本文選題：青藏高原 + 時(shí)空分布��； 參考：《中國(guó)地質(zhì)大學(xué)(北京)》2016年博士論文

【摘要】：近幾十年中,很多研究通過(guò)簡(jiǎn)單的空間化、定量化、多尺度化以及時(shí)間序列分析的方法來(lái)探討區(qū)域植被和環(huán)境因素的結(jié)構(gòu)、功能以及相關(guān)變化過(guò)程,具體概括為兩點(diǎn):1)時(shí)間序列上主要是簡(jiǎn)單的一次線性統(tǒng)計(jì)分析;2)空間分布上主要從空間自相關(guān)性的角度出發(fā),簡(jiǎn)單利用Moran's I系數(shù)或者半變異函數(shù)進(jìn)行評(píng)價(jià),分析不夠深入具體,且在植被綠度遙感監(jiān)測(cè)方面的應(yīng)用較少,而且地表NDVI和氣候變量的相關(guān)性的研究尚處在初級(jí)階段,其影響程度隨著地理位置的改變也不相同�？梢哉f(shuō)利用遙感手段綜合、充分地從時(shí)間序列上和空間分布上,定量化地研究植被時(shí)空變化、空間異質(zhì)性以及時(shí)空相關(guān)性的工作相對(duì)較少。本論文基于1982-2006年GIMMS AVHRR NDVI數(shù)據(jù)和2001-2010年MODIS NDVI數(shù)據(jù)利用一次分段線性回歸方法、空間自相關(guān)分析、半變異函數(shù)分析、分維分析的方法來(lái)研究青藏高原植被在時(shí)間序列和空間分布上的變化,并借助MERRA氣候數(shù)據(jù)(平均氣溫、降水總量、太陽(yáng)總輻射)和中國(guó)氣象站點(diǎn)日值氣候資料(年均最小相對(duì)濕度、年均日最高氣溫、年均日最低氣溫、年總?cè)照諘r(shí)數(shù)、年平均相對(duì)濕度、年平均氣溫、年平均風(fēng)速以及年總降水量)綜合評(píng)估近三十年的時(shí)空變化特征,主要完成的研究?jī)?nèi)容和結(jié)論如下:(1)利用線性回歸方法分析時(shí)間序列數(shù)據(jù),就植被整體、各植被類(lèi)型以及區(qū)域植被變化方面展開(kāi)研究,結(jié)果發(fā)現(xiàn):整體植被綠度具有增長(zhǎng)的趨向;具有較高綠度水平的植被類(lèi)型在氣候變化的影響下具有較高的敏感度;區(qū)域化研究中,人類(lèi)對(duì)植被的影響非常顯著。(2)鑒于時(shí)間序列數(shù)據(jù)中存在突變點(diǎn)情況,提出了使用分段線性回歸的方法來(lái)監(jiān)測(cè)植被變化,結(jié)果表明:該方法能夠成功監(jiān)測(cè)一次線性回歸方法并不能監(jiān)測(cè)到的突變情況。(3)開(kāi)展三維空間維度變化分析、空間自相關(guān)分析、半變異函數(shù)分析和分維分析,結(jié)果發(fā)現(xiàn):植被具有正的空間自相關(guān)性且表現(xiàn)出明顯的高值和低值聚集區(qū);結(jié)構(gòu)性因子在空間總變異中占主導(dǎo)地位(70%),地貌特征和山脈走勢(shì)導(dǎo)致植被空間分布主要沿東南-西北方向展布;區(qū)域的氣候條件、地形地貌以及人類(lèi)活動(dòng)對(duì)植被空間分布的影響在逐年增強(qiáng)。(4)鑒于研究數(shù)據(jù)中存在的非平穩(wěn)現(xiàn)象,提出采用低階二次多項(xiàng)式擬合趨勢(shì)的方法來(lái)達(dá)到去趨勢(shì)的目的,結(jié)果表明:該方法成功地達(dá)到了預(yù)期目的。(5)研究全年MERRA數(shù)據(jù)和AVHRR數(shù)據(jù)以及生長(zhǎng)季站點(diǎn)日值資料和MODIS數(shù)據(jù)的相關(guān)性,結(jié)果發(fā)現(xiàn):在不同時(shí)間尺度不同空間尺度上,植被與氣候變量的相關(guān)性是基本一致的;植被類(lèi)型不同,其主要?dú)夂蝌?qū)動(dòng)變量也不同。
[Abstract]:In recent decades, many studies have explored the structure, functions and related processes of regional vegetation and environmental factors through simple spatial, quantitative, multi-scale and time series analysis.It is summed up specifically as two points and one) the time series is mainly a simple one-order linear statistical analysis.) the spatial distribution is mainly from the angle of spatial autocorrelation. The simple use of Moran's I coefficient or semi-variogram to evaluate, the analysis is not deep enough to be specific.Moreover, the application of remote sensing in vegetation greening monitoring is rare, and the correlation between surface NDVI and climate variables is still in the primary stage, and its influence degree varies with the change of geographical location.It can be said that the use of remote sensing means synthesis, fully from the time series and spatial distribution, quantitative study of space-time changes of vegetation, spatial heterogeneity and space-time correlation work is relatively less.This paper is based on GIMMS AVHRR NDVI data from 1982 to 2006 and MODIS NDVI data from 2001-2010 to 2001-2010 using a piecewise linear regression method, spatial autocorrelation analysis, semi-variable function analysis.The method of fractal dimension analysis is used to study the time series and spatial distribution of vegetation in Qinghai-Xizang Plateau, and with the help of MERRA climate data (mean temperature, total precipitation,Total solar radiation) and daily climatic data of meteorological stations in China (mean minimum relative humidity, annual maximum daily air temperature, average annual minimum daily temperature, annual total sunshine hours, annual mean relative humidity, annual average temperature,The main contents and conclusions of this study are as follows: 1) using linear regression method to analyze time series data.The study on vegetation types and regional vegetation changes shows that the overall vegetation greenery tends to increase; the vegetation types with higher green degree level have a higher sensitivity under the influence of climate change; in the regionalization research,In view of the existence of mutation points in time series data, a piecewise linear regression method is proposed to monitor vegetation change.The results show that this method can successfully monitor the mutation situation that can not be detected by the linear regression method. It can be used to analyze the dimensional change of three-dimensional space, spatial autocorrelation analysis, semi-variogram analysis and fractal dimension analysis.The results showed that the vegetation had positive spatial autocorrelation and showed obvious high and low value concentration areas.Structural factors play a dominant role in the total spatial variation, geomorphological characteristics and mountain trends lead to the spatial distribution of vegetation mainly along the southeast to northwest direction; regional climate conditions,The influence of landform and human activities on the spatial distribution of vegetation is increasing year by year. In view of the non-stationary phenomenon in the study data, the method of fitting the trend with low-order quadratic polynomials is proposed to achieve the purpose of removing the trend.The results show that the proposed method has successfully achieved the desired purpose. (5) the correlation between annual MERRA data and AVHRR data, as well as the daily data of growing season site and MODIS data is studied. The results show that: at different time scales and different spatial scales,The correlation between vegetation and climate variables is basically the same, and the main climate driving variables are different with different vegetation types.
【學(xué)位授予單位】：中國(guó)地質(zhì)大學(xué)(北京)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：Q948

