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[Lecture Notes in Electrical Engineering] Microelectronics, Electromagnetics and Telecommunications Volume 521 (Proceedings of the Fourth ICMEET 2018) || Estimation of Water Contents from Vegetation Using Hyperspectral Indices
摘要： This paper outlines the research objectives to investigate the approaches for assessment of vegetation water contents using hyperspectral remote sensing and moisture sensor. Water contents of crops monitor crop health for precision farming and monitoring. In the present research, spectral indices with some chemical extraction procedures were identi?ed for estimation of water contents of crops. The investigated crop species, namely Vigna Radiata, Vigna Mungo, Pearl Millet, and Sorghum were collected from Aurangabad region of Maharashtra, India. Spectral re?ectance curve of crop growth patterns was measured using ASD ?eld Spec 4 Spectroradiometer and 150 Soil moisture sensor including healthy, diseased, and dry leaves with standard laboratory environment. It is found that there was a positive correlation between WI and Soil moisture sensor with 0.99, 0.76, and 0.97 accuracy.
关键词： Coef?cient of correlation,Crop analysis,Spectral indices,Spectral re?ectance
更新于2025-09-10 09:29:36
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Evaluating Leaf and Canopy Reflectance of Stressed Rice Plants to Monitor Arsenic Contamination
摘要： Arsenic contamination is a serious problem in rice cultivated soils of many developing countries. Hence, it is critical to monitor and control arsenic uptake in rice plants to avoid adverse effects on human health. This study evaluated the feasibility of using re?ectance spectroscopy to monitor arsenic in rice plants. Four arsenic levels were induced in hydroponically grown rice plants with application of 0, 5, 10 and 20 μmol¨ L′1 sodium arsenate. Re?ectance spectra of upper fully expanded leaves were acquired over visible and infrared (NIR) wavelengths. Additionally, canopy re?ectance for the four arsenic levels was simulated using SAIL (Scattering by Arbitrarily Inclined Leaves) model for various soil moisture conditions and leaf area indices (LAI). Further, sensitivity of various vegetative indices (VIs) to arsenic levels was assessed. Results suggest that plants accumulate high arsenic amounts causing plant stress and changes in re?ectance characteristics. All leaf spectra based VIs related strongly with arsenic with coef?cient of determination (r2) greater than 0.6 while at canopy scale, background re?ectance and LAI confounded with spectral signals of arsenic affecting the VIs’ performance. Among studied VIs, combined index, transformed chlorophyll absorption re?ectance index (TCARI)/optimized soil adjusted vegetation index (OSAVI) exhibited higher sensitivity to arsenic levels and better resistance to soil backgrounds and LAI followed by red edge based VIs (modi?ed chlorophyll absorption re?ectance index (MCARI) and TCARI) suggesting that these VIs could prove to be valuable aids for monitoring arsenic in rice ?elds.
关键词： SAIL model,spectral re?ectance,vegetative indices,arsenic uptake,leaf chlorophyll,red edge,plant stress,soil re?ectance,LAI,rice
更新于2025-09-09 09:28:46