Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986
541
An efficient classification scheme for verifying lack fidelity
of existing county level findings to cultivated land cover areas
Yang Kai, Lin Kaiyu, Chen Jun & Lu Jian
Wuhan Technical University of Surveying and Mapping, China
ABSTRACT: In order to verify the lack fidelity of existing findings to cultivated land
cover areas in county level for the purpose of rural economical planning, a special com
puter aidded classification scheme has been tested and is introduced in this paper. The
schene consists of three main aspects, namely the preprocessing of IANDSAT MSS multitem
poral image data, the selecting of optimum feature image set and the classification pro
cessing with auxiliary ground height information. Based on this schene, the improvement of
classification accuracy amongting to 8% was obtained, and the man-male mistakes in existing
findings of testing county have been checked out.
1. Introduction
In order to meet the needs of planning for develo
ping- rural economies, it is neccesory for the author
ities of different level's goverments to know the
actual situation of land cover types. But unfortu
nately, the existing county level findings in ques
tion in China are mostly not reliable enough for
planning purpose. This is because not only of the
technical reasons, but mainly of the historical and
man-made reasons, for instance, the definition of
distal ce or area measure for cultivated land was not
corresponding to the couversion between Chinese rule
and metric one; and the peasents used to report the
cultivated land areas less than actual one for paying
less agricultural tax. However, the uncorrectness of
existing findings to cultivated land was rather
systenatical, especially within a local regin. So
it becomes possible to estimate the actual cultiva
ted lend areas all over the regin, by determining
the correction factor from some sampling area, e.g.
a typical county. This is the main purpose of our
subject.
Under above description, the next question could
be hov can detormine the actual land cover situation
in county level. There are options, the one is based
on cor ventional photogrammetry procedure which is
accurate but time consuming; the other is based on
satellite remote sensing techniques which is less
accurate than the former but rather time saving. We
have chosen the latter one. Of course, the problem
following our choice is to design a scheme to impro
ve the classification accuracy based on satellite
images, which is the key point that our research
subject was going to solve.
Our classification scheme can be cha.racterrized
by following key words: LANDSAT images; multitem
poral data, image transformation in multispectral
domair, feature image selection, and computer-aided
classification with auxiliary ground height informa
tion. The principle of the scheme and corresponding
experimental results will be introduced as follows.
2. Pieparation of basic image data
The Xian-ning county of Hubei province in China was
selected as sampling and testing area. Three types
of basic image data, were neccesary for performing
the classification scheme, namely:
1. origional LANDSAT MSS images within the county
bound ery.
In this experiment two-temporal LANDSAT MSS images
with total 8 bands were used, which were seperately
imaged on Oct. 16, 1978 (digital image CCT) and on
June 16, 1979 (negtives with scale 1:3*36 million).
Three steps was needed to form the required image
windows as shown in figure 1 (taking one band as
example).
(a) read (or scan) a rectangular image window covering
testing county area from the raw image carrievs;
(b) digitally rectify the image window based on
selected control points;
(c) digitally mask the rectified image and form the
image windows within the county boundary.
2. digital terrain model (DTM) image
The DTM image in our exeriment was created by
direct reading the height value of DTM grid with
200m intervals on existing topographic map. Then
it is densified in computer by interpola.tion method
for each DTM pixels which have the same geometric
resolusion as origional image ha.s.
3* real ground feature encoding image in selected
sampling areas
vVithin the testing county area six sampling area.s
selected, which were distributed at typical parts
of the county, seperately with the height range;
(1) 0 - 20m, (2) 21 - 50m, (3) 51 - 100m, (4)
101 - 200m and (5) 201 - 900m. Each of them has
60 x 60 pixels whose class attribute has been
Figure 1. image window within county boundary.
