Improvement the Leaf Water Content Inventory Model Based on the Hyper Spectral Data

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Managhebi Tayebe; Mobasheri MohammadReza

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Journal Paper

Paper Information

Journal: JOURNAL OF SPACE SCIENCE, TECHNOLOGY AND APPLICATIONS Year:2022 | Volume:1 | Issue:2 Page(s): 10-21

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Information Journal Paper

Title

Improvement the Leaf Water Content Inventory Model Based on the Hyper Spectral Data

Author(s)

Managhebi Tayebe | Mobasheri MohammadReza | Issue Writer Certificate

Keywords

Experimental data

Hyperspectral images

Leaf water content

Remote sensing

Spectral curve

Supervised modelling

Abstract

The Leaf water content is a specific index for the assessment of the physiological status of the plant based on the water content of the vegetation. This research provides an appropriate model based on the reflectance spectra between 400 and 2500 nm to estimate the Leaf water content. We examined 53 different species of the well-known Leaf Optical Properties Experiment and a total of 263 Spectral curves were employed in a Supervised modelling procedure. for this purpose, three different linear models were proposed based on the two different indices and their combination. The first index refers to the ratio of reflectance value in two wavelengths and the second one is the ratio of the derivative of the Spectral curve slop in two wavelengths. The experimental results indicate the dependence between the water absorption bands and Leaf water content. Finally determination of coefficient for hybrid linear model, which is used both indices, resulted to be 87 percent, indicating a very good fit. Also, the 0. 06 relative root mean square error represents the aceptable accuracy in the water content modelling.

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APA: Copy

Managhebi, Tayebe, & Mobasheri, MohammadReza. (2022). Improvement the Leaf Water Content Inventory Model Based on the Hyper Spectral Data. JOURNAL OF SPACE SCIENCE, TECHNOLOGY AND APPLICATIONS, 1(2 ), 10-21. SID. https://sid.ir/paper/965594/en

Vancouver: Copy

Managhebi Tayebe, Mobasheri MohammadReza. Improvement the Leaf Water Content Inventory Model Based on the Hyper Spectral Data. JOURNAL OF SPACE SCIENCE, TECHNOLOGY AND APPLICATIONS[Internet]. 2022;1(2 ):10-21. Available from: https://sid.ir/paper/965594/en

IEEE: Copy

Tayebe Managhebi, and MohammadReza Mobasheri, “Improvement the Leaf Water Content Inventory Model Based on the Hyper Spectral Data,” JOURNAL OF SPACE SCIENCE, TECHNOLOGY AND APPLICATIONS, vol. 1, no. 2 , pp. 10–21, 2022, [Online]. Available: https://sid.ir/paper/965594/en

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