The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
1138 
Data 
source 
( Sensor) 
Wav Spatial _ . Image 
. . Polan .. Imaging 
e resolutio . positio . 
. , zation , time 
band n n code 
Landsat-7 
(ETM+ 
) 
Landsat-7 
(ETM+ 
) 
Envisat-1 
(ASAR 
) 
Envisat-1 
(ASAR 
) 
1 8 30 200L 
1-8 30 - - 08 U 
1 8 30 2005 - 
30 " “ 09.03 
D C ~ nc VV / 2001.6.2 
Ban 12.5 IS2 n 
j HH y 
a 
n' n C VV / 2005.7.1 
Ban 12.5 IS4 0 
. HH 2 
d 
Table 2. Remote sensing data sources 
3. REMOTE SENSING DATA PREPROCESSING 
3.1 TM Data Preprocessing 
The pre-treatment of TM images including geometric correct 
and optimal band combination. In the study area collected 
obvious 10 GPS control point of a uniform distribution, for the 
ETM+ images geometric correct, adopted Second Order 
Polynomial transform, and used three-dimensional convolution 
interpolation re-sampling, the precision of geometric correct 
was controlled of the RMS <0.5 pixels. The ETM+ optimal 
band were combined according to the study area topography, 
vegetation distribution, spectral reflectance characteristics. 
According to the index-related variance correlation 
coefficient matrix, OIF index of the combination bands, in most 
cases, TM3, 4,5 and TM1, 4,5-band combination are the best, 
most detailed. In the TM345-band, roads, water, the residents, 
farmland and other places clear Comparison, better-performing 
and useful for the classification between features (Figure 1). 
Figure 1. TM345-band combination images 
3.2 SAR Data Preprocessing 
As ENVISAR satellite imaging to be done in the course of 
coherent processing, and thus formed a signal to the noise, it 
made great impact with the interpretation of radar images, 
reducing the ability to identify targets and structure on the 
ground, making thematic feature extraction and classification of 
Obstacles, so need for Noise Reduction. After noise reduction, 
evaluated the filtering effect with smoothing index F and 
smoothing maintain index E of edge. F value is higher means 
that the ability smoothing stronger, E value is higher means that 
the ability to maintain higher, the formula is as follows: 
£|(g„,-g„)| 
E = 
after filtering 
SK G *,- G *2l 
before filtering 
(1) 
The SAR data image pre-processing according to the landscape, 
the typical characteristics of surface features and ENVISAT 
data in the mining area. As the study area relatively flat terrain, 
a typical feature mainly vegetation, soil, water, the residents, 
farmland, respectively KUAN filtering, enhanced Lee filtering, 
enhanced filtering FROST, GAMMA filtering done a test. 
Texture complex information to residents, attention should be 
paid in noise reducing, at the same time try to avoid the loss of 
texture information leading to the fuzzy of brink; farmland 
relatively homogeneous, not too rich texture information, 
speckle easy to filter out, but to maximize the ability to 
maintain the edge; water for the homogeneous region, 
regardless of ability to maintain the edge. Taking all these 
factors, according to smoothing effect and maintain ability of 
the edge after noise reducing to choose the enhanced Lee 
filtering (Figure 2, Figure 3). 
Figure 2. Original SAR image 
Figure 3. Enhanced Lee filtering