基于遥感的青藏高原热融湖塘时空演化监测与趋势分析
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摘要
在全球气候转暖及人类活动频繁增加的背景下，青藏高原多年冻土处于强烈的退化过程，而热融湖塘作为热融灾害中最为典型的灾害之一，也是多年冻土退化的重要标志，应该说从环境和工程影响方面，热融湖塘（热喀斯特湖）是热融灾害中最为典型、对冻土环境和工程影响最为直接的一种热融灾害。本论文针对青藏高原热融湖塘，基于对不同时期航空、航天遥感资料的分析，结合区域典型热融湖塘的监测与调查，从灾害学与地理学的角度，以发育于青藏铁路、青藏公路秀水河至风火山段沿线的典型热融灾害—热融湖塘为研究对象，通过分析热融湖塘敏感性发育的条件和因素，基于GIS平台研究了区域热融湖塘的时空演化特征，建立了敏感性评价方法，实现了区域热融湖塘敏感性评价，通过多年代航空、航天影像研究了典型湖塘——BLH-A热融湖塘的发育过程及其发育趋势，分析了青藏公路、青藏铁路沿线热融湖塘41年以来的时空演化规律，为青藏高原环境与工程协调和持续发展、规划及对策实施提供了科学依据。主要研究成果如下：
（1）首先针对研究区范围内2006年分辨率为0.6m的QuickBird卫星影像数据和2010年分辨率为2.5m的SPOT-5卫星影像数据的处理方法进行了研究，重点对热融湖塘优势性的融合、纠正、镶嵌处理方法进行了选择与比较，探索出判读热融湖塘的最优技术方法，并建立了热融湖塘遥感解译标志，对遥感数据中的热融湖塘进行了解译，获取了热融湖塘的大量信息数据。
（2）选取包括冻土类型、地温、植被类型、土质类型、水文地质条件以及坡度在内的六个因子，分析了热融湖塘与各因子的关系，采用数理统计法获得了各评价因子的敏感系数值。根据敏感因子与热融湖塘形成条件的对比分析，获得了研究区域59种不同地质环境综合敏感系数指标，为热融湖塘的空间演化分析提供了科学依据。
（3）针对位于北麓河盆地的一代表性热融湖塘（BLH-A热融湖塘），通过遥感动态监测及实地监测，研究了BLH-A热融湖塘的时间演化趋势。1969年、1999年、2006年、2008年、2010年的遥感动态监测显示，BLH-A热融湖塘的面积1969年至1999年以0.35%的增长率扩张，1999年至2006年增长率为0.42%，2006年至2008年增长率为0.44%，2008年至2010年增长率为0.49%，在全球气候变暖、年平均气温不断上升的条件下，BLH-A热融湖塘的面积随时间推移增长越来越快。BLH-A热融湖塘向旧青藏公路方向扩张的速率在1969年至1999年为0.42m/a，在1999年之后，湖塘扩张的速率有所增加，大约是0.6m/a，2008年后湖塘扩张的速率达0.65m/a，经推算41年后，BLH-A热融湖塘将向新建青藏铁路方向扩张51.8m，会对青藏铁路路基造成危害。实地监测结果表明，BLH-A热融湖塘湖岸不断坍塌后退，从2007年8月～2010年10月，湖岸最大后退了3.2m，最小后退了0.6m，实地监测的结果验证了遥感数据的可靠性。
（4）利用1969年至2010年41年间的资料，分析了青藏公路和青藏铁路修建前后热融湖塘随时间的演化规律。结果表明，41年来热融湖塘的面积年增长量和年增长率均与综合地质环境因素敏感系数呈正比，且前30年增长相对缓慢，而在青藏铁路修建后热融湖塘的个数和面积剧烈增加。根据热融湖塘历史时空演化规律，推测50年后，该区域热融湖塘的面积较2010年增大了1倍，约占研究区总面积的4.5%。100年后热融湖塘的面积接近2010年湖塘面积的5倍，约占研究区总面积的10.0%。
In the context of the development of the global warming and frequent human activities,permafrost degradation in the Qinghai-Tibet Plateau (QTP) is serious. Thermokarst lake, as one ofthe most typical thermal hazards, is also an important symbol of permafrost degradation. From theview of the aspects of environment and engineering, the effects of thermokarst lake to them aretypical and direct. In order to study thermokarst lakes in QTP in this thesis, a typical zone fromXiushuihe to Fenghuoshan along the Qinghai-Tibet Railway (QTR) and the Qinghai-TibetHighway (QTH) was selected to analyze the distribution and developing characteristics of thethermokarst lakes. From the perspective of disaster and geography, the works were based on theanalysis of aviation and spaceflight remote sensing data in different periods and monitoring thetypical zones. The conditions and factors influencing the thermokarst lake sensitivity, space-timeevolution characteristics of the thermokarst lakes were analyzed on the basis of GIS platform.Then the evaluation method of sensitivity was established and sensitivity evaluation of thethermokarst lakes was realized. In order to understand the space-time evolution laws of thethermokarst lakes more than40years, the development process of a typical lake, named BLH–A,and its development trend were studied through aviation images. The works might providereference for coordination and sustainable development planning and strategy implementationbetween the environment and local project in QTP. The main conclusions are as follows.
