75 um) with 20 meter resolution (Figure 2
(b)). In particular, a Colour-Infrared (CIR) aerial photography
acquired in November, 2000 was utilized to derive training/test
data for an ISP CART-based prediction model based and
validation data for accuracy assessment of ISP mapping. The
CIR aerial photograph was scanned color balanced into a digital
format with 33-cm nominal spatial resolution. The SPOT 5 data
and the CIR aerial photograph were geometrically corrected and
ortho-rectified to Hong Kong 1980 Grid Map Projection using a
1:5, 000 Digital Elevation Model (DEM) data of Hong Kong.
For merging multi-sensors remote sensing data, several pre
processing steps are necessary to establish a more direct
relationship between image signals and physical phenomena. In
this study, some standard InSAR pre-processing steps were
applied to the two ERS-2 SLC SAR data above, mainly
including radiometric calibration, coregistration (with 0.1 pixel
accuracy), a temporal SAR speckle filtering applying to
amplitude images, and deviation of InSAR features (coherence,
average amplitude and amplitude ratio). In order to geocode the
InSAR products, the satellite precision orbit data and the
mentioned large-scale DEM data were utilized to generate a
geocoding lookup table for the conversion between DEM
projection coordinate and SAR imaging geometry. The
geocoding process was completed with sup-pixel accuracy by
using GAMMA DIFF&GEO module (www.gamma-rs.ch). The
geocoded InSAR products, coherence image, average amplitude
image and amplitude ratio image, finally were resampled at 10
m spatial resolution as same as the SPOT data.
In this case study, a CART-based approach developed by Yang
(2003) was adopted to estimate sub-pixel percentage of
impervious surface with the synergistic use of SPOT multi-
spectral imagery and InSAR products. This approach used high-
resolution imagery as a source of training data for representing
urban land-cover heterogeneity, and medium-resolution
imagery to extrapolate imperviousness over large spatial areas.
Figure 2 The medium-resolution remote sensing data set in the study area (a)ERS-2 InSAR data (Red-Coherence, Green-
Interferogram amplitude, Blue-Amplitude ratio); (b) SPOT5 HRG data(Red-Band4, Green-Band 1, Blue-Band3,)