Knowledge Resource Center for Ecological Environment in Arid Area
| 青藏高原数字地貌特征分析与过程模拟 | |
| 其他题名 | Digital Geomorphologic Analysis and Process Simulation in the Qinghai-Tibet Plateau |
| 赵尚民 | |
| 出版年 | 2012 |
| 学位类型 | 博士 |
| 导师 | 周成虎 ; 陈曦 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 地处中国西南部的青藏高原，海拔高峻，气候严寒，自然环境十分恶劣，其地貌特征一直是地学研究的热点和难点之一。遥感技术的快速发展和大量高分辨率遥感影像的不断出现，GTOPO30、SRTM3 DEM、ASTER GDEM等一系列覆盖全球陆地的数字高程模型（DEM）数据的发布与免费下载，中国1:100万数字地貌数据遥感解译的完成，青藏高原各种数据资料的日益丰富和功能强大的地理信息系统（GIS）分析技术，为全面、系统、定量地研究青藏高原的数字地貌特征及其分布动态过程等提供了完备的基础和条件。\n本 文首先对青藏高原进行了地貌区划，在地貌区划成果的基础上，分析了青藏高原及其不同地貌区地貌类型的空间分布特征，基本成因与地形、气候和地质等要素的空 间分布关系，基本成因、地形和成因地形综合三类地貌类型的地貌格局指数，并基于地貌数据，利用地形信息图谱方法进行了图形化分区研究；然后基于青藏高原多 源数据（包括地貌、DEM、气候和地质等），通过数字分析方法，在对DEM数据精度进行评价和其应用进行分析的基础上，利用线状地形剖面图和带状地形剖面图对公格尔山的地形抬升特征进行了分析，并利用改进的地形剖面方法研究了青藏高原西北缘的地貌形态特征；最后以青藏高原的典型地貌类型——冻土地貌为例，利用模拟模型对青藏高原及祁连山过去50年（1960-2009）每个年代高海拔冻土的空间分布进行了数值模拟，并分析了其演变过程和变化趋势。研究结果表明：\n（1）参考前人地貌区划成果并基于地貌数据，在遥感影像图和地貌晕渲图上通过地形和地貌特征的空间分异将青藏高原划分为不同的7个地貌区和24个地貌亚区，7个地貌区分别为：喜马拉雅山、冈底斯山与念青唐古拉山、横断山、昆仑山与喀喇昆仑山、祁连山与阿尔金山、羌塘高原、柴达木盆地—海 南平原与山地；分析地貌营力在青藏高原不同地貌区的空间分布特征，可得：流水地貌面积最大，主要分布在昆仑山与喀喇昆仑山、横断山和羌塘高原地貌区；其次 为冰缘地貌，主要分布于羌塘高原和昆仑山与喀喇昆仑山地貌区；第三为冰川地貌，主要分布在冈底斯山与念青唐古拉山、横断山、昆仑山与喀喇昆仑山和喜马拉雅 山地貌区；湖成地貌在青藏高原广泛散布，干燥和风成地貌主要分布在柴达木盆地。对地貌类型基本成因与基本形态、气候特征和地质特征的空间分布关系进行分 析，认为：基本成因分布与基本形态有密切关系；冰缘地貌分布区的气候特征可能比冰川地貌分布区更加寒冷、干旱。关于地貌格局指数在青藏高原及其各个地貌区 的分布，对于多样性，基本成因 < 基本形态 < 成因形态类型；对于均匀度，形态和成因形态均匀度相差不大，它们均大于成因类型的均匀度；聚集度数值在80到95之间，整体水平较高；蔓延度数值整体上位于40到65之间，程度相对较低；连通性数值则均位于90以上，连通性很好。\n（2）利用地学信息图谱分析方法对青藏高原地貌类型的空间分布进行图形化分析：对于海拔高度，从东北到西南分为4个 带状区域：即祁连山脉区域，近似弓形，以高海拔和中海拔为主；柴达木盆地和海南平原与山地区域，近似梯形，以中海拔为主；东昆仑山和横断山脉区域，近似梯 形，以高海拔和极高海拔为主；青藏高原西部和南部区域，像一个不规则菱形，以极高海拔为主。对于起伏度，按照起伏度从小到大小划分为4个等级，第1等级位于柴达木盆地，近似菱形；第2等级位于羌塘高原及其东北部，近似椭圆形；第3等级位于第1和第2等级外围，它们一起构成近似“双黄蛋”形；第4等级位于青藏高原西北部和东南部，即青藏高原“鸵鸟”形状的头部和尾端。基本成因按照分布特征也分为4个区域，区域1位于柴达木盆地，近似菱形，以风成和干燥地貌为主；区域2位于区域1周围，以阿尔金山、祁连山和东昆仑山为主，和区域1组成弓形，以流水地貌为主；区域3位于羌塘高原及其东部，近似扇形，以冰缘地貌为主；区域4分布在青藏高原西部和南部，近似“μ”形，以冰川和流水地貌为主。\n（3）和SRTM3 DEM相比，ASTER GDEM拥有更高的水平分辨率，因此能表达更多的地表形态细节信息；相对来说，SRTM3 DEM的垂直精度整体上要稍好于ASTER GDEM。由于ASTER GDEM数据较高的水平分辨率带来的大数据量和较低的处理速度，对于青藏高原这种大区域来说，利用SRTM3 DEM数据进行地貌形态和地势特征进行分析更加合理。利用SRTM3 DEM数据自动提取的地貌形态特征可以为遥感自动解译提供基础和依据；基于SRTM3 DEM数据和Global Mapper软件自动生成的地貌晕渲图则可以生动地反映区域地势特征。\n（4）在公格尔山东北侧，从塔里木盆地边缘到公格尔山顶，地形抬升共可分为3段：分别是从海拔高度2000m左右上升到约4500m，从4500m上升到将近6000m，从将近6000m上升到约7500m； 其中第三段抬升速度最快，第一段次之，第二段由于水平距离最长，抬升速度最慢。通过对垂直于山体走向且具有一定间距的地形剖面线进行数理统计分析，获得了 典型的地形剖面图，改进的地形剖面图不仅降低了线状地形剖面图选择剖面线时的主观性，又解决了带状地形剖面图统计数据没有对应地面位置的缺点，同时可以通 过调整剖面线间距来改变典型地形剖面图的精度。在青藏高原西北缘，从塔里木盆地边缘到山顶地形抬升速率与山体组成物质所经历的地质年代的数量之间呈现负相 关关系。对于西昆仑山北缘整体来说，地形梯度在两边较大，中间较小；对于不同的地貌带，流水地貌带地形梯度最大，其次为冰川地貌带，然后是冰缘地貌带，干 燥地貌带处于山麓地带，地形梯度最小。\n（5）通过基于海拔高度模型的响应模型并利用SRTM3 DEM数据、多年平均气温数据和气温垂直递减率数据，对青藏高原过去50年每个年代的冻土分布进行了模拟。在过去50年，青藏高原冻土模拟面积在1960s、1970s、1980s、1990s和2000s分别为160.110×10P4P kmP2P、148.549×10P4P kmP2P、145.376×10P4P kmP2P、136.166×10P4P kmP2P 和 126.656×10P4P kmP2P。因此，青藏高原冻土在过去50年一直呈减少趋势，且减少的速度整体上越来越快。\n（6）基于高质量冻土分布图，利用地形要素数据（包括海拔高度、坡度、坡向、经度和纬度）和气候要素数据（多年平均气温数据、多年平均降水数据和多年平均日照时数数据）建立了逻辑回归模型。然后利用逻辑回归模型、地形数据和不同阶段的气候要素数据，对祁连山高山冻土在过去50年每个年代的空间分布进行了模拟。模拟结果可知：在过去50年中，祁连山从1960s到2000s每个年代高山冻土分布面积分别为：10.749×10P4P kmP2P、9.847×10P4P kmP2P、10.044×10P4P kmP2P、8.533×10P4P kmP2P和8.686×10P4P kmP2P。因此，祁连山高山冻土整体呈下降趋势；但在下降过程中，还有一些微小的波动。\n本研究不仅利用多种方法分析了青藏高原地貌类型的空间分布格局，对青藏高原地貌成因、地貌演化、地貌利用、生态修复和环境保护等多个领域的研究有重要意义，也为青藏高原地貌演变趋势预测和人类活动对地貌演化的影响等研究奠定基础；而且加深了对全球DEM数据质量的认识，改进了地形剖面图的分析方法，分析了青藏高原西北缘的地貌形态特征，对认识青藏高原地貌隆升过程及印度—欧亚大陆碰撞的远程效应具有一定意义；多年冻土空间分布的模拟则为研究冻土演变趋势及未来分布状况的预测奠定了基础，对青藏高原乃至全球气候变化，荒漠化，基础设施建设，植被变化，生物化学过程等都具有重要的影响。 |
