本文選題：雷達(dá)后向散射系數(shù) + 地表粗糙度��； 參考：《蘭州大學(xué)》2015年碩士論文

【摘要】：地表土壤水分在全球水資源中的所占比重較小,但是它卻是非常重要的,它是聯(lián)系地表水和地下水的紐帶,作為陸地水資源循環(huán)過(guò)程中的一個(gè)重要變量,成為眾多水文模型、生態(tài)模型、氣候模型等的一個(gè)輸入?yún)?shù)。土壤水分的變化會(huì)受到土壤特性、氣候因子、地形因子的影響,但反過(guò)來(lái)土壤水分的變化也會(huì)影響氣候的變化,是一個(gè)相互作用的過(guò)程。土壤水分傳統(tǒng)的測(cè)量方法無(wú)法再短時(shí)間內(nèi)獲取大面積土壤水分變化,微波遙感監(jiān)測(cè)由于微波能夠進(jìn)行全天時(shí)、全天候的觀測(cè),并對(duì)表層土壤水分極其敏感,因而被廣泛應(yīng)用到土壤水分的研究當(dāng)中。本研究選擇白龍江流域武都段作為研究區(qū),在研究雷達(dá)數(shù)據(jù)反演土壤水分原理的基礎(chǔ)上,利用C波段Envisat ASAR雷達(dá)數(shù)據(jù)(2009年和2010年)和其他輔助數(shù)據(jù),采用變化檢測(cè)的方法,開展了0-10cm深度土壤水分的反演工作,期望對(duì)基于雷達(dá)數(shù)據(jù)以流域尺度的土壤水分反演工作增色,為研究區(qū)內(nèi)生態(tài)保持、生態(tài)環(huán)境恢復(fù)等研究提供支持。研究得到的主要結(jié)論：(1)根據(jù)前人研究的所得到的植被含水量(VWC)與歸一化濕度指數(shù)(NDMI)之間的轉(zhuǎn)換關(guān)系,建立低矮植被的VWC與NDMI之間的多項(xiàng)式關(guān)系,即可得到VWC；再利用水云模型進(jìn)行植被冠層體散射(σ0veg)的估算,發(fā)現(xiàn)植被體散射對(duì)總散射的貢獻(xiàn)可以忽略不計(jì),即本研究不考慮植被的影響。(2)利用改進(jìn)的積分方程模型AIEM模擬地表粗糙度,發(fā)現(xiàn)雷達(dá)后向散射系數(shù)與土壤水分和地表粗糙度之間表現(xiàn)為一個(gè)對(duì)數(shù)關(guān)系；再利用變化檢測(cè)的方法消除地表粗糙度的影響,建立土壤水分反演的經(jīng)驗(yàn)?zāi)Ｐ?并對(duì)反演結(jié)果做精度驗(yàn)證,得出反演的土壤水分是可靠的,因而該土壤水分的反演模型是適用于本研究區(qū)內(nèi)大面積草地和耕地的土壤水分反演研究的。(3)土壤水分的空間分布規(guī)律為：東北方向和西南方向的土壤水分高,溝道兩側(cè)坡面的土壤含水量是較低的,土壤水分的空間分布是具有時(shí)間穩(wěn)定性；(4)土壤水分空間分布影響因子分析結(jié)果為：土壤的含水量與土壤特性的關(guān)系密切,不同土壤質(zhì)地的土壤含水量不同,一般表現(xiàn)為砂質(zhì)壤土壤土砂土；坡度與土壤水分是表現(xiàn)為顯著的負(fù)相關(guān)關(guān)系,并且不同坡向的土壤水分的差異是非常明顯的,一般表現(xiàn)為向陽(yáng)坡向陰坡,高程與土壤水分呈顯著的正相關(guān)關(guān)系；降雨是影響土壤水分的重要因素之一,與土壤水分表現(xiàn)為正相關(guān)。
[Abstract]:Surface soil water accounts for a relatively small proportion of global water resources, but it is very important. It is a link between surface water and groundwater, and as an important variable in the process of terrestrial water circulation, it has become a lot of hydrological models. An input parameter to an ecological model, a climate model, etc. The change of soil moisture will be affected by soil characteristics, climatic factors and topographic factors, but in turn, the change of soil moisture will also affect the climate change, which is an interactive process. The traditional measurement method of soil moisture can not obtain large area soil moisture change in a short time. Microwave remote sensing monitoring is very sensitive to surface soil moisture because it can be observed all day and all weather. Therefore, it is widely used in the study of soil moisture. In this study, Wudu section of the Bailong River Basin was selected as the study area. On the basis of studying the principle of soil moisture retrieval from radar data, the C-band Envisat ASAR radar data (2009 and 2010) and other auxiliary data were used to detect changes. The inversion of 0-10cm depth soil moisture is carried out, which is expected to enhance the retrieval of soil moisture on watershed scale based on radar data, and to provide support for the study of ecological conservation and ecological environment restoration in the study area. The main conclusion of this study is: (1) the polynomial relationship between VWC and NDMI of low vegetation is established according to the transformation relationship between the water content of vegetation and the normalized humidity index obtained by previous studies. Using water cloud model to estimate vegetation canopy scattering (蟽 0veg), it is found that the contribution of vegetation body scattering to total scattering is negligible. That is, this study does not consider the influence of vegetation. (2) the improved integral equation model AIEM is used to simulate the surface roughness, and it is found that the radar backscattering coefficient is logarithmic with soil moisture and surface roughness. Then using the method of change detection to eliminate the influence of surface roughness, the empirical model of soil moisture inversion is established, and the accuracy of the inversion result is verified, and it is concluded that the soil moisture inversion is reliable. Therefore, the inversion model of soil moisture is suitable for the study of soil moisture inversion of large area grassland and cultivated land in this study area. The spatial distribution law of soil moisture is: the soil moisture is high in the northeast direction and the southwest direction. Soil water content on both sides of the gully slope is relatively low, and the spatial distribution of soil moisture is time-stable. The results show that the relationship between soil moisture content and soil characteristics is close. The soil moisture content of different soil texture is different, generally the sandy loam soil sandy soil, the slope and soil moisture are significantly negative correlation, and the difference of soil moisture in different slope direction is very obvious. Rainfall is one of the most important factors affecting soil moisture, and it is positively correlated with soil moisture.
【學(xué)位授予單位】：蘭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：S152.7

