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| 变量施肥条件下冬小麦长势及品质变异遥感监测 | |
| 引用本文： | 宋晓宇,王纪华,黄文江,阎广建,常 红.变量施肥条件下冬小麦长势及品质变异遥感监测[J].农业工程学报,2009,25(9):155-162. |
| 作者姓名： | 宋晓宇 王纪华 黄文江 阎广建 常 红 |
| 作者单位： | 1. 国家农业信息化工程技术研究中心,北京,100097;北京师范大学地理学与遥感科学学院遥感与GIS研究中心,北京,100875 2. 国家农业信息化工程技术研究中心,北京,100097;北京农产品质量检测与农田环境监测技术研究中心,北京,100097 3. 国家农业信息化工程技术研究中心,北京,100097 4. 北京师范大学地理学与遥感科学学院遥感与GIS研究中心,北京,100875 5. 北京农产品质量检测与农田环境监测技术研究中心,北京,100097 |
| 基金项目： | 北京市自然科学基金项目（4092017）；北京市科技计划课题（D07060500860701）；国家863项目（2006AA10Z271，2006AA120101，2006AA10A308）；农业部行业科技项目（200803037）和948项目（2006-G63（4）） |
| 摘 要： | 卫星遥感数据能够在作物生长期内获取大范围“面状”地物光谱信息，反映作物的长势变异情况，以2005－2006年度国家精准农业研究示范基地冬小麦变量施肥试验为基础，以高空间分辨率卫星遥感影像Quickbird为数据源，结合地面获取的冬小麦品质、产量等数据，研究冬小麦长势及品质的变异情况。研究结果表明，Quickbird光谱参数能够反映冬小麦不同施肥处理小区的长势变异，而冬小麦早期的空间长势变异与其最终产量、品质变异有着密切的关系；冬小麦孕穗后期长势光谱信息与其产量有着很好的正相关关系，而与其品质信息存在着显著的负相关关系，其中OSAVI与产量的相关性达到0.536、GNDVI与冬小麦籽粒蛋白质及湿面筋含量的相关性分别达到了-0.531和-0.535；研究还发现，不同植被指数所反映的作物长势存在一定差异，反映冬小麦群体长势的植被参数和反映冬小麦叶绿素密度的植被指数在指示作物空间长势变异上有所不同。因此，利用遥感影像监测作物长势及其品质空间变异在技术上是可行的。 |
| 关 键 词： | 遥感，生长，作物，冬小麦，Quickbird遥感影像，长势变异 |
| 收稿时间： | 2008/6/18 0:00:00 |
| 修稿时间： | 2009/8/25 0:00:00 |
Monitoring spatial variance of winter wheat growth and grain quality under variable-rate fertilization conditions by remote sensing data |
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| Song Xiaoyu,Wang Jihu,Huang Wenjiang,Yan Guangjian and Chang Hong.Monitoring spatial variance of winter wheat growth and grain quality under variable-rate fertilization conditions by remote sensing data[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(9):155-162. | |
| Authors: | Song Xiaoyu Wang Jihu Huang Wenjiang Yan Guangjian and Chang Hong |
| Institution: | 1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. College of Geography/Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing 100875, China,1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. Beijing Research Center for Agrifood Testing and Farmland Monitoring, Beijing 100097, China,1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China,2. College of Geography/Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing 100875, China and 3. Beijing Research Center for Agrifood Testing and Farmland Monitoring, Beijing 100097, China |
| Abstract: | Remote sensing images acquired by satellite-based sensors have the potential for monitoring crop growth variation because they can provide an area global view for entire field within the crop growth season with scathelessness. This study aimed to use Quickbird image to evaluate the spatial variabilities of winter wheat growth and grain quality under different fertilization levels. The variable-rate fertilization experiment was carried out on National Experimental Station for Precision Agriculture during 2005-2006 the wheat growing season. The results indicated that the spectrum parameters of Quickbird image could reflect the spatial variabilities of winter wheat growth in different fertilization study areas. Meanwhile the spatial variabilities of wheat growth at early stage could reflect the variance of yield and grain quality. The wheat growth information at the booting stage had strong positive correlations with yield, and strong negative correlations with grain protein and wet gluten. The correlation coefficient between OSAVI (optimized soil adjusted vegetation index) and wheat yield was 0.536. It was -0.531 for GNDVI (greenness-normalized difference vegetation index) and grain protein content, and -0.535 for GNDVI and wet gluten, respectively. The study also indicated that diverse spectrum parameters had different sensitivities to the wheat growth spatial variance. So it is feasible to use remote sensing data to investigate the crop growth and quality spatial variance. |
| Keywords: | remote sensing growth crops winter wheat Quickbird imagery spatial variance |
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