| 英文摘要 | With high altitude, severe climate and rigorous natural and environmental conditions, Qinghai-Tibet Plateau (QTP), located in the southwestern part of China, is a hot and difficult area in geographic research. The rapid development of remote sensing technology and the adventure of abundant images with high resolution, the release and freely download of global digital elevation model (DEM) data such as GTOPO30, SRTM3 DEM and ASTER GDEM, the achievement of remote sensing interpretation of geomorphologic data in China at one million-scale, the richness of all kinds of data in the QTP and the strong geographic information system (GIS) technology provide a complete basis and conditions for comprehensive, systematic and qualitative research for the digital geomorphologic characteristics and its dynamic spatial distribution of the QTP.\nThis paper firstly did the geomorphologic regionalization on the QTP, based on the geomorphologic regionalization results of the QTP, the analysis to the spatial distribution characteristics of geomorphologic types data in different geomorphologic regions, the analysis of spatial distribution relation among basic genesis, topographic, climatic and geologic data, the landscape index analysis to basic genesis, topographical and genesis-topographical data, the geo-info tupu analysis to the geomorphologic data, the spatial distribution pattern of geomorphologic data in the QTP were conducted; using geomorphologic data, DEM data, climatic data, geomorphologic regionalization data, geological data and so on in the QTP, this research then analyzed the geomorphologic landform characteristics of the western edge of the QTP based on the accuracy estimation and application analysis of the DEM data and including the analysis for topographic uplifting characteristic of Mt. Kongur; finally, taking the typical geomorphologic type — permafrost as an example, the decadal spatial distribution of the permafrost on the QTP and Qilian Mountain are simulated using different models from 1960 to 2009, and the spatial distribution change during different decades are analyzed. Though this research, the following conclusions can be obtained.\n(1) Referencing previous geomorphologic regionalization achievements and based on geomorphologic data, the QTP is divided into seven geomorphologic regions and twenty four geomorphologic sub-regions in remote sensing images and geomorphologic shading maps through the spatial differentiation of landform and geomorphologic characteristics. The seven geomorphologic regions are Himalaya Mountains, Gandisi Mountains and Nynqientangulha Mountain, Hengduan Mountains, Kunlun Mountains and Karokaram Mountains, Qilian Mountains and Altun Mountains, Qiangtang Plateau, Qaidam Basin—Hainan Plain and Hills respectively. The analysis to the basic genesis types of geomorphologic data in the seven different geomorphologic regions shows: fluvial geomorphology has the largest area, which mainly distributes in the geomorphologic regions of Kunlun Mountain and Karokaram Mountain, Hengduan Mountain and Qiangtang Plateau; the next is periglacial geomorphology, which mainly distributes in Qiangtang Plateau, Kunlun Mountain and Karokaram Mountains; glacial geomorphology is the third one, which distributes in Gangdisi Mountain and Nynqientangulha Mountain, Hengduan Mountain, Kunlun Mountain and Karokaram Mountain, Himalayan Mountain; lacustrine geomorphology sparsely distributed in the QTP; arid and aeolian geomorphology mainly distributes in the Qaidam Basin. The analysis to the spatial distribution relationship among basic genesis and landform, climate types and geological types show: basic genesis and basic landform has close relationship in distribution; the climate in periglacial distribution area may be colder and drier than it in glacial areas. About the landscape pattern indexes in the whole QTP and every geomorphologic regions, as to