水旱地冬小麦叶绿素含量高光谱监测

生态学杂志

水旱地冬小麦叶绿素含量高光谱监测

李方舟¹,冯美臣¹,杨武德^1**,李广信^1,2,王超¹,宋月荷¹,高龙梅¹,张凯³

（¹山西农业大学旱作农业工程研究所，山西太谷 030801； ^2山西省农业科学院作物科学研究所，太原 030032； ^3山西省汾西县农业局土肥站，山西汾西 031500）

出版日期:2013-12-10 发布日期:2013-12-10

Monitoring of winter wheat chlorophyll content in irrigated and dry lands of Shanxi Province of China based on hyperspectral remote sensing.

LI Fang-zhou¹, FENG Mei-chen¹, YANG Wu-de^1**, LI Guang-xin^1,2, WANG Chao¹, SONG Yue-he¹, GAO Long-mei¹, ZHAGN Kai^3

(¹Institute of Dry Farming Engineering, Shanxi Agricultural University, Taigu 030801, Shanxi, China; ²Crop Science Institute, Shanxi Academy of Agricultural Science, Taiyuan 030031, Shanxi, China; ³Soil manure station, Agricultural Bureau of Fenxi, Fenxi 031500, Shanxi, China)

Online:2013-12-10 Published:2013-12-10

摘要/Abstract

摘要： 叶绿素是影响冬小麦产量和品质的重要农学参数，麦田土壤水分的不同会对冬小麦生长产生明显影响，因此实现水旱地冬小麦叶绿素含量的遥感监测具有重要意义。本研究通过分析灌溉地和旱地冬小麦冠层光谱特征，提取敏感波段，并在此基础上通过相关分析，构建叶绿素含量的最佳遥感监测模型。结果表明：灌溉地和旱地的光谱反射及其一阶导数光谱曲线的变化趋势相似，但其值的大小存在较大差异；灌溉地冬小麦冠层光谱特征波段为624、780、958、1053、1082 nm，以FDMSAVI(1082, 624)为变量建立的预测模型效果最佳，检验模型的R²为0.8447；旱地的特征波段为691、848、871、1199和1212 nm，以FDMSAVI(1212, 691)为变量所建模型预测效果，检验模型的R²为0.8627。因此，利用高光谱技术进行水旱地冬小麦叶绿素含量的监测是可行的，可为麦田科学管理及决策提供技术-支持。

Abstract: Chlorophyll content is one of the important agronomic parameters affecting winter wheat yield and quality, while the difference in the farmland soil moisture content can obviously affect the winter wheat growth. It is of significance to realize the hyperspectral remote sensing monitoring of winter wheat chlorophyll content both in irrigated and dry lands. This paper analyzed the winter wheat canopy characteristics in irrigated and dry lands of Shanxi, extracted the sensitive bands, and constructed the optimal remote sensing models of chlorophyll content through correlation analysis. The spectral reflectance and the first derivative spectra had the similar variation trend, but their values had greater differences for the irrigated and dry lands. The spectral characteristic bands of the winter wheat canopy in irrigated lands and in dry lands were 624, 780, 958, 1053, and 1082 nm, and 691, 848, 871, 1199, and 1212 nm, respectively, and the prediction models for monitoring the chlorophyll content of winter wheat in the irrigated lands and dry lands had the best effect when constructed by FDMSAVI (1082, 624) and FDMSAVI (1082, 624), with the R² being 0.8447 and 0.8627, respectively. It was considered that to utilize hyperspectral technology to monitor the chlorophyll content of winter wheat both in irrigated and in dry lands would be feasible, and could provide technical supports for the scientific management and decision-making of wheat field.

李方舟1,冯美臣1,杨武德1**,李广信1,2,王超1,宋月荷1,高龙梅1,张凯3. 水旱地冬小麦叶绿素含量高光谱监测[J]. 生态学杂志.

LI Fang-zhou1, FENG Mei-chen1, YANG Wu-de1**, LI Guang-xin1,2, WANG Chao1, SONG Yue-he1, GAO Long-mei1, ZHAGN Kai3. Monitoring of winter wheat chlorophyll content in irrigated and dry lands of Shanxi Province of China based on hyperspectral remote sensing.[J]. cje.