本文關(guān)鍵詞： 土壤水分 宇宙射線中子法 遙感 像元尺度 耦合驗證　出處：《中國水利水電科學研究院》2017年碩士論文　論文類型：學位論文

【摘要】：土壤水分是水循環(huán)、能量循環(huán)和生物地球化學循環(huán)過程中的基本組成部分,在水文、氣候、農(nóng)業(yè)和生態(tài)等研究領(lǐng)域都具有十分重要的作用。大范圍的土壤水分遙感監(jiān)測過多地依賴點測量結(jié)果,這兩種方法空間尺度上的較大差異導致遙感反演結(jié)果的精度難以得到保證。因此,本研究基于區(qū)域尺度的宇宙射線中子法,開展烘干稱重法和介電特性法FDR點測量、宇宙射線中子法CRS區(qū)域監(jiān)測和像元遙感反演的多尺度土壤水分協(xié)同觀測試驗和耦合驗證研究。該研究不僅能夠豐富土壤水分測量技術(shù),而且能夠從像元尺度上為遙感反演結(jié)果提供有效的驗證手段,對水文、生態(tài)和氣候等科學研究都具有重要作用。本論文的研究內(nèi)容和結(jié)論主要有:荒漠草原宇宙射線中子法土壤水分測量。利用土壤水分的烘干稱重法測量結(jié)果以及FDR和CRS的連續(xù)測量結(jié)果,開展了宇宙射線中子法在荒漠草原的土壤水分測量應用研究,證明該方法對荒漠草原土壤水分的測量精度能夠滿足科學研究和實際應用的要求,具有較好的發(fā)展?jié)摿�。通過對植被和降雨進行影響因素分析,證明研究區(qū)植被對測量結(jié)果的影響很小,同時證明CRS對降雨的響應比FDR靈敏�；谥凶訑�(shù)與氫的密切相關(guān)性,本研究利用不同位置的中子強度在中子總量中的權(quán)重作為對應位置土壤水分的權(quán)重,構(gòu)建土壤水分尺度轉(zhuǎn)換模型,并提出了基于中子強度的加權(quán)法;通過四種加權(quán)方法的對比分析,發(fā)現(xiàn)基于中子強度加權(quán)法的平均土壤水分與CRS 土壤水分的擬合效果最好,相關(guān)系數(shù)高達0.92;擇優(yōu)選取該加權(quán)法作為模型參數(shù)(權(quán)重系數(shù))校準的最佳方案,由此建立了 CRS測量足跡內(nèi)的尺度轉(zhuǎn)換模型;基于權(quán)重系數(shù)的最優(yōu)解,分析出CRS測量足跡的實際空間特征:①CRS的足跡范圍不是標準的圓柱體,而是扁平的陀螺型;②關(guān)于土壤水分點測量結(jié)果的權(quán)重,垂直權(quán)重隨深度的增大而減小,水平權(quán)重隨徑向距離的增大而減小。熱慣量法土壤水分遙感反演。采用熱慣量法,分別開展Landsat 8 30m衛(wèi)星影像數(shù)據(jù)和MODIS 1km數(shù)據(jù)產(chǎn)品的土壤水分遙感反演。其中,對于Landsat8數(shù)據(jù)的熱慣量法反演參數(shù)溫度日較差△T,通過結(jié)合Landsat8日地表溫度反演結(jié)果和MODIS夜地表溫度產(chǎn)品計算得到。多尺度土壤水分測量結(jié)果耦合驗證。通過FDR點測量、CRS區(qū)域測量和遙感像元反演的多尺度土壤水分協(xié)同觀測試驗,基于CRS足跡范圍內(nèi)的尺度轉(zhuǎn)換模型,統(tǒng)一不同測量方法的空間尺度,開展不同尺度土壤水分觀測結(jié)果的耦合驗證。CRS與FDR 土壤含水量擬合的R2高達0.84,RMSE僅為0.0128kg/kg,相對誤差多數(shù)都在20%以內(nèi),說明宇宙射線中子法的測量結(jié)果精度較高,能夠滿足科學研究和生產(chǎn)應用的要求。FDR 土壤含水量與30m像元和1km像元遙感反演結(jié)果擬合的R2均為0.74,CRS與兩種像元反演結(jié)果擬合的R2分別為0.82和0.81,說明CRS區(qū)域土壤含水量對遙感反演結(jié)果的驗證效果更佳。
[Abstract]:Soil moisture is a basic component of the water cycle, energy cycle and biogeochemical cycle processes in hydrology and climate. Research fields such as agriculture and ecology play a very important role. A wide range of remote sensing monitoring of soil moisture depends too much on the results of point measurement. The difference between the two methods on spatial scale makes the precision of remote sensing inversion difficult to be guaranteed. Therefore, the cosmic ray neutron method based on regional scale is studied in this paper. The measurement of FDR points by drying weighing method and dielectric characteristic method was carried out. The multi-scale soil moisture cooperative observation experiment and coupling verification study of cosmic ray neutron method CRS area monitoring and pixel remote sensing inversion can not only enrich the soil moisture measurement technology. And it can provide an effective verification method for remote sensing inversion results from the pixel scale to hydrology. Ecological and climatic studies play an important role. The main contents and conclusions of this paper are as follows:. Soil moisture was measured by cosmic ray neutron method in desert steppe. The results were measured by drying and weighing method of soil moisture and the continuous measurement results of FDR and CRS. The application of cosmic ray neutron method to soil moisture measurement in desert steppe has been studied. It is