中国土地覆盖变化与环境影响遥感研究
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摘要
土地覆盖是联系生态系统和气候系统的重要环节,人类社会正是通过对土地的利用,改变土地覆盖的生物地球化学特征,进一步影响生态系统的结构和功能,影响到气候系统。土地覆盖是全球变化研究中的关键内容。
     在综合分析国内外土地覆盖、土地利用和全球变化研究现状和发展趋势后,从定量遥感的理论出发,基于前人的研究成果,提出一套土地覆盖遥感研究体系。首先,土地覆盖的内涵应包括土地的生物物理特征,提出定量的遥感土地覆盖分类体系;依据定量遥感理论计算出反照率、陆地表面温度、植被指数和净第一性生产力四个重要土地覆盖特征参数;提出基于生态系统观点的遥感土地覆盖分类研究;分析了中国土地覆盖特征参数的季相变化规律,对20年中国土地覆盖变化进行了研究;在此基础上,对中国沙尘进行了沙尘源地、沙尘输送路径、沙尘携沙量和风蚀对中国土壤碳库的影响研究;并对中国土地覆盖和沙尘的发生进行了相关分析。
     本文得出的主要结论如下:
     1.定量的土地覆盖分类体系的建立
     在分析了国内的植被分类系统、土地资源分类系统和国外的FAO、美国国家土地覆盖数据NLCD系统、IGBP、USGS、Holdridge植被气候分类的基础上,指出土地覆盖的生物物理参数是土地覆盖的合理内容,在土地覆盖分类体系中应使用定量化的指标描述土地覆盖类型。基于定量遥感获取的土地覆盖生物物理特征参数,主要是反照率、净初级生产力、植被指数和陆面温度四个指标,提出一种定量化的遥感分类系统,每一种土地覆盖类型或植被类型对应一定的生物物理参数指标。
     2.中国陆面温度研究
     近年来国内外利用遥感方法在陆面温度精确反演中开展了大量的研究工作,采用了一个在大区域上适用的由NOAA-AVHRR数据反演陆面温度的方法,反演中国晴空条件下各月和全年平均陆面温度,分析了中国陆面温度的分异规律,并与气温的分异规律作了对比,同时对中国土地利用/土地覆盖变化研究(LUCC)样带上的陆面温度变化进行了分析。这项工作从晴空条件重新认识了地面温度场的空间分异,对于研究中国陆地土壤蒸发、植物光合作用、土地覆盖的分布具有重要的指示意义。
     3.中国土地覆盖特征库的建立
     通过对已有反演算法的分析比较,使用在大尺度上适用的遥感反演方法,
    