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 程曉娟;楊貴軍;徐新剛;陳天恩;王冬;;基于近地高光譜與TM遙感影像的冬小麥冠層含水量反演[J];麥類作物學(xué)報(bào);2014年02期

2 王培娟;謝東輝;張佳華;許云;;基于不同灌溉條件下冠層光譜與參數(shù)的關(guān)系反演冬小麥冠層含水量[J];光譜學(xué)與光譜分析;2012年01期

3 陳翠玲;姚素梅;肖冰冰;劉歡歡;陶燁;;新鄉(xiāng)市四區(qū)六縣土壤田間持水量抽樣調(diào)查[J];河南科技學(xué)院學(xué)報(bào)(自然科學(xué)版);2011年03期

4 周鵬;丁建麗;王飛;古麗加瑪麗·吾不力;張治廣;;植被覆蓋地表土壤水分遙感反演[J];遙感學(xué)報(bào);2010年05期

5 蔡愛(ài)民;邵蕓;李坤;宮華澤;張風(fēng)麗;陳權(quán);王國(guó)軍;;冬小麥不同生長(zhǎng)期雷達(dá)后向散射特征分析與應(yīng)用[J];農(nóng)業(yè)工程學(xué)報(bào);2010年07期

6 王軍戰(zhàn);鮑艷松;張友靜;屈建軍;張偉民;;多極化多角度ASAR數(shù)據(jù)反演裸露和小麥地表土壤濕度[J];農(nóng)業(yè)工程學(xué)報(bào);2010年06期

7 張友靜;王軍戰(zhàn);鮑艷松;;多源遙感數(shù)據(jù)反演土壤水分方法[J];水科學(xué)進(jìn)展;2010年02期

8 王樹果;李新;韓旭軍;晉銳;;利用多時(shí)相ASAR數(shù)據(jù)反演黑河流域中游地表土壤水分[J];遙感技術(shù)與應(yīng)用;2009年05期

9 陳亮;施建成;蔣玲梅;杜今陽(yáng);;基于物理模型的被動(dòng)微波遙感反演土壤水分[J];水科學(xué)進(jìn)展;2009年05期

10 劉萬(wàn)俠;劉旭攏;王娟;曾文華;;華南農(nóng)作物覆蓋區(qū)土壤水分ENVISAT-ASAR與MODIS數(shù)據(jù)聯(lián)合反演算法研究[J];干旱地區(qū)農(nóng)業(yè)研究;2008年03期

相關(guān)博士學(xué)位論文 前2條

1 鄭興明;東北地區(qū)土壤濕度被動(dòng)微波遙感高精度反演方法研究[D];中國(guó)科學(xué)院研究生院(東北地理與農(nóng)業(yè)生態(tài)研究所);2012年

2 劉偉;植被覆蓋地表極化雷達(dá)土壤水分反演與應(yīng)用研究[D];中國(guó)科學(xué)院研究生院（遙感應(yīng)用研究所）;2005年

相關(guān)碩士學(xué)位論文 前4條

1 寧凱;基于SAR影像反演山區(qū)森林郁閉度的方法研究[D];西南交通大學(xué);2014年

2 屈創(chuàng);基于多源遙感數(shù)據(jù)的白龍江流域土壤水分反演研究[D];蘭州大學(xué);2014年

3 俱戰(zhàn)省;小流域土壤水分時(shí)空分布和地形濕度指數(shù)適用性評(píng)價(jià)研究[D];西北農(nóng)林科技大學(xué);2012年

4 張彩霞;基于DEM的地形濕度指數(shù)提取與應(yīng)用研究[D];西北農(nóng)林科技大學(xué);2006年

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