河南省赵口灌区土壤含水量遥感反演研究

发布时间：2018-04-27 20:34

本文选题：MODIS + 土壤含水量　；参考：《郑州大学》2014年硕士论文

【摘要】：土壤含水量是用来监测土地退化与干旱的重要指标，它关系到粮食的生产、植被的长势与作物的生长状况等，同时也是水文、气候、农业与生态等领域的重要参数。遥感技术的快速高效地发展，使得实时、动态监测和评估大面积的土壤水分状况成为可能，克服了传统土壤含水量监测方法的不足。本文主要研究了基于MODIS数据的赵口灌区土壤含水量的遥感反演，通过对土壤含水量以及土壤含水量遥感几种反演方法的介绍，在裸土或作物生长的初期选取了表观热惯量的方法来反演土壤水分的分布状况，在高植被覆盖区域时选取了植被供水指数的方法来计算土壤水分的分布状况，并且利用NDVI的值对地表的覆盖类型进行划分。用两种方法相结合来共同反演赵口灌区的土壤含水量的分布状况。主要研究内容：（1）本文对国内外运用遥感技术来反演土壤含水量的方法进行了分析研究，对于土壤含水量的反演，传统的方法不能够满足工作的要求，遥感技术与地理信息系统相结合提供了新的方法，可以实现高效、快速的大范围的监测。然后对几种遥感反演土壤含水量的方法的优缺点进行了介绍以及综合比较分析，表观热惯量的方法相对来说比较简单，在对裸土以及作物生长初期的农作物的土壤含水量的反演精度比较高，但是对于高植被覆盖区域用此方法来反演土壤含水量的精度相对较差，而植被供水指数法（VSWI）则是适合于高的植被覆盖度的区域，在低的植被覆盖度时，它会夸大植被的影响作用。因此，本研究采用表观热惯量与植被供水指数相结合的方法来反演土壤含水量。（2）对遥感影像进行了介绍，因为MODIS数据的成像时间快、光谱分辨率高、容易获取，然后成像的范围大，这些优点是选择MODIS影像反演土壤含水量的关键所在。然后对MODIS的传感器及数据进行了介绍，最后选取了MOD021KM，也就是分辨率为1000米的数据，然后利用ENVI遥感图像处理软件对影像进行了数据预处理，主要包括：去除条带噪声、bow-tie纠正、几何校正以及根据ArcGIS的矢量化功能进行矢量的赵口灌区的边界图对处理过的影像进行裁剪。（3）在利用MODIS遥感影像反演土壤含水量时，为了提高反演的精度，需要首先判断出研究区域的地表覆盖类型，即判断出地表是属于裸地/低植被覆盖区域还是高植被覆盖区域。对于前者，本文采用表观热惯量模型，后者采用植被供水指数法来进行反演，并且利用NDVI（归一化植被指数）来进行地域覆盖类型的划分，然后对不同的植被覆盖度区域采用不同的方法进行反演，以提高利用遥感反演土壤含水量的精度。然后对于模型中的关键参数进行了反演计算，并生成相应的遥感影像计算结果图，最后与实测数据相结合，对实测值与反演值进行了比较分析，，得到赵口灌区的土壤含水量的分布状况。结果表明，本文构建的赵口灌区土壤含水量遥感反演模型提高了土壤水分监测的精度。
[Abstract]:Soil water content is an important indicator for monitoring land degradation and drought. It is related to the production of grain, the growth of vegetation and the growth of crops. It is also an important parameter in the fields of hydrology, climate, agriculture and ecology. The rapid and efficient development of remote sensing technology makes the real-time, dynamic monitoring and evaluation of large area soil moisture. It is possible to overcome the shortcomings of traditional soil moisture monitoring methods.
This paper mainly studies remote sensing inversion of soil water content in Zhao Kou irrigation area based on MODIS data. By introducing several inversion methods of soil water content and soil moisture content, the method of apparent thermal inertia is selected to retrieve the distribution of soil moisture in the early stage of bare soil or crop growth. The distribution of soil moisture is calculated by the method of vegetation water supply index, and the cover types of the surface are divided by the value of NDVI. The distribution of soil water content in Zhao Kou irrigation area is retrieved by two methods. The main contents are as follows:
(1) this paper analyses the method of using remote sensing technology to invert the soil moisture content at home and abroad. For the inversion of soil water content, the traditional method can not meet the requirements of the work. The combination of remote sensing technology and geographic information system provides a new method, which can realize high efficiency, rapid and large range monitoring. Then, several kinds of methods can be realized. The advantages and disadvantages of remote sensing method for soil water content inversion are introduced and comprehensive comparative analysis. The method of apparent thermal inertia is relatively simple. The inversion accuracy of soil water content in the bare soil and the early crop growth is relatively high, but the method is used to invert the soil moisture content in the high vegetation covered area. The precision is relatively poor, and the vegetation water supply index (VSWI) is a suitable area for high vegetation coverage. It exaggerates the effect of vegetation on low vegetation coverage. Therefore, this study uses the method of apparent thermal inertia and vegetation water supply index to reverse the soil water content.
(2) the remote sensing images are introduced, because the imaging time of the MODIS data is fast, the spectral resolution is high, and the range of the imaging is large. These advantages are the key to the selection of the soil moisture content of the MODIS image. Then the sensor and data of the MODIS are introduced. Finally, the MOD021KM is selected, that is the resolution is 1000 meters. And then using the ENVI remote sensing image processing software, the image is preprocessed, including the removal of strip noise, bow-tie correction, geometric correction, and the boundary map of the Zhao Kou irrigation area based on the vectorization function of ArcGIS to cut the processed images.
(3) in the use of MODIS remote sensing image inversion of soil water content, in order to improve the accuracy of the inversion, it is necessary to determine the surface cover type of the study area first, that is to judge whether the surface belongs to the bare land / low vegetation cover area or the high vegetation cover area. For the former, the apparent thermal inertia model is used in this paper, and the latter adopts the vegetation water supply index. The method is used to invert, and the NDVI (normalized vegetation index) is used to divide the region cover type, and then the different vegetation coverage regions are retrieved by different methods to improve the accuracy of using remote sensing to retrieve the soil water content. Then, the key parameters in the model are retrieved and the corresponding teleconnection is generated. In the end, the measured data and the measured data are combined to compare the measured values with the inversion values. The distribution of soil water content in Zhao Kou irrigation area is obtained. The results show that the remote sensing inversion model of soil water content in Zhao Kou irrigation area has improved the accuracy of soil water monitoring.

【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP79

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