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 吳炳方;苑全治;顏長(zhǎng)珍;王宗明;于信芳;李?lèi)?ài)農(nóng);馬榮華;黃進(jìn)良;陳勁松;常存;劉成林;張磊;李曉松;曾源;包安明;;21世紀(jì)前十年的中國(guó)土地覆蓋變化[J];第四紀(jì)研究;2014年04期

2 張曉克;魯旭陽(yáng);王小丹;;2000—2010年藏北申扎縣植被NDVI時(shí)空變化與氣候因子的關(guān)系[J];山地學(xué)報(bào);2014年04期

3 邊多;普布次仁;尼珍;劉奎軍;;基于MODIS-NDVI時(shí)序數(shù)據(jù)的西藏阿里地區(qū)草地覆蓋時(shí)空變化[J];中國(guó)草地學(xué)報(bào);2014年03期

4 王青霞;呂世華;鮑艷;馬迪;李瑞青;;青藏高原不同時(shí)間尺度植被變化特征及其與氣候因子的關(guān)系分析[J];高原氣象;2014年02期

5 呂洋;董國(guó)濤;楊勝天;周秋文;蔡明勇;;雅魯藏布江流域NDVI時(shí)空變化及其與降水和高程的關(guān)系[J];資源科學(xué);2014年03期

6 廖清飛;張?chǎng)?馬全;姚瑤;于東平;;青海省東部農(nóng)業(yè)區(qū)植被覆蓋時(shí)空演變遙感監(jiān)測(cè)與分析[J];生態(tài)學(xué)報(bào);2014年20期

7 劉櫟杉;延軍平;李雙雙;;2000-2009年青海省植被覆蓋時(shí)空變化特征[J];水土保持通報(bào);2014年01期

8 王濤;沈渭?jí)?歐陽(yáng)琰;林乃峰;;1982—2010年西藏草地生長(zhǎng)季NDVI時(shí)空變化特征[J];草地學(xué)報(bào);2014年01期

9 周偉;剛成誠(chéng);李建龍;章超斌;穆少杰;孫政國(guó);;1982-2010年中國(guó)草地覆蓋度的時(shí)空動(dòng)態(tài)及其對(duì)氣候變化的響應(yīng)[J];地理學(xué)報(bào);2014年01期

10 李亞楠;張麗;廖靜娟;王翠珍;;藏北中部地區(qū)草地退化遙感監(jiān)測(cè)[J];遙感技術(shù)與應(yīng)用;2013年06期

相關(guān)博士學(xué)位論文 前1條

1 馮益明;空間統(tǒng)計(jì)學(xué)及其在森林圖形與圖像處理中應(yīng)用的研究[D];中國(guó)林業(yè)科學(xué)研究院;2004年

相關(guān)碩士學(xué)位論文 前1條

1 莫偉華;基于EOS/MODIS衛(wèi)星數(shù)據(jù)的洪澇災(zāi)害遙感監(jiān)測(cè)應(yīng)用技術(shù)研究[D];南京信息工程大學(xué);2006年

，

本文編號(hào)：1732167