本文選題：MODIS + 土壤含水量�。� 參考：《鄭州大學》2014年碩士論文

【摘要】：土壤含水量是用來監(jiān)測土地退化與干旱的重要指標，它關(guān)系到糧食的生產(chǎn)、植被的長勢與作物的生長狀況等，同時也是水文、氣候、農(nóng)業(yè)與生態(tài)等領(lǐng)域的重要參數(shù)。遙感技術(shù)的快速高效地發(fā)展，使得實時、動態(tài)監(jiān)測和評估大面積的土壤水分狀況成為可能，克服了傳統(tǒng)土壤含水量監(jiān)測方法的不足。 本文主要研究了基于MODIS數(shù)據(jù)的趙口灌區(qū)土壤含水量的遙感反演，通過對土壤含水量以及土壤含水量遙感幾種反演方法的介紹，在裸土或作物生長的初期選取了表觀熱慣量的方法來反演土壤水分的分布狀況，在高植被覆蓋區(qū)域時選取了植被供水指數(shù)的方法來計算土壤水分的分布狀況，并且利用NDVI的值對地表的覆蓋類型進行劃分。用兩種方法相結(jié)合來共同反演趙口灌區(qū)的土壤含水量的分布狀況。主要研究內(nèi)容： （1）本文對國內(nèi)外運用遙感技術(shù)來反演土壤含水量的方法進行了分析研究，對于土壤含水量的反演，傳統(tǒng)的方法不能夠滿足工作的要求，遙感技術(shù)與地理信息系統(tǒng)相結(jié)合提供了新的方法，可以實現(xiàn)高效、快速的大范圍的監(jiān)測。然后對幾種遙感反演土壤含水量的方法的優(yōu)缺點進行了介紹以及綜合比較分析，表觀熱慣量的方法相對來說比較簡單，在對裸土以及作物生長初期的農(nóng)作物的土壤含水量的反演精度比較高，但是對于高植被覆蓋區(qū)域用此方法來反演土壤含水量的精度相對較差，而植被供水指數(shù)法（VSWI）則是適合于高的植被覆蓋度的區(qū)域，在低的植被覆蓋度時，它會夸大植被的影響作用。因此，本研究采用表觀熱慣量與植被供水指數(shù)相結(jié)合的方法來反演土壤含水量。 （2）對遙感影像進行了介紹，因為MODIS數(shù)據(jù)的成像時間快、光譜分辨率高、容易獲取，然后成像的范圍大，這些優(yōu)點是選擇MODIS影像反演土壤含水量的關(guān)鍵所在。然后對MODIS的傳感器及數(shù)據(jù)進行了介紹，最后選取了MOD021KM，也就是分辨率為1000米的數(shù)據(jù)，然后利用ENVI遙感圖像處理軟件對影像進行了數(shù)據(jù)預處理，主要包括：去除條帶噪聲、bow-tie糾正、幾何校正以及根據(jù)ArcGIS的矢量化功能進行矢量的趙口灌區(qū)的邊界圖對處理過的影像進行裁剪。 （3）在利用MODIS遙感影像反演土壤含水量時，為了提高反演的精度，需要首先判斷出研究區(qū)域的地表覆蓋類型，即判斷出地表是屬于裸地/低植被覆蓋區(qū)域還是高植被覆蓋區(qū)域。對于前者，本文采用表觀熱慣量模型，后者采用植被供水指數(shù)法來進行反演，并且利用NDVI（歸一化植被指數(shù)）來進行地域覆蓋類型的劃分，然后對不同的植被覆蓋度區(qū)域采用不同的方法進行反演，以提高利用遙感反演土壤含水量的精度。然后對于模型中的關(guān)鍵參數(shù)進行了反演計算，并生成相應的遙感影像計算結(jié)果圖，最后與實測數(shù)據(jù)相結(jié)合，對實測值與反演值進行了比較分析，，得到趙口灌區(qū)的土壤含水量的分布狀況。結(jié)果表明，本文構(gòu)建的趙口灌區(qū)土壤含水量遙感反演模型提高了土壤水分監(jiān)測的精度。
[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.

【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP79

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