【摘 要】
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Spatially distributed chlorophyll content of crops provides an important indicator of a plants health status, which might provide the crucial information for the agricultural managers.Recent advances
【机 构】
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College of Life Science and Forestry, Chongqing University of Art and Science, Chongqing,402160, Chi
【出 处】
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The Sixth Asian Conference on Precision Agriculture (第六届亚洲精准
论文部分内容阅读
Spatially distributed chlorophyll content of crops provides an important indicator of a plants health status, which might provide the crucial information for the agricultural managers.Recent advances in optical remote sensing led to improved methodologies to monitor crop properties.The red-edge-based vegetation index considered to be one of the most powerful tools for estimating the chlorophyll content (Chl) was usually constructed from in-situ hyperspectral reflectance.In this paper, we present the work done to compare the Chl predictive quality by various red-edge-based vegetation indices based on the CASI data.The results indicated that, of the selected vegetation indices, TCARI/OSAVI-based model estimated Chl (R2 =0.46, RMSE =0.60 and p<0.01) with the best accuracy.To search the optimal vegetation index for Chl estimation, the normalized difference spectral index (NDSI) and ratio spectral index (RSI) were developed by using the waveband combination algorithm.A high linear correlation (R2=0.79, RMSE=0.38 and p<0.01) was acquired by combining the 869.20 and 754.90nm wavebands, then NDSI(869.20, 754.90)was applied to the CASI image to generate the Chl distribution map.It suggests that more fertilizer should be provided for the southwest areas due to the lower Chl.
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