lon —
tion,
te the
is de-
d lin-
10 ef-
is de-
ne in
1 gen-
racted
to re-
s that
> road
notely
toring
n.
on the
scien-
have
n the
se ap-
e dis-
rieties
icted.
' edge
They
endi ea
Fig. 1 An ideal step edge Fig. 2 A roof line
ne as
Fig. 3 A rectangle line
luu X ee
Fig. 4 A real line
have no ability to integrate multi-band information. It is
impossible for these methods to detect and extract the
road when road has the similiar gray level with its back-
ground on single band image.
In this paper, one contextual method simulating the vi-
sual interpretation is developed to extract the road fea-
tures. It uses the shape information that is long lenth
and narrow width to detect and extract road features. It
also can integrate the multi-band information. It was
found that roads extracted by this method are almost i-
dentical to those produced by field investigation.
2. STUDY SITE
The TM data were obtained on August 25, 1987 from
the Chinese Satellite Ground Station (CSGS). CSGS
provided both the false color composited photo and com-
puter compatible tape(CCT). The study area was select-
ed to the Yueyang City, Huan Province (see fig. 5).
The downtown area, in the northern part of Hunan
Province, has about 300,000 population. Great Dongt-
ing Lake is adjacent at its west and the Yangzhi River at
its north. Beijing to Guangzhou railway passes the whole
area. It is developed rapidly in the recent years and now
is the one most important base for industry, transporta-
tion, aquatic production and agriculture.
Yueyang city expands median-small urban area. The
435
G A
’ V vu uf *
T Q Huer ç p
0
*
: East
; Do Gt tn
; Lape Jj
"e
29° wikow/
Xiang yl |
em]
77 km
LA Az
J
River Railway High way
Fig. 5 Study site of Yueyang city
complexity of road distribution increases difficulty of the
extraction of road system from TM data.
3. ANALYSIS AND ALGORITHM
For more than a decade, efforts to extract information
from multispectral remote sensing image data have
proved increasinly successful. To a large extent, these
efforts have focused on the application of pattern recog-
nition techniques to the multispectral measurements
made on individul ground resolution elements, i. e. ,
scenes have been classified pixel-by-pixel based on the
measurement vectors associated with the individual pix-
el. However, sole spectral information is not adequate
to recognize the road features. There are many applica-
tions for which the classes of interest can be better char-
acterized if the spatial information in the remote sensing
data is utilized in addition to the spectral information.
Characteristic spatial features include, for example, tex-
ture and context. Contextual information generally indi-
cates the structural relationships between pixels.
One way to approach contextual information is to utilize
the shape information. One particular target is the object
with regular shape projecting on the image. Shape infor-