empirical regression models for estimating multiyear leaf area index of rice from several vegetation indices at the field scale
Clicks: 299
ID: 159722
2014
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
30.0
/100
299 views
69 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #80 of 499 articles by views in Journal of pharmacological sciences
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 499 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Leaf area index (LAI) is among the most important variables for monitoring crop growth and estimating grain yield. Previous reports have shown that LAI derived from remote sensing data can be effectively applied in crop growth simulation models for improving the accuracy of grain yield estimation. Therefore, precise estimation of LAI from remote sensing data is expected to be useful for global monitoring of crop growth. In this study, as a preliminary step toward application at the regional and global scale, the suitability of several vegetation indices for estimating multi-year LAI were validated against field survey data. In particular, the performance of a vegetation index known as time-series index of plant structure (TIPS), which was developed by the authors, was evaluated by comparison with other well-known vegetation indices. The estimated equation derived from the relationship between TIPS and LAI was more accurate at estimating LAI than were equations derived from other vegetation indices. Although further research is required to demonstrate the effectiveness of TIPS, this study indicates that TIPS has the potential to provide accurate estimates for multi-year LAI at the field scale.
| Reference Key |
maki2014remoteempirical
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Masayasu Maki;Koki Homma |
| Journal | Journal of pharmacological sciences |
| Year | 2014 |
| DOI |
10.3390/rs6064764
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.