發(fā)布時(shí)間：2021-11-07 09:33

　　在過去的一個(gè)世紀(jì)中,非洲大陸許多地方發(fā)生了嚴(yán)重的自然災(zāi)害事件,特別是干旱產(chǎn)生的危害最大。干旱和土地退化是威脅非洲大陸糧食和畜牧可持續(xù)生產(chǎn)的主要因素,同時(shí)也嚴(yán)重影響當(dāng)?shù)厝嗣竦纳?特別是主要依靠雨水養(yǎng)育地區(qū)的農(nóng)業(yè)活動(dòng)為生的農(nóng)村居民。非洲北部的撒哈拉沙漠到南部以熱帶稀疏草原和森林雨區(qū)為中心的地區(qū),因缺水和夏季高溫導(dǎo)致土地退化和頻繁的干旱。該地區(qū)受到氣候變化和環(huán)境退化的影響,從而影響了該地區(qū)的農(nóng)業(yè)生產(chǎn)。我們發(fā)現(xiàn)非洲的薩赫勒地區(qū)周邊國家在過去幾十年中受影響最大,因此,我們的研究重點(diǎn)是薩赫勒地區(qū)國家,分析干旱對(duì)主要農(nóng)作物生產(chǎn)的影響,具體如下:首先,我們調(diào)查了非洲土地表面溫度(LST)的時(shí)空變化,以確定溫度對(duì)農(nóng)業(yè)生產(chǎn)的影響。盡管熱紅外遙感技術(shù)可以快速獲取表面溫度信息,但是它受到云和降雨的影響很大。為了獲得有關(guān)非洲LST時(shí)空變化的完整且連續(xù)的數(shù)據(jù)集,本研究通過利用地面站點(diǎn)數(shù)據(jù)和建立數(shù)據(jù)重構(gòu)模型對(duì)中分辨率成像光譜儀(MODIS)LST時(shí)間序列數(shù)據(jù)非洲大陸LST數(shù)據(jù)集(2003-2017)進(jìn)行了重構(gòu)。在此基礎(chǔ)上,對(duì)非洲大陸地表溫度進(jìn)行了時(shí)空變化分析,分析結(jié)果表明:2003-2017年LST的年平均變化很...

【文章來源】： 中國農(nóng)業(yè)科學(xué)院北京市

【文章頁數(shù)】：128 頁

【文章目錄】：
博士學(xué)位論文評(píng)閱人、答辯委員會(huì)簽名表
摘要
abstract
List of Abbreviations
CHAPTER1:INTRODUCTION
    1.1 FOOD SECURITY CHALLENGES
    1.2 IMPACT OF CLIMATE CHANGE
    1.3 CLIMATE CHANGE IMPACTS ON AFRICA
    1.4 AGRICULTURAL PRODUCTION
        1.4.1 Agricultural land degradation
        1.4.2 Drought and its impact on agricultural land
    1.5 THE ROLE OF REMOTE SENSING IN DROUGHT ASSESSMENTS
        1.5.1 Drought assessment indices
        1.5.2 Remote sensing-based drought assessment
        1.5.3 Advantages of remote sensing in agricultural drought monitoring
    1.6 RESEARCH PROBLEM
    1.7 RESEARCH QUESTIONS
    1.8 SIGNIFICANCE OF THE STUDY
    1.9 SCOPE OF THE STUDY
    1.10 STUDY AREA
    1.11 OBJECTIVES OF THE STUDY
    1.12 THESIS ORGANIZATION
CHAPTER2:ANALYSIS OF THE SPATIOTEMPORAL CHANGE IN LAND SURFACE TEMPERATURE FOR A LONG-TERM SEQUENCE IN AFRICA(2003-2017)
    2.1 INTRODUCTION
    2.2 MATERIALS AND METHODS
        2.2.1 MODIS data
        2.2.2 Ground observation data
        2.2.3 LST data reconstruction method
        2.2.4 LST pixel filtering
        2.2.5 LST data recovery
        2.2.6 Estimation of Invalid Pixel Values
        2.2.7 Validation
        2.2.8 Mean LST
        2.2.9 Trend analysis of change(slope)and the correlation coefficient(R)
    2.3.RESULTS
        2.3.1 Average LST change
        2.3.2 Daytime and nighttime change analysis
        2.3.3 Analysis of the diurnal temperature difference
        2.3.4 Seasonal change analysis
        2.3.5 Monthly average change analysis
        2.3.6 Validation
    2.4 DISCUSSION
    2.5 CONCLUSIONS
CHAPTER3:THE SPATIO-TEMPORAL CHANGES OF SOIL MOISTURE IN AFRICA(2003–2017)USING PASSIVE MICROWAVE SOIL MOISTURE DATA
    3.1 INTRODUCTION
    3.2 MATERIALS AND METHODS
        3.2.1 MODIS data sets
        3.2.2 Vegetation temperature condition index
        3.2.3 Soil moisture data sets
        3.2.4 Soil moisture time series method
        3.2.5 Downscaling method
        3.2.6 Ground observation data
        3.2.7 Validation
        3.2.8 Analysis of the SM time series trend
    3.3 RESULTS
        3.3.1 Verification of downscaled SM
        3.3.2 Spatiotemporal change analysis for different natural partitions in Africa
        3.3.3 Characteristics of the spatiotemporal variations of SM at annual scale
        3.3.4 The characteristic of Seasons trend
        3.3.5 SM time series trend at Month scale
        3.3.6 Correlation of SM with climate and non-climate factors
    3.4 DISCUSSION
    3.5 CONCLUSIONS
CHAPTER4:SPATIO-TEMPORAL DROUGHT ASSESSMENT OVER SAHELIAN COUNTRIES FROM1985 TO
    4.1 INTRODUCTION
    4.2 MATERIALS AND METHODS
        4.2.1 Remote sensing Datasets:
        4.2.2 Crop data
        4.2.3 Supplementary data
        4.2.4 Agricultural Drought Index
        4.2.5 Meteorological Drought Indicators
        4.2.6 Yield anomalies
        4.2.7 Assessment of drought vulnerability
        4.2.8 Pearson Correlation Coefficient(PCC)
    4.3 RESULTS AND DISCUSSION
        4.3.1 Meteorological drought assessment
        4.3.2 Remote sensing drought assessment and drought characteristic
        4.3.3 The relation between SPI,SPEI and VCI anomaly with yield anomaly
        4.3.4 Assessment of drought vulnerability
    4.4 CONCLUSIONS
CHAPTER5:CONCLUSIONS
    5.1 RECOMMENDATIONS
    5.2 FUTURE RESEARCH
REFERENCES
APPENDIX
ACKNOWLEDGEMENT
CURRICULUM VITAE


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