Conference Proceeding

Discussion on the requirements of VNIR hyperspectral data for agricultural applications according to PHI data and CSAM model

Inst. of Remote Sensing Applications, Acad. Sinica, Beijing;
02/2001; DOI:10.1109/ICII.2001.982731 ISBN: 0-7803-7010-4 pp.115 - 120 vol.1 In proceeding of: Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on, Volume: 1
Source: IEEE Xplore

ABSTRACT According to the application of PHI data to agricultural
information extraction both in Changzhou, China and Nagano. Japan. we
found that the results closely depend on the hyperspectral remote
sensing data quality. As the spectral features of vegetation are
particular with high shape similarity but with high intensity variation,
the quality requirements are special. The general factors of pixel size,
band combination and noise limit for different information objects are
discussed in this paper. According to the two models of CSAM and IARS,
with rice as example, it shows that a pixel size of 1.2 meter is
suitable in the areas such as Changzhou and Nagano. The top-priority
range of VNIR should be the red edge of 670-780 nm and fine-division is
necessary with a suggestion of about 40 bands with 3 nm resolution.
While in belts of 400-670 and 780-900 nm. wider and less bands are
acceptable. According to the application of IARS and the linear property
of rice spectra. it was suggested that S/N in order of ×10 is
enough for plant recognition. but for species classification for a
certain plant, it should be square with all order up to ×102
-× 103

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Keywords

3 nm resolution
 
certain plant
 
Changzhou
 
China
 
hyperspectral remote
 
linear property
 
noise limit
 
particular
 
PHI data
 
pixel size
 
plant recognition
 
red edge
 
shape similarity
 
species classification
 
spectral features
 
suitable
 
two models
 
wider
 

Yongchao Zhao