(1) The processing methods on QuickBird satellite image data with a resolution of0.6m in2006and the SPOT-5satellite image data with a resolution of2.5m in2010in the study areawere discussed. Focusing on fusion, correct and mosaic processing methods on thermokarst lakedominance, a better interpretation method of thermokarst lake was explored. According to theinterpretation marks of the thermokarst lakes, remote sensing data was interpreted, andinformation of thermokarst lakes was obtained.
(2) Six factors, including the type of permafrost, the ground temperature, vegetation type, soiltype, hydrogeological conditions and slope angle were selected to statistically analyze thedistribution of the thermokarst lake. After the analysis and evaluation of statistical results, usingthe mathematical statistics for the factors, the sensitive coefficient of each factor was calculatedand the results were evaluated. Finally, the sensitivity value of each factor was obtained through the average method. And the forming conditions of the thermokarst lakes were compared based onthe analysis of the sensitive factors. Then59comprehensive sensitivity coefficient indices indifferent geological environment in the study area were obtained, which provided the basis for thespace evolution analysis of the thermokarst lakes.
(3) In order to investigate the developing trend of the thermokarst lakes, a lake located in theBeiluhe Basin (named BLH-A) was dynamically monitored through remote sensing and fieldinvestigation. According to remote sensing images in1969,1999,2006,2008and2010, the areaof the BLH–A was increasing with the growth of0.35%from1969to1999, and then the rateincreased with time. Under the background of the global climate warming, the area was growingfaster and faster over time: the growth rate was0.42%from1999to2006,0.44%from2006to2008, and0.49%from2008to2010. And the expansion trend of the lake was also increasing.From1969to1999the dilation rate of the lake was0.42m/a. After1999the rate was around0.6m/a, and was up to0.65m/a after2008. Through calculation, the BLH–A expanded51.8mtoward QTR in41years, which would do damage to the roadbed of QTR. This result wasconsistent with field monitoring data, which showed that the shore of the lake collapsed and fellback constantly. From August2007to October2010, all the monitoring points along the lakeshoredrew back more than0.6m, with the maximum of3.2m.
(4) In order to analyze the evolvement law of Thermokarst Lake with the change of the timein41years from1969to2010, or before and after the Qinghai-Tibet highway and theQinghai-Tibet railway construction, combining with the geological environment sensitivity factorsand images of remote sensing dynamic monitoring project to Thermokarst Lake. The results showthat, during the41years, with increasing the PDmn, the total area of the thermokarst lakes and theannual growth rate increase accordingly. In addition, in the first30years, they grow slow;however, the number and the total area of the thermokarst lakes grow faster after the finishing ofthe Qinghai-Tibet railway construction. Moreover, the results forecast that the area of the totalthermokarst lakes will become doubling in the near50years, which is4.5%of the study area.After100years, the area will almost achieve five fold than that in2010, which could be10.0%ofthe study area.
（1）首先针对研究区范围内2006年分辨率为0.6m的QuickBird卫星影像数据和2010年分辨率为2.5m的SPOT-5卫星影像数据的处理方法进行了研究，重点对热融湖塘优势性的融合、纠正、镶嵌处理方法进行了选择与比较，探索出判读热融湖塘的最优技术方法，并建立了热融湖塘遥感解译标志，对遥感数据中的热融湖塘进行了解译，获取了热融湖塘的大量信息数据。
（2）选取包括冻土类型、地温、植被类型、土质类型、水文地质条件以及坡度在内的六个因子，分析了热融湖塘与各因子的关系，采用数理统计法获得了各评价因子的敏感系数值。根据敏感因子与热融湖塘形成条件的对比分析，获得了研究区域59种不同地质环境综合敏感系数指标，为热融湖塘的空间演化分析提供了科学依据。
（3）针对位于北麓河盆地的一代表性热融湖塘（BLH-A热融湖塘），通过遥感动态监测及实地监测，研究了BLH-A热融湖塘的时间演化趋势。1969年、1999年、2006年、2008年、2010年的遥感动态监测显示，BLH-A热融湖塘的面积1969年至1999年以0.35%的增长率扩张，1999年至2006年增长率为0.42%，2006年至2008年增长率为0.44%，2008年至2010年增长率为0.49%，在全球气候变暖、年平均气温不断上升的条件下，BLH-A热融湖塘的面积随时间推移增长越来越快。BLH-A热融湖塘向旧青藏公路方向扩张的速率在1969年至1999年为0.42m/a，在1999年之后，湖塘扩张的速率有所增加，大约是0.6m/a，2008年后湖塘扩张的速率达0.65m/a，经推算41年后，BLH-A热融湖塘将向新建青藏铁路方向扩张51.8m，会对青藏铁路路基造成危害。实地监测结果表明，BLH-A热融湖塘湖岸不断坍塌后退，从2007年8月～2010年10月，湖岸最大后退了3.2m，最小后退了0.6m，实地监测的结果验证了遥感数据的可靠性。
（4）利用1969年至2010年41年间的资料，分析了青藏公路和青藏铁路修建前后热融湖塘随时间的演化规律。结果表明，41年来热融湖塘的面积年增长量和年增长率均与综合地质环境因素敏感系数呈正比，且前30年增长相对缓慢，而在青藏铁路修建后热融湖塘的个数和面积剧烈增加。根据热融湖塘历史时空演化规律，推测50年后，该区域热融湖塘的面积较2010年增大了1倍，约占研究区总面积的4.5%。100年后热融湖塘的面积接近2010年湖塘面积的5倍，约占研究区总面积的10.0%。
