NDLI: Evaluation of paddy yield and protein estimation methods based on various vegetation indices, NDSI and PLS using an airborne hyperspectral sensor AISA in Shonai Plain, Yamagata, Japan

Content Provider	IEEE Xplore Digital Library
Author	Odagawa, S. Uto, K. Kosugi, Y. Saito, G. Sasaki, Y. Oda, K. Kato, M.
Copyright Year	2011
Description	Author affiliation: Earth Remote Sensing Data Analysis Center, Japan (Kato, M.) \|\| Yamagata Prefectural Government, Japan (Oda, K.) \|\| Yamagata University, Japan (Sasaki, Y.) \|\| Tokyo Institute of Technology, Japan (Uto, K.; Kosugi, Y.; Saito, G.) \|\| Asia Air Survey Co., Ltd., Japan (Odagawa, S.)
Abstract	This paper describes to evaluate rice yield and protein estimation methods based on various vegetation indices (VIs), NDSI and PLS using an airborne hyperspectral sensor AISA in Shonai plane, northeast Japan. In several developing stages, which are the tillering stage (middle June), the maximum tiller number stage (early July) and the dough ripe stage (late August), PLS has stable and high correlation for all stages. NDSI shows several discriminative wavelengths to estimate rice conditions. VIs slightly estimated those situations in the dough ripe stage. In this result, a hybrid method of PLS and NDSI, which is similar to iPLS, suggests the best estimation method for rice yield and protein.
Starting Page	1926
Ending Page	1929
File Size	404059
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049502
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Correlation Estimation Reflectivity Hyperspectral imaging Laboratories PLS Hyperspectral data Rice yield Protein content NDSI
Content Type	Text
Resource Type	Article

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