秦占飞, 常庆瑞, 申健, 于洋, 刘佳岐. 引黄灌区水稻红边特征及SPAD高光谱预测模型[J]. 武汉大学学报 ( 信息科学版), 2016, 41(9): 1168-1175. DOI: 10.13203/j.whugis20140516
引用本文: 秦占飞, 常庆瑞, 申健, 于洋, 刘佳岐. 引黄灌区水稻红边特征及SPAD高光谱预测模型[J]. 武汉大学学报 ( 信息科学版), 2016, 41(9): 1168-1175. DOI: 10.13203/j.whugis20140516
QIN Zhanfei, CHANG Qingrui, SHEN Jian, YU Yang, LIU Jiaqi. Red Edge Characteristics and SPAD Estimation Model Using Hyperspectral Data for Rice in Ningxia Irrigation Zone[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1168-1175. DOI: 10.13203/j.whugis20140516
Citation: QIN Zhanfei, CHANG Qingrui, SHEN Jian, YU Yang, LIU Jiaqi. Red Edge Characteristics and SPAD Estimation Model Using Hyperspectral Data for Rice in Ningxia Irrigation Zone[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1168-1175. DOI: 10.13203/j.whugis20140516

引黄灌区水稻红边特征及SPAD高光谱预测模型

Red Edge Characteristics and SPAD Estimation Model Using Hyperspectral Data for Rice in Ningxia Irrigation Zone

  • 摘要: 叶绿素含量是评估水稻长势和产量的重要参数。为了实现快速而准确的叶绿素含量估测,以宁夏引黄灌区宁粳43号水稻为试验对象,通过不同的氮素水平试验,测定了水稻在拔节期、抽穗期和乳熟期的冠层高光谱反射率和叶片绿色度土壤、作物分析仪器开发(soil and plant analyzer development,SPAD)值,分析了水稻不同时期冠层光谱的红边变化特征,并建立了SPAD的估测模型。结果表明,水稻叶片SPAD值随供氮水平的增加而增加,随生育期的变化表现为至抽穗期达到最高,而后逐渐降低。冠层光谱反射率随供氮水平的提高在可见光波段降低,在近红外波段增加。冠层光谱的红边位置、红边幅值和红边面积从拔节期到抽穗期呈现出“红移”,至乳熟期呈“蓝移”现象,三个红边参数均随氮素水平的提高而增加。水稻拔节期是以红边面积为变量建立的模型对SPAD预测能力较好,而抽穗期和乳熟期则是以红边位置为参数建立的模型精度较高,与南方稻田叶绿素估算模型有所差异。利用高光谱技术对水稻SPAD值进行定量反演,可为西北地区水稻长势遥感监测提供理论依据。

     

    Abstract: Chlorophyll content is an important parameter when assessing rice cultivation and production. In order to estimate chlorophyll content quickly and precisely, different nitrogen level experiments for Ninggeng 43 were conducted. Canopy hyperspectral reflectance and the SPAD value at different growth stages were measured. We analyzed the red edge characteristics of hyperspectral reflectance at the canopy level and built the SPAD estimation models. Our results revealed that the SPAD value increased with an increasing nitrogen level, and reached a maximum value at the booting stage and then drops. Spectral reflectance gradually became smaller in the visible wavelengths and bigger in the near infrared wavelengths with increasing nitrogen levels, there were 'red shift' and 'blue shift' phenomena from jointing to booting, before the filling stage for the red edge position, amplitude and region of the canopy spectra. All three red edge parameters increased with increases in the nitrogen level. The model with the red edge region area as the independent variable was determined to be the optimalfor the SPAD of the rice canopy at jointing stage, but for the booting and filling stages, the model based on red edge position was more reliable for predicting SPAD values.These results are a little different from rice in south China, using hyperspectral technology can quantitatively retrieve the SPAD values of rice at the canopy level, and therefore provide a theoretical basis for rice growth monitoring based on remote sensing.

     

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