diversity, basic genesis < basic landform < genesis-landform; to evenness, the evenness of the basic landform is similar to that of genesis-landform, which are both larger than that of basic genesis type; to aggregation, the number is between 80 and 95, so the general level is high; to contagion, generally between 40 and 65, so the level is relatively low; to cohesion, all above than 90, so the cohesion is very good. \n(2) The spatial distribution of geomorphologic types is analyzed using geo-info tupu method: to altitude, the QTP is divided into four band regions from northeast to southwest; Qilian Mountain likes bow shape, which mainly distributes high and middle altitude; Qaidam Basin, Hainan Plain and Hills like trapezium shape, which mainly distribute middle altitude; East Kunlun Mountain and Hengduan Mountain also like trapezium, which mainly distribute high and extremely-high altitude; southwestern part of the QTP likes irregular diamond, which mainly distributes extremely-high altitude. For the relief, the QTP can be classified four grades from small to big; the first grade locates in Qaidam Basin, like diamond; the second grade locates in Qiangtang Plateau and its northeastern part, like ellipse; the third grade locates in the skirt regions of the first and second grade regions, which forms an approximately “double-yolked egg” combined with the last two regions; the fourth grade locates in the northwestern and southeastern part of the QTP, that is, head and back end of the “ostrich-shaped” QTP. Basic genesis is also divided into four regions according to its distribution; the first region locates in Qaidam Basin, like diamond, which mainly distributes aeoline and arid geomorphology; the second region around the first region, mainly includes Altun Mountain, Qilian Mountain and East Kunlun Mountain, which forms bow combined with the first region, and mainly distributes fluvial geomorphology; the third region locates in Qiangtang Plateau and its eastern part, which likes a fan, and mainly distributes periglacial geomorphology; the fourth region mainly locates in the southwestern part of the QTP, approximately “μ” shape, mainly distributes glacial and fluvial geomorphology.\n(3) ASTER GDEM has higher spatial accuracy than SRTM3 DEM, so it can represent more ground detail information; generally speaking, the vertical accuracy of SRTM3 DEM is better than that of ASTER GDEM. Since the higher spatial resolution of ASTER GDEM can cause larger data volume and lower process velocity, so SRTM3 DEM is more proper for conducting geomorphologic landform and relief characteristics analysis in the QTP. The automatic extraction from DEM data can provide important reference for remote sensing interpretation of geomorphologic data; the automatic production of relief shading map using SRTM3 DEM and Global Mapper software can vividly represent the regional relief characteristics.\n(4) In the northeastern side of Mt. Kongur, the topographic uplifting part from the edge of Tarim Basin to the summit of Mt. Kongur can be divided into 3 sections: from the altitude about 2000m to the altitude 4500m, from 4500m to nearly 6000m, and from nearly 6000m to about 7500m; among them, the third section has the highest uplifting velocity, then the first section, the second section has the lowest velocity because of the largest horizontal distance. Through statistical analysis to the topographic profile lines at fixed distance perpendicular to the trend of the mountains, the typical topographic profile can be achieved; the improved topographic profile method can not only decrease the subjectivity of traditional linear topographic profile in profile line selection, but also