proved that the precision of this method can meet the requirements of scientific research and practical application. Through the analysis of the influence factors of vegetation and rainfall, it is proved that the vegetation in the study area has little effect on the measured results. It is also proved that the response of CRS to rainfall is more sensitive than that of FDR, based on the close correlation between neutron number and hydrogen. In this study, the weight of neutron intensity in the total neutron amount was used as the weight of soil moisture in the corresponding position, and the scale conversion model of soil moisture was constructed, and the weighting method based on neutron intensity was proposed. Through the comparison and analysis of four weighting methods, it was found that the fitting effect of average soil moisture and CRS soil moisture based on neutron intensity weighting method was the best, and the correlation coefficient was as high as 0.92; The weighting method is chosen as the best method for calibration of model parameters (weight coefficient), and the scale conversion model within the footprint of CRS is established. Based on the optimal solution of weight coefficient, the actual spatial feature of CRS measurement footprint: 1: 1CRS is analyzed. The footprint range of CRS is not a standard cylinder, but a flat gyroscope. 2 for the weight of soil moisture measurement results, the vertical weight decreases with the increase of depth, and the horizontal weight decreases with the increase of radial distance. The thermal inertia method is used to retrieve soil moisture by remote sensing. Soil moisture remote sensing inversion of Landsat 830m satellite image data and MODIS 1km data products were carried out respectively. For the Landsat8 data, the thermal inertia method is used to retrieve the daily temperature difference T of the parameters. By combining the Landsat8 daily surface temperature inversion results with the MODIS night surface temperature products calculation. The results of multi-scale soil moisture measurement coupled verification. Through the FDR point measurement. Based on the scale conversion model in the range of CRS footprint, the multi-scale soil moisture cooperative observation experiment based on CRS regional measurement and remote sensing pixel inversion unifies the spatial scale of different measurement methods. The results of soil moisture observation at different scales were coupled to verify that the R2 fitting between CRS and FDR soil moisture content was as high as 0.84kg / kg, only 0.0128kg / kg. Most of the relative errors are less than 20%, which indicates that the accuracy of the cosmic ray neutron method is high. FDR soil moisture content fitting with 30m pixel and 1km pixel fitting R2 is 0.74. The R2 fitting between CRS and two kinds of pixel inversion results is 0.82 and 0.81respectively, which indicates that the soil moisture content in CRS area is more effective for the validation of remote sensing inversion results.
【學位授予單位】：中國水利水電科學研究院
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：S812.2

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