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基于TM影像的棉花旱情遥感监测

Remote Sensing Monitoring of Drought in Cotton Based on TM Images

【作者】 孙安利

【导师】 贾建华;

【作者基本信息】 西安科技大学 , 地图制图学与地理信息工程, 2010, 硕士

【摘要】 干旱是一种常见的自然现象,它造成的影响与损失在所有的自然灾害中所占比重较大。对干旱监测与预测,长期以来已开展了多专题多手段的理论与技术研究,并建立了多个业务应用系统对区域或全球尺度旱情进行监测。传统田间实测法和土壤旱情模型法多适用于小范围的农田,遥感影像具有丰富的地物信息,且覆盖地表面积大,并能及时获取,所以对大范围农田土壤旱情的实时监测还需用遥感的手段完成。本文结合863课题“杂交棉田间信息管理技术研究与应用”子课题的工作,以新疆石河子生产建设兵团147和148团场的棉花种植区域为对象,研究大范围农田土壤旱情遥感监测的方法与模型。由于新疆地区接收的卫星数据种类有限,因此课题组选取了实验区应用较多的TM影像,根据棉花旱灾发生关键时期的Landsat TM图像(2008年7月13日、7月29日、8月14日、8月30日)及同步外业调查数据,研究应用简单而有效的棉田旱情监测方法,以期指导生产实践。本文主要研究内容如下:①光学与热红外融合的农田土壤含水量遥感模型与方法研究。应用Landsat TM影像穗帽变换的方法,获取湿度分量,同时结合TM第6波段反演高植被棉花冠层温度信息进行分析、建模和反演棉田含水量。②可见光-近红外光谱特征空间与农田旱情遥感方法研究。应用Red-Nir二维特征空间分布分析,获取土壤线,分别采用垂直干旱指数PDI和改进的垂直干旱指数建模反演棉田旱情,并进行两种模型适用性比较。③基于混合像元分解的土壤含水量遥感监测方法研究。应用混合像元线性解混方法对影像分解,获得土壤纯净像元进行土壤湿度反演,验证结果显示精度达到监测需求。④农田旱情的综合遥感监测方法与应用研究。针对新疆石河子生产建设兵团147和148团场的大田开展实验,反演的结果表明遥感监测的旱情分布规律与实际情况是相符的。同时开展了农田旱情综合反演模型和方法研究,监测与评价棉田土壤墒情,对其进行旱情划分等级,根据旱情等级确定灌溉量,为合理灌溉和水资源高效利用提供了技术支持。

【Abstract】 Drought is a common natural disaster,which leads to the worst impact and largest loss of all natural disasters. The drought monitor and forecasting,since a long time,has developed multi-methods of the theory and the technology research. Meanwhile,has established lots of application systems serve the monitoring of the region drought or the global drought. Traditional Field measurement method and the model of soil drought method are usually used on the small-scare farmland;Remote sensing image has abundant information of ground object,it not only covers large area,but also timely,so for the Large-scale fields,the real-time monitoring of drought needs remote sensing technology.This paper combine with Sub-topics of 863 subject“Research and apply management technique in hybrid cotton field information”.This thesis takes cotton field of Construction Corps 147,148 groups in Xinjiang Shihezi as research object,studies the method and the model in large-scale field’monitoring of drought.As Xinjiang receives the satellite data types are limited,we selected TM image which type is applied more in the area. According to the combination of TM images(July 13,July 29,August 14,August 30in2008)and field data during the crucial moment when drought would occur,we developed a simple and effective method on the monitoring of soil drought in cotton field,which can conduct the production and practice. The main content of this thesis in the following are as:①Research of remote sensing in cropland’s soil moisture model and method falling together optical and thermal infrared.Using tasseled cap transformation method to get moisture data,meanwhile,combined with cotton canopy temperature information for analyze which inverting from the 6-band of TM image,then established model and got the water content of soil.②Research of remote sensing method in Visible - Near Infrared Spectroscopy of space and cropland’s drought.Two-dimensional of the spatial distribution analysis was applied with Red-Nir to gain the soil line,the vertical drought index PDI and the improved vertical drought index was separately used to found cotton field drought model. Moreover,compared the applicability of the two models.③Research of remote sensing monitoring method in soil moisture which based on spectral unmixing.The linear mixed-pixel unmixing method was used to decompose the images and got the soil pure pixel for soil moisture. The precision result reaches the demand of the monitoring.④Research of remote sensing monitoring methods and application in agricultural drought.Carried out Xinjiang Shihezi Construction Corps (147 and 148) field experiments to obtain the results,and which shows the ravages of a drought and the real situation are unanimous.At the same time,research agricultural drought in an integrated model and the method of inversion,monitoring and evaluation of soil moisture content in cotton field,then divide the drought level. So that,people can according to the different drought level to apply the corresponding management measure. Meanwhile,this thesis provide technical support to make irrigating reasonably and water resources utilize efficiently.

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