    计算出中国陆地表面温度、反照率、植被指数和净初级生产力的一年或多年月
    平均数据,建立起中国土地覆盖特征库。
     4.基于生态系统观点的遥感土地覆盖分类研究
     生态系统作为一个整体,存在物质能量的转化和利用,而遥感直接探测的
    是生态系统表层的生物和非生物的能量特征信息。利用NOAA-MiEtIL数据计
    算出能反映生态系统能量特征的吸收率和陆地表面温度参数,以及反映生态系
    统物质特征的植被指数和净第一性生产力参数。基于这四个参数及其反映的明
    显生态系统季相变化特征,提出一种可用于生态系统模型研究的从物质能量角
    度出发的遥感土地覆盖分类方法,最后以中国为例进行了初步实验。
     5.近20年中国土地覆盖变化研究
     植被指数NDVI的年际变化可以指示出土地覆盖的变化特征,在近20年中,
    NDW指示出中国大部分地区植被呈现增加的趋势,少部分地区呈现减少的趋
    势。进一步,在 80年代(从 1982到 1991年),中国大部分地区植被呈现增加
    的趋势,面积达 95%,但在 90年代(从 1991到 2000年),中国西部和北部地
    区植被呈现减少的趋势,面积为62%。近20年是处在全球变暖的背景下,90
    年代中国中西部的植被状况急剧恶化,是与温度增高,降雨减少的气候条件存
    在密切关系。
     6.东亚沙尘源地、沙尘输送路径的遥感研究
     东亚沙尘灾害严重影响东亚各国的生态环境,在源地大量侵蚀表层土壤,
    在输送过程中严重污染大气环境质量。此外,作为气溶胶,对区域辐射平衡和
    大气系统产生重大影响。利用ScawiFS遥感数据分析了东亚沙尘灾害的源地、
    沙尘输送路径,结果显示:东亚沙尘的三个主要源地是蒙古的戈壁、内蒙古中
    西部的沙漠戈壁和塔克拉玛于沙漠。沙尘输送路径有北路、中路和南路三条,
    北路主要影响中国的东北地区,中路主要影响中国的华北地区,南路主要影响
    中国的华中、华东地区。
     7.风蚀对中国土壤碳库的影响研究
     在中国西北干旱、半于旱地区,陆地生态系统的净初级生产力WP 很低,
    转换成土壤有机碳的量也很低,同时,由于降雨少,风蚀成为该区水土流失的
    主要原因,引起表层士壤有机碳的大量减少。西北地区士壤有机碳的平衡是陆
    地生态系统稳定生产力的关键。
     首先利用光能利用率模型计算出西北地区的NPP。同时根据第:次全国上
    壤普查数据计算出表层土壤有机碳库和表层土壤有机质含量。利用第二次全国
    士壤侵蚀遥感调查中的风力侵蚀强度图,估算出土壤风力侵蚀量和土壤有机碳
    流失分布图。进一步,通过分析土壤有机碳库、NPP和由于风蚀所损失的土壤
    有机碳,认为西北地区的士壤有机碳总体上处于减少状态。风蚀是中国中西部
    地区土壤碳库减少的一个主要原因。
Land cover is the important interface between terrestrial ecosystem and climate system. Actually, by utilizing the land resources, human society affects the biogeochemical feature of land cover, further, affects the structure and function of terrestrial ecosystem and so much as affects the climate system. In all, land cover is the key field of global change research.
    Based on the analysis of previous outcome and trend of land cover research, from the view of quantitative theory of remote sensing this thesis brings forward a research system of remote sensing on land cover. First, the biophysical features of land cover are rational contents of land cover. Second, the four key parameters of land cover (albedo, land surface temperature, vegetation index and net primary production) are retrieved from satellite data. Further, Land cover classification from the view of ecosystem is brought forward. This thesis not only analyzes the seasonal variation of land cover, but also analyzes land cover change during the past 20 years In addition, tracks and source areas of Asian dust, dust loading and balance study of soil organic matter are under study. Based on the above researches, this thesis makes correlative analysis of land cover change and dust trend in China. This thesis includes the following contents,
    1. Construction of quantitative system of land cover classification
    Based on the analysis of China vegetation classification system, China land resource classification system, America national land cover data (NLCD) system,IGBP,USGS and Holdridge vegetation-climate classification system, this
    
    
    
    thesis indicates that biophysical features of land cover are rational contents of land cover and quantitative parameters should be used to describe the land cover type. On the basis of retrieve of biophysical parameters (albedo, land surface temperature, vegetation index and net primary production) from remote sensing data, this thesis brings forward a classification system, in which every land cover type is corresponding to specific value of biophysical parameters.
    2. Study of variation of land surface temperature in China
    By using a suitable split window algorithm on large scale, the authors retrieved the yearly and monthly land surface temperature(LST) from the thermal bands of NOAA-AVHRR data set over China. The result indicates that the variation of LST has some specific features and is different from that of air temperature.
    As to LST, the hottest part is in Northwest drought region, the higher LST part is in Southeast region, and the low LST parts are in Tibet plateau and Northeast region. Moreover, there is no 0癈 isotherm of annual LST over China. Further, the 0癈 isotherm of LST in January lies higher in latitude than that of air temperature. And Eastern Tibet and Western Tibet have different seasonal features of LST.
    3. Building of database of land cover features in China
    Based on the analysis and compare of current retrieval algorithms, this thesis utilizes a suitable algorithm on large scale to calculate albedo, land surface temperature, vegetation index and net primary production with a temporal resolution of month, and build the database of land cover features in China.
    4. Land cover classification from the view of ecosystem
    Ecosystem as a whole is composed of biology and its environment (such as soil and atmosphere), and there exist transform and utilization of substance and energy in an ecosystem. However, remote sensing directly observes the radiation energy of upper layer of ecosystem, the radiation energy includes a lot of information about land surface and ecosystem, and these uncovered feature about ecosystem can be used to make land cover classification.
    Absorptivity( a ),land surface temperature(Ts), vegetation index(NDVI) and net primary production(NPP) can be retrieved from remote sensing(such as AVHRR data), a and Ts represent the energy feature of ecosystem, and NDVI and NPP represent the substance feature of ecosystem. These four bio-parameters have close relationship with speci
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