The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008
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interactive visual interpretation method which forms along with
the computer technology and the remote sensing image
processing technology's development. The image can be
zoomed in, zoomed out, moved and enhanced on the software
platform. According to the screen interpretation symbol of land
objects, the interpretation person outlines the border line
directly with the mouse along the image characteristic edge
after the image achieves the best visual interpretation effect.
The supervised classification is one of the computer automatic
classification methods. Its most basic characteristic is before the
classification people have investigated the sample area. With
the artificial visual interpretation, people have got the prior
knowledge about land objects’ category attribute. Then the
computer trains the discrimination function to complete the
classification according to the knowledge. The classical
supervised classification methods are the maximum likelihood
method, the minimum distance method, parallelepiped method
and so on (Lillesand, 1994; Cshowengerdt, 1983).
The interactive visual interpretation can make full use of the
interpretation person's experience and knowledge. It is flexible
and good at extracting spatial information, but spends more
time and has difference between individuals. Computer
automatic classification consumes shorter time, and its
repeatability is good. But because it is difficult to use the
person’s knowledge and extract spatial information, it causes
the wrong classification and omitting some land objects easily
(Zhang Yinhui, 2002).
3. REMOTE SENSING IMAGE INTERPRETATION
METHODS SERVING URBAN PLANNING
3.1 Supervised Classification
As a result of the urban objects' complexity as well as the urban
planning’s requirements of the function districts partition, only
the computer automatic classification cannot satisfy the needs
of the urban present situation investigation. Now take
supervised classification as an example to discuss it.
The supervised classification usually carries out the
classification of land objects in the image by establishing study
samples of typical land objects, such as the building, the water
body, the vegetation, the road and so on. Although supervised
classification consumes shorter time, but is not suitable to the
land objects classification in the urban planning. Firstly, in the
way of the remote sensing classification's requirements of the
image, because there are too many kinds of the urban land
objects, the matter of same kind of objects having different
spectrums and the different kinds of objects having same
spectrum is very common. It is also impossible to establish the
samples of all types. So it is easy to make the wrong
classification or there are not enough types. And the buildings
are very crowded. The shadow’s influence is serious, which
reduces the accuracy of classification results. Next, in the way
of requirements of urban planning, the key point of urban
planning and the management is studying the rationality of the
urban function unit and the structure, the scientific nature of
urban configuration as well as the appraisal and forecast of
urban environment ecosystem and the urban environment
pollution (Shen Qi, 2006). The land objects having similar or
the same spectral characteristic may belong to the identical
category, but their functions in the urban are not always same.
For example, the main road and the inferior road belong to the
same road type, but they are actually different in municipal
transportation's supporting capacity. A certain urban function
unit contains many kinds of land objects mostly. In other words,
an urban function unit contains different spectral characteristics.
It is impossible to realize the discrimination of urban function
units by supervised classification or any other computer
automatic classification methods.
3.2 Man-Machine Interactive Visual Interpretation Based
On GIS
Compared with the supervised interpretation, the man-machine
interactive visual interpretation can use the operating person's
experience and the knowledge fully, which is advantageous in
associating with other non-remote sensing information, and can
distinguish the goals and their nature and function in the image
using the contrastive analysis method. Therefore, although
visual interpretation consumes more time, but in the way of
classification accuracy and the scientific nature, the visual
interpretation has more superiorities, and is more suitable for
the urban planning, compared with supervised classification and
other computer automatic classification methods.
First of all, the remote sensing image used in the urban present
situation investigation should be able to display the land
objects’ geometry characteristics and geographical positions as
well as the detail information precisely. The high spatial
resolution's aerial image containing the rich spatial information
and the clear textural property can satisfy urban information
demands well. It has very big superiority in the fine land object
extraction and the quantitative investigation, and is helpful in
realizing the more environmentally-friendly, more economical,
and more accurate planning, which has already became the
essential data to establish modernistic city and realize urban
sustainable development (Shen Qi, 2006).
In the interpretation process, the urban digital line graphics
about road, building, land objects points and so on should be
referred to for a clearer understanding about the urban land
object’s function.
In the GIS platform, the existing urban land object’s vector data
layer can be added. And the high resolution aerial image can be
zoomed in, zoomed out and moved for the man-machine
interactive visual interpretation easily. Meanwhile the
classification result can be written into the attribute database
directly, which is advantageous to the data’s management and
sharing.
3.3 Case Study
Take 0.2 meter resolution's aerial image and 1:2000 urban
digital line graphics (contains road, building and other layers)
of some district in Beijing, as well as the ArcGIS platform as an
example to explain the man-machine interactive visual
interpretation method’s superiority in present situation
investigation serving the urban planning.
For the first place, register the image based on the existing road
layer. Then do the edit on the basis of the road layer according
to land objects points distribution and land objects’
characteristics reflected from the image, as well as <Urban
Land Classification And Planning Construction Classification
Standard CBJ137-90>, to get the different urban function units
(e.g. Figure 1).