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核农学报  2015 

不同播期冬小麦地上干物质的光谱监测

DOI: 10.11869/j.issn.100-8551.2015.06.1158, PP. 1158-1164

Keywords: 冬小麦,播期,地上干物质,高光谱遥感,监测模型

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Abstract:

为了更好地利用遥感技术快速、准确监测冬小麦地上干物质,本试验对不同播期条件下京9428、超优66在开花期的地上干物质和冠层光谱反射率进行了测定,通过提取地上干物质的光谱敏感波段和植被指数,构建冬小麦地上干物质光谱监测模型。结果表明,地上干物质与原始光谱的一阶微分处理的相关性优于原始光谱,据此提取的特征波段和构建植被指数也均与地上干物质达到极显著水平,所构建的光谱监测的预测效果较好,其中以FDEVI(730,850)为变量建立的模型监测精度最高;播期组合的地上干物质与FDEVI(730,850)有很高的相关性,具有一定实践意义。此外研究发现,播期1(10月1日)条件下的模型决定系数达0.8685,经验证,RRMSE和RE也较小,故该播期适宜于冬小麦地上干物质监测。本研究可为冬小麦地上干物质无损动态监测及生产科学管理提供一定技术依据和实践参考。

 References

[1]  刘占宇,黄敬峰,吴新宏,董永平,王福民,刘朋涛.草地生物量的高光谱遥感估算模型[J].农业工程学报,2006,22(2):111-115
[2]  Hansen P M, Schjoerring J K.Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression[J].Remote Sensing of Environment,2003,86(4): 542-553
[3]  Ren H R, Zhou G S, Zhang X S.Estimation of green aboveground biomass of desert steppe in Inner Mongolia based on red-edge reectance curve area method [J].Biosystems Engineering,2011,109(4):385-395
[4]  黄春燕,王登伟,陈冠文,袁杰,祁亚琴,陈燕,程诚.基于高光谱植被指数的棉花干物质积累估算模型研究[J].棉花学报,2006,18(2):115-119
[5]  Todd S W, Hoffer R M, Milchunas D G.Biomass estimation on grazed and ungrazed rangelands using spectral indices[J].International Journal of Remote Sensing,1998,19(3):427-438
[6]  Mutanga O, Skidmorea A K.Narrow band vegetation indices overcome the saturation problem in biomass estimation [J].International Journal of Remote Sensing,2004,25(19):3999-4012
[7]  Fu Y Y, Yang G J, Wang J H.Winter wheat biomass estimation based on spectral indices, band depth analysis and partial least squares regression using hyperspectral measurements[J].Computers and Electronics in Agriculture,2014,100:51-59
[8]  王渊,王福民,黄敬峰.油菜不同组分生物量光谱遥感估算模型[J].浙江农业学报,2004,16(2):79-83
[9]  宋开山,张柏,李方,段洪涛,王宗明.高光谱反射率与大豆叶面积及地上鲜生物量的相关分析[J].农业工程学报,2005,21(1):36-40
[10]  傅玮东,刘绍民,黄敬峰.冬小麦生物量遥感监测模型的研究[J].干旱区资源与环境,1997,11(1):84-89
[11]  王秀珍,黄敬峰,李云梅,王人潮.水稻地上鲜生物量的高光谱遥感估算模型研究[J].作物学报,2003,29(6):815-821
[12]  Martin L G, Miao Y X, Yuan F.Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages [J].Field Crops Research,2014,155(1):42-55
[13]  马勤建,王登伟,黄春燕,袁杰,陈燕,赵鹏举.棉花叶面积指数和地上干物质积累量的高光谱估算模型研究[J].棉花学报,2008,20(3):217-222
[14]  张凯,王润元,王小平,赵鸿,韩海涛.黄土高原春小麦地上鲜生物量高光谱遥感估算模型[J].生态学杂志,2009,28(6):1155-1161
[15]  候学会,牛铮,黄妮,许时光.小麦生物量与真实叶面积指数的高光谱遥感估算模型[J].国土资源遥感,2012,95(4):30-35
[16]  朱艳,吴华兵,田永超,姚霞,周冶国,曹卫星.基于冠层反射光谱的棉花干物质积累量估测[J].应用生态学报,2008,19(1):105-109
[17]  Thenkabil P S, Smith R B, De Pauw E.Hyperspectral vegetation indices and their relationships with agricultural crop characteristics [J].Remote Sensing of Environment,2000,71(2):158-182
[18]  王超,冯美臣,王君杰,肖璐洁,杨武德.基于光谱遥感的冬小麦籽粒淀粉积累量的监测[J].中国生态农业学报,2013,21(4):440-447
[19]  李彩虹,冯美臣,王超,尹超.不同播期冬小麦叶绿素含量的冠层光谱响应研究[J].核农学报,2014,28(2):309-317
[20]  李凤秀,张柏,刘殿伟,宋开山.洪河自然保护区乌拉苔草生物量高光谱遥感估算模型[J].湿地科学,2008,6(1):51-59
[21]  李凤秀,张柏,刘殿伟,王宗明,宋开山,靳华安,刘焕军.湿地小叶章叶绿素含量的高光谱遥感估算模型[J].生态学杂志,2008,27(7):1077-1083
[22]  Jordan C F. Derivation of leaf area index from quality of light on the forest floor [J]. Ecology, 1969, 50: 663-666
[23]  Richardson A J,Wiegand C L. Distinguishing vegetation from soil background information [J].Photogrammetry Engineering & Remote Sensing,1997,43(12):1541-1552
[24]  李爱国,宋晓霞,吴春西.播期播量对国审小麦新品种漯麦9号产量的影响[J].作物研究,2012,26(6):635-638
[25]  李豪圣,宋健民,刘爱峰,程敦公,王西芝,杜长林,赵振东,刘建军.播期和种植密度对超高产小麦'济麦22’产量及其构成因素的影响[J].中国农学通报,2011,27(5):243-248
[26]  刘明,陶洪斌,王璞,易镇邪,鲁来清,王宇.播期对春玉米生长发育与产量形成的影响[J].中国生态农业学报,2009,17(1):18-23
[27]  唐延林,王纪华,黄敬峰,王人潮,何秋霞.水稻成熟过程中高光谱与叶绿素、类胡萝卜素的变化规律研究[J].农业工程学报,2003,19(6):167-173
[28]  Compton J T.Remote sensing of leaf water content in the near infrared [J]. Remote Sensing of Environment,1980,10(1):23-32
[29]  王备战,王来刚,温暖,任瑞萍,郑涛,杨武德.基于多源数据的县域冬小麦氮肥调控管理分区[J].农业工程学报,2012,28(17):95-101
[30]  李方舟,冯美臣,杨武德,李广信,王超,宋月荷,高龙梅,张凯.水旱地冬小麦叶绿素含量高光谱监测[J].生态学杂志,2013,32(12):3213-3218
[31]  Heege H J, Reusch S, Thiessen E.Prospects and results for optical systems for site-specific on-the-go control of nitrogen-top-dressing in Germany[J].Precision Agriculture,2008,9(3):115-131
[32]  Renjean J L, Breon F M. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements [J].Remote Sensing of Environment, 1995, 51: 357-384
[33]  Liu H Q, Huete A R. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise[J].IEEE Transactions on Geoscience and Remote Sensing, 1995,33(1):457-465

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