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Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces.

Lu S, Lu X, Zhao W, Liu Y, Wang Z, Omasa K - J. Exp. Bot. (2015)

Bottom Line: The results showed that most of the published VIs had strong relationships with LCC on the one-surface dataset, but did not show a clear relationship with LCC when both adaxial and abaxial surface reflectance data were included.It explained 92% of LCC variation in this research, and the root mean square error of the LCC prediction was 5.23 μg/cm(2).This new index is insensitive to the effects of adaxial and abaxial leaf surface structures and is strongly related to the variation in reflectance caused by chlorophyll content.

View Article: PubMed Central - PubMed

Affiliation: School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.

No MeSH data available.


Related in: MedlinePlus

The map for coefficient of determination (R2) between the two-band simple difference (Eq. 1), simple ratio (Eq. 2) and normalized difference (Eq. 3) indices and leaf chlorophyll content for both surfaces of both plant species. (A) simple difference, (B) simple ratio, (C) normalized difference.
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Figure 4: The map for coefficient of determination (R2) between the two-band simple difference (Eq. 1), simple ratio (Eq. 2) and normalized difference (Eq. 3) indices and leaf chlorophyll content for both surfaces of both plant species. (A) simple difference, (B) simple ratio, (C) normalized difference.

Mentions: The R2 values between the LCC and the SD, SR and ND indices are shown in Fig. 4, where the x-axis represents λ1 and the y-axis λ2. In this figure, 230 samples comprising the adaxial and abaxial surfaces of both species, were used to calculate R2. These maps provide an overview of the statistical significance of the indices for all combinations of two wavelengths. They enable efficient extraction of significant peak wavelengths as well as the extent of the effective regions for assessment of Chl content. The results showed that the LCC-sensitive regions mainly involved two areas. One was made up of red edge and blue wavelengths, with λ1 ranging from 705 to 715nm and λ2 from 420 to 440nm.


Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces.

Lu S, Lu X, Zhao W, Liu Y, Wang Z, Omasa K - J. Exp. Bot. (2015)

The map for coefficient of determination (R2) between the two-band simple difference (Eq. 1), simple ratio (Eq. 2) and normalized difference (Eq. 3) indices and leaf chlorophyll content for both surfaces of both plant species. (A) simple difference, (B) simple ratio, (C) normalized difference.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585420&req=5

Figure 4: The map for coefficient of determination (R2) between the two-band simple difference (Eq. 1), simple ratio (Eq. 2) and normalized difference (Eq. 3) indices and leaf chlorophyll content for both surfaces of both plant species. (A) simple difference, (B) simple ratio, (C) normalized difference.
Mentions: The R2 values between the LCC and the SD, SR and ND indices are shown in Fig. 4, where the x-axis represents λ1 and the y-axis λ2. In this figure, 230 samples comprising the adaxial and abaxial surfaces of both species, were used to calculate R2. These maps provide an overview of the statistical significance of the indices for all combinations of two wavelengths. They enable efficient extraction of significant peak wavelengths as well as the extent of the effective regions for assessment of Chl content. The results showed that the LCC-sensitive regions mainly involved two areas. One was made up of red edge and blue wavelengths, with λ1 ranging from 705 to 715nm and λ2 from 420 to 440nm.

Bottom Line: The results showed that most of the published VIs had strong relationships with LCC on the one-surface dataset, but did not show a clear relationship with LCC when both adaxial and abaxial surface reflectance data were included.It explained 92% of LCC variation in this research, and the root mean square error of the LCC prediction was 5.23 μg/cm(2).This new index is insensitive to the effects of adaxial and abaxial leaf surface structures and is strongly related to the variation in reflectance caused by chlorophyll content.

View Article: PubMed Central - PubMed

Affiliation: School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.

No MeSH data available.


Related in: MedlinePlus