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Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
Published on: August 29, 2019
[New index for crop canopy fresh biomass estimation]
Peng-Fei Chen1, Tremblay Nicolas, Ji-Hua Wang
1College of Resources and Environment Science, China Agricultural University, Beijing 100193, China. pengfeichen-001@hotmail.com
Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|April 14, 2010
Summary
A new vegetation index, the red-edge triangular vegetation index (RTVI), accurately estimates corn fresh biomass, even at high levels. This remote sensing tool offers improved precision for agricultural monitoring.
Area of Science:
- Agricultural Science
- Remote Sensing
- Plant Physiology
Background:
- Accurate estimation of crop biomass is crucial for agricultural management and yield prediction.
- Existing vegetation indices often struggle with saturation at high biomass levels, limiting their utility.
Purpose of the Study:
- To develop and validate a novel vegetation index for precise corn canopy fresh biomass estimation.
- To improve remote sensing capabilities for high biomass scenarios.
Main Methods:
- Collected hyperspectral reflectance data from corn canopies (2004-2008).
- Measured fresh biomass through destructive sampling.
- Designed the red-edge triangular vegetation index (RTVI) and compared it with existing indices.
- Validated RTVI using Compact Airborne Spectrographic Imager (CASI) data.
Main Results:
- RTVI demonstrated superior performance in predicting canopy fresh biomass compared to existing indices.
- The power fit model for RTVI and biomass yielded a high coefficient of determination (R² = 0.96).
- Validation with CASI imagery showed a strong relationship (R² = 0.58) between predicted and actual biomass.
Conclusions:
- The developed RTVI is a highly effective tool for estimating corn fresh biomass, particularly at high levels.
- RTVI offers enhanced sensitivity and accuracy for remote sensing-based biomass assessment in agriculture.