In the context of the development of the global warming and frequent human activities,permafrost degradation in the Qinghai-Tibet Plateau (QTP) is serious. Thermokarst lake, as one ofthe most typical thermal hazards, is also an important symbol of permafrost degradation. From theview of the aspects of environment and engineering, the effects of thermokarst lake to them aretypical and direct. In order to study thermokarst lakes in QTP in this thesis, a typical zone fromXiushuihe to Fenghuoshan along the Qinghai-Tibet Railway (QTR) and the Qinghai-TibetHighway (QTH) was selected to analyze the distribution and developing characteristics of thethermokarst lakes. From the perspective of disaster and geography, the works were based on theanalysis of aviation and spaceflight remote sensing data in different periods and monitoring thetypical zones. The conditions and factors influencing the thermokarst lake sensitivity, space-timeevolution characteristics of the thermokarst lakes were analyzed on the basis of GIS platform.Then the evaluation method of sensitivity was established and sensitivity evaluation of thethermokarst lakes was realized. In order to understand the space-time evolution laws of thethermokarst lakes more than40years, the development process of a typical lake, named BLH–A,and its development trend were studied through aviation images. The works might providereference for coordination and sustainable development planning and strategy implementationbetween the environment and local project in QTP. The main conclusions are as follows.
(1) The processing methods on QuickBird satellite image data with a resolution of0.6m in2006and the SPOT-5satellite image data with a resolution of2.5m in2010in the study areawere discussed. Focusing on fusion, correct and mosaic processing methods on thermokarst lakedominance, a better interpretation method of thermokarst lake was explored. According to theinterpretation marks of the thermokarst lakes, remote sensing data was interpreted, andinformation of thermokarst lakes was obtained.
(2) Six factors, including the type of permafrost, the ground temperature, vegetation type, soiltype, hydrogeological conditions and slope angle were selected to statistically analyze thedistribution of the thermokarst lake. After the analysis and evaluation of statistical results, usingthe mathematical statistics for the factors, the sensitive coefficient of each factor was calculatedand the results were evaluated. Finally, the sensitivity value of each factor was obtained through the average method. And the forming conditions of the thermokarst lakes were compared based onthe analysis of the sensitive factors. Then59comprehensive sensitivity coefficient indices indifferent geological environment in the study area were obtained, which provided the basis for thespace evolution analysis of the thermokarst lakes.
(3) In order to investigate the developing trend of the thermokarst lakes, a lake located in theBeiluhe Basin (named BLH-A) was dynamically monitored through remote sensing and fieldinvestigation. According to remote sensing images in1969,1999,2006,2008and2010, the areaof the BLH–A was increasing with the growth of0.35%from1969to1999, and then the rateincreased with time. Under the background of the global climate warming, the area was growingfaster and faster over time: the growth rate was0.42%from1999to2006,0.44%from2006to2008, and0.49%from2008to2010. And the expansion trend of the lake was also increasing.From1969to1999the dilation rate of the lake was0.42m/a. After1999the rate was around0.6m/a, and was up to0.65m/a after2008. Through calculation, the BLH–A expanded51.8mtoward QTR in41years, which would do damage to the roadbed of QTR. This result wasconsistent with field monitoring data, which showed that the shore of the lake collapsed and fellback constantly. From August2007to October2010, all the monitoring points along the lakeshoredrew back more than0.6m, with the maximum of3.2m.
(4) In order to analyze the evolvement law of Thermokarst Lake with the change of the timein41years from1969to2010, or before and after the Qinghai-Tibet highway and theQinghai-Tibet railway construction, combining with the geological environment sensitivity factorsand images of remote sensing dynamic monitoring project to Thermokarst Lake. The results showthat, during the41years, with increasing the PDmn, the total area of the thermokarst lakes and theannual growth rate increase accordingly. In addition, in the first30years, they grow slow;however, the number and the total area of the thermokarst lakes grow faster after the finishing ofthe Qinghai-Tibet railway construction. Moreover, the results forecast that the area of the totalthermokarst lakes will become doubling in the near50years, which is4.5%of the study area.After100years, the area will almost achieve five fold than that in2010, which could be10.0%ofthe study area.
引文
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