resolve the defect of swath topographic profile in losing ground location, additionally, the accuracy of the typical topographic profile can be adjusted by changing the fixed distance. In the northwestern edge of the QTP, the topographic uplifting velocity and the geologic times of the mountain body from the edge of Tarim Basin to the summit presents negative correlation. To the whole north side of the West Kunlun Mountains, the topographic gradient is higher in the two edges, but lower in the middle part; to different geomorphologic belts, fluvial geomorphologic belt has the highest topographic gradient, then the glacial geomorphologic belt, the next is the periglacial geomorphologic belt, the arid geomorphologic belt has the lowest topographic gradient as it is in the piedmont.\n(5) Based on the response model developed form altitude model and using SRTM3 DEM data, mean annual average temperature data and vertical lapse rate of temperature data, the permafrost distribution in the QTP are simulated for the past 50 years. The simulated areas of the permafrost on the QTP in 1960s, 1970s, 1980s, 1990s and 2000s were 160.110×10P4P kmP2P, 148.549×10P4P kmP2P, 145.376×10P4P kmP2P, 136.166×10P4P kmP2P and 126.656×10P4 PkmP2 respectively. So the permafrost distribution greatly decreased and the decreased velocity generally accelerated over past 50 years. \n(6) Logistic regression model (LM) is constructed based on bench-mark distribution map of alpine permafrost and the topographic (including altitude, slope, aspect, longitude and latitude) and meteorological (including mean annual average temperature, mean annual precipitation and mean annual sunshine hours) factors. Based on LM, the decadal alpine permafrost distributions in the Qilian Mountains are simulated over past 50 years. The simulated areas of alpine permafrost in 1960s, 1970s, 1980s, 1990s and 2000s are 10.749×10P4P kmP2P, 9.847×10P4P kmP2P, 10.044×10P4P kmP2P, 8.533×10P4P kmP2P and 8.686×10P4P kmP2P respectively. Hence, the distribution of alpine permafrost presents an overall degraded tendency with some slight fluctuations.\nThis research not only analyzes the spatial distribution pattern of geomorphologic types in the QTP using multiple methods, which has important meaning for many research fields, such as geomorphologic genesis, geomorphologic evolution, geomorphologic utilization, ecologic restore and environmental protection, and builds base for the researches such as the evolving trend prediction of the geomorphology in the QTP and the impact of human activity to geomorphologic evolution; but also pays attention to the quality of global DEM data, improves the analysis method of topographic profile, analyzes the geomorphologic landform characteristics of the northwestern edge of the QTP, which has significance for understanding the uplifting process of the QTP and the remote effect of the collision between India-Eurasia Continents; the spatial distribution simulation of the permafrost builds base for the research of evolving trend and future spatial distribution prediction of the permafrost, so as to has important impact for the QTP and global climate change, desertification, infrastructure construction, vegetation change and biochemical process. |
| 中文关键词 | 青藏高原 ; 数字地貌 ; 空间格局 ; 地形分析 ; 冻土分布模拟 |
| 英文关键词 | Qinghai-Tibet Plateau digital geomorphology spatial pattern topographic analysis permafrost distribution simulation |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 地图学与地理信息系统 |
| 来源机构 | 中国科学院新疆生态与地理研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287042 |
| 推荐引用方式 GB/T 7714 | 赵尚民. 青藏高原数字地貌特征分析与过程模拟[D]. 中国科学院大学,2012. |
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