You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Mapping without the sun
Zhang, Jixian

The QuickBird image products can be classifieds as into basic
images, standard images, ortho-photos and stereo-photo pairs
usually. They are also classed into panchromatic band image
data, multispectral image data, products package of
panchromatic band image data and multispectral image data and
fusion image data (true color or false color) based on the
integrated bands.
2.2 The brief introductions of experimental satellite photos
The experimental satellite photos are single panchromatic of
standard products and multispectral satellite photos taken on
January 7, 2003 of USA time in Fuxin City of Liaoning
Province. The ground sampling resolution is 0.636m, the
reference ellipsoid is WGS84. the projection is transverse
Mercator projection, the heliacal horizontal angle is 159.671°
and the heliacal zenith angle is 23.0836°, the satellite horizontal
angle is 99.4251°, the satellite zenith angle is 76.867°, the
orbital perspective angle is 0.0473414° and the vertical orbital
perspective angle is 12.2236°. The satellite position and
situation are measured accurately so that the quality in good
condition. The ground intervals both in longitudinal and lateral
directions are 0.6m and the mode is quadrate convolution for
resample. The other information is almost the same of
multispectral satellite photos and panchromatic satellite photos
except that they all have red, green, and blue bands. Meanwhile,
the intervals are 2.542m in ground sampling and 2.4m in
3.1 Images preprocessing
3.1.1 Clipping and fusion of images: The human eyes are
limited in the ability of density of black and white, in which
only can reach ten gray-levels, but is higher in the
discrimination of color images. If the average resolution of
human eyes is AA — 3uiYl , more than hundred of colors can
be distinguished and this only is one of elements in colors. If
the other two factors saturation and lightness are considered, the
level of distinguishing different colors for human eyes is far
greater than that of distinguishing between black and white. In
order to take advantage of colors in remote sensing image
interpretation, panchromatic images and multispectral images
can be merged, so that the characteristics of both the high
spatial resolution of panchromatic images and the interpretation
of multispectral image can be reserved. The main-elements
analysis method of Erdas is applied in fusion, the quadrate
convolution mode used in resample and a combination of
bands-1, -2 and -3 in image display. Because the range of
satellite photos we got is very large about 200 km 2 , the amount
of data is too much, that is, the panchromatic satellite photos
are about 1.7 Gbit, the multispectral satellite photos are about
700 Mbit, and the data after fusing is near 7 Gbit. Considering
the data quantity and convenience in data processing, an image
around the Liaoning Technology University approximately one
square kilometers scope is captured where the relief is flat (the
difference in elevation is less than one meter) and crowded by
3.1.2 Determination of internal geometric precision: The
QuickBird standard image is corrected by using a rough DEM
model, and ground and land features are standardized on
WGS84 reference ellipsoidal surface, so that it isn’t
orthographic images, because the degree of precision is quite
low. The QuickBird standard images should have better internal
geometric precision. Hence after systematic correction,
generally speaking, if the interior geometric error of satellite
image is smaller than or equal to a pixel, it will satisfy the
precision request in the most remote sensing application. Erdas
remote sensing software carries on the image geometric
rectification by the way of the integral correction, and if the
internal geometric precision high, then the image precision will
be better after rectification. Therefore, an analyzing to the
internal geometric precision of the empirical data should be
undertaken. The concreting method is that by choosing 15
control points on the topographic diagram to discover the
corresponding image points in the fusion image, the root mean
square of length difference between each line connecting
control points on the image and its corresponding lines on the
topographic map, that is
Where, Ad t = d mi - d gi , (z = 1,2,3, ••*,«), d mi is the
length of the line i connecting the control points on the image,
d . is the length of the corresponding lines on the topographic
map, and n is the total number of the lines between control
Fifteen control points are selected in this experiment, therefore
there are 105 control sides altogether, and after
calculation, 8 = 0.5723m < 0.6m it is smaller than a pixel
in which indicates that the internal precision is quite high from
using the QuickBird standard images.
3.2 Accurate geometric rectification of images
For the purpose of relationship registration of the remote
sensing images and the geographic space on site, which is
called location and orientation, the geometric rectification to the
images must be carried out before the evaluation of the interior
position precision. The conventional methods for the geometric
rectification are divided into optical rectification and the digital
one. At present, since the images are usually based on the
digital data, the digital geometric rectification is generally used.
Actually, there are two kinds of methods applied: one is the
collinear equations using digital elevation model (DEM) and
corresponding imaging equation and another is control point
computation method based on a certain mathematical model, in
which the polynomial method is typical one. Theoretically, the
method of collinearly equations is stricter than the polynomials,
specially introduced the ground elevation information in the
process, so that is superior to the polynomials in the case of
ground undulation. Although the method is higher in precision,
but the DEM model must be established firstly, otherwise the
rectification will become difficulty and complicated if lack of
the digital ground elevation. Moreover, in satellite dynamic
sensor, the position and the attitude angles of sensor are