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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (2) : 82-88     DOI: 10.6046/gtzyyg.2019.02.12
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Improvement and application of forced invariance vegetation suppression in southern vegetation area
Zhan YIN1, Lijun ZHANG2, Jianliang DUAN1, Pei ZHANG1
1.China Non-Ferrous Metals Resource Geological Survey, Beijing 100012, China
2.Research Institute of Hunan Provincial Nonferrous Metals Geological Exploration Bureau, Changsha 410083, China
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Abstract  

Vegetation cover causes great interference in rock alteration information extraction. Forcing invariant vegetation suppression technology has achieved good vegetation suppression effect in semi-arid and open terrain area, but the effect remains to be verified in mountainous areas where vegetation is flourishing. Based on the forcing invariant vegetation suppression technology, in the southern vegetation area, the subsection leveling and programming are implemented in the key technical curve leveling steps, which can solve the contradiction between vegetation suppression, color deviation in bare land and information integrity. The vegetation information after subsection leveling is well suppressed, and the underlying bedrock information is prominent and the tone is natural. By using this method to extract remote sensing alteration information, the vegetation area’s remote sensing anomaly is obviously enhanced, the anomaly agrees well with the actual wall rock alteration, and the effect is better.
Keywords forced invariance      vegetation suppression      subsection leveling      alteration information extraction      southern vegetation area     
:  TP79  
Issue Date: 23 May 2019
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Zhan YIN
Lijun ZHANG
Jianliang DUAN
Pei ZHANG
Cite this article:   
Zhan YIN,Lijun ZHANG,Jianliang DUAN, et al. Improvement and application of forced invariance vegetation suppression in southern vegetation area[J]. Remote Sensing for Land & Resources, 2019, 31(2): 82-88.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.02.12     OR     https://www.gtzyyg.com/EN/Y2019/V31/I2/82
Fig.1  Scatter plots of band-wise pixel values vs NDVI
Fig.2  Variation and smoothed curves of band-wise pixel values vs NDVI
Fig.3  Vegetation index corresponding to the classification of ground objects
波段 NDVI分段对应平化值
[0,150) [150,200) [200,255]
B2 750 1 180 620
B3 860 1 230 825
B4 640 1 360 845
B5 125 3 550 3 620
B6 125 4 550 2 850
B7 110 3 360 2 150
Tab.1  Segmental leveling values of each band
Fig.4  Image contrast of forced invariance
Fig.5  Comparison of the effect of remote sensing alteration information
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