Comparative Analysis of Different Methods of Leaf Area Index Estimation of Strawberry under Egyptian Condition

Abdelraouf M. Ali, Mohamed Aboelghar, (doi: 10.23953/cloud.ijarsg.405)

Abstract


Leaf area index (LAI) is a factor for vegetative growth parameter. It is defined as leaf area per unit of ground area and could be used as a linkage between plant biophysical, biochemical and spectroscopic parameters. In this research, direct laboratory LAI measurements were tested versus different in situ field measurements for different parameters including LAI derived from LAI-2000 canopy analyzer and six hyperspectral vegetation indices (VIs) (normalized difference vegetation index (NDVI), chlorophyll index (CHI), photochemical reflectance index (PRI), triangular vegetation index (TVI), modified triangular vegetation index (MTVI)), that were generated from ASD-4 field spectroradiometer measurements. The objective is to calibrate the accuracy of LAI-2000 measurements and to examine hyperspectral vegetation indices as estimators of LAI through regression models. A strawberry cultivated area in the Nile delta of Egypt was selected as a study site. Linear regression models were used to calculate LAI through different variables with a high correlation coefficient (0.97, 0.93, 0.90, 0.90, 0.89 and 0.85) for LAoptical, PRI, TVI, NDVI, MTVI and Chl. Respectively. The correlation coefficient between actual and predicted models wasused for validation assessment, the higher accuracy for validation showed high accuracy of all generated models, however, PRI index MTVI, TVI, LAoptical, NDVI and Chl. Index showed relative higher accuracy 0.941, 0.927, 0.927, 0.906, 0.902 and 0.806 respectively. High similarity was found between optical and actual LAI. Generated models are valid during the maximumphase of vegetative growth of strawberry under local conditions of Egyptian Nile delta.


Keywords


Hyperspectral remotely sensed data; LAI; VIs

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