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山西省因其地质构造而拥有丰富的煤炭资源,与此同时,在煤田边缘、煤层浅埋藏地带及废弃煤窑采空区存在大量煤层自燃现象。针对山西省煤层自燃和基础调查数据特征,本文应用地理信息系统理论方法,研建了山西省煤层自燃信息管理系统。本文从有效管理煤层自燃信息角度出发,就系统架构设计、数据库设计、功能设计进行论述,依据全省煤层自燃、煤炭资源等图形、数据资料,建立山西省煤层自燃信息管理系统,从而更好地支持政府决策,促进煤层自燃的治理与开发二者之间的协调发展。 相似文献
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煤层自燃是煤炭资源的主要危害之一,它对煤层破坏作用巨大,导致自燃煤层周围煤炭资源的开采困难和贬值,同时也对生态环境产生了恶劣影响.利用GPS RTK技术测定平庄煤田火区1∶2 000地形图,确定火区位置,用物探、遥感和遥测等新技术进行煤火监测,火区灾害防治和矿区环境保护,火区灭火工程、矿井安全生产和矿区可持续发展都具有... 相似文献
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根据遥感物理基础,提出了应用DTM计算出地表的太阳辐射强度,并以此为依据校正TM第6波段的象元值,消除地形的影响,突出由煤层自燃引起的地表热异常,为灭火工程及火区动态监测提供信息和指导。文中选择了新疆准南煤田的硫磺沟火区为试验区,展示了研究的成果。 相似文献
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煤层自燃是中国北方煤田中普遍存在的灾害现象,它不但烧掉了大量的煤炭资源,而且还污染了环境。实践证明,利用遥感影像判别火区位置、圈定火区范围和对火区进行动态监测,及时为灭火工程提供信息,是一项经济和社会意义很大的工作。由于受多种因素的制约,不同地区、不同波段、不同时相、不同空间分辨率的遥感图像,其影像特征(含与煤层自燃有关的热异常影像特征)都有较大的差异,因而从图像上分析和提取地物的热红外辐射特征时,需要考虑遥感图像类型、成像时间、地形条件、气象条件和岩性特征等因素的影响。本文着重讨论了地表辐射温度与上述各项因素之间的关系。 相似文献
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煤层自燃是中国北方煤田中普遍存在的灾害现象,它不但烧掉了大量的煤炭资源,而且还污染了环境。实践证明,利用遥感影像判别火区位置、圈定火区范围和对火区进行动态监测,及时为灭火工程提供信息,是一项经济和社会意义很大的工作。由于受多种因素的制约,不同地区、不同波段、不同时相、不同空间分辨率的遥感图像,其影像特征(含与煤层自燃有关的热异常影像特征)都有较大的差异,因而从图像上分析和提取地物的热红外辐射特征时,需要考虑遥感图像类型、成像时间、地形条件、气象条件和岩性特征等因素的影响。本文着重讨论了地表辐射温度与上述各项因素之间的关系。 相似文献
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本课题以可见光黑白航空像片为主要信息源,对陕西神府煤田新民烧变区进行了1:5万航空遥感地质调查,圈定了该区烧变岩分布范围及煤层自燃边界线。文中着重介绍了遥感调查煤层烧变区的技术方法与工作成果。调查区为煤层自燃死火区。调查首先从烧变岩的基本地质特征入手,划分了烧变岩的宏观类型,确定了烧变岩的主要形成时代,探讨了烧变岩的形成机理;第二,根据掌握资料选取已知区,研究烧变岩及煤层自燃边界线的影像特征,建立初步解译标志;第三,在全区范围内进行煤层自燃边界线的遥感调查,并对解译标志进行补充、修改与完善。在调查中,解译与调绘相结合,遥感与地面调查方法相结合,最终圈定了区内各煤层的自燃边界线,并经钻孔验证,精度达到要求。 相似文献
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新疆拜城地区煤田煤层自燃的陆地卫星遥感探测方法研究 总被引:1,自引:0,他引:1
利用TM图像,结合区域实测、地质和区域能源分布资料,分析了煤田煤层自燃的光谱特征,对煤田地火燃烧区进行定位;在此基础上对新疆拜城地区TM图像进行线性变换、边界增强、波段运算、多波段假彩色合成等增强处理,识别并提取影像中煤田煤层自燃引起的地表热信息、地表植被异常和岩石烧变信息等,通过分析达到探测煤田火区的目的。 相似文献
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地下煤火分布广泛,屡治不止,造成资源浪费、生态破坏。中国是世界上煤火灾害最严重的国家,80%的煤层有自燃倾向。煤田隐蔽火源的快速、全面、及时、精准探测是实现防灭火及生态治理的基础和前提,多源遥感极具应用潜力,但需穿透地表、深入地下,存在诸多瓶颈。将煤田隐蔽火源多源遥感探测问题抽象为同源(同一地下自燃火源)、多象(地表形成的多种异常现象)、多像(多源遥感拍摄的包括多种地表异常信息的影像)关键节点及同源多象-象像映射-源象传递-多像识源研究链条进行分析,在此基础上探讨煤田隐蔽火源多源遥感探测的技术瓶颈,给合中国新疆维吾尔自治区阜康、米泉、宝安等火区隐蔽火源探测实际,给出在极化时序InSAR火区形变探测、时空温度阈值法火区圈定、多源卫星遥感火区联合识别、无人机火区监测试验等方面的研究进展及效果,展望了地下煤火多源天空地井协同感知认知研究的发展方向。 相似文献
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朱爱萍 《测绘与空间地理信息》2018,(3):83-86
煤田自燃一直是煤矿生产不容忽视的问题。本文利用热红外遥感技术检测因煤火导致地面温度异常的地区,采用两种不同的遥感反演温度算法(单窗算法、基于影像的算法),使用ETM+数据并通过阈值分割法提取2010年乌尊布拉克煤田火区的温度。结果表明,两种遥感反演算法得到的地下煤火区地表温度的空间分布趋势一致,反演结果符合要求。据此对地下煤火的变化类型进行判断,并确定煤火的生成状况,从而为煤田火灾防治提供必要的决策支持。 相似文献
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Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9 × 9 pixels for ASTER and 27 × 27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold. 相似文献
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Many real-world applications require remotely sensed images at both high spatial and temporal resolutions. This requirement, however, is generally not met by single satellite system. A number of spatiotemporal fusion models have been developed to overcome this constraint. Landsat and Visible Infrared Imaging Radiometer Suite (VIIRS) data have been extensively used for detection and monitoring of active fires at different scales. Fusing the data obtained from these sensors will, therefore, significantly contribute to the satellite-based monitoring of fires. Among the available spatiotemporal fusion methods, the spatial and temporal adaptive reflectance fusion model (STARFM) and enhanced STARFM (ESTARFM) algorithms have been widely used for studying the land surface dynamics in the homogeneous and heterogeneous regions. The present study explores the applicability of STARFM and ESTARFM algorithms for fusing the high spatial resolution Landsat-8 OLI data with high temporal resolution VIIRS data in the context of active surface coal fire monitoring. Further, a modified version of ESTARFM algorithm, referred as modified-ESTARFM, is developed to improve the performance of the fusion model. Jharia coalfield (India), known for widespread occurrences of coal fires, is taken as the study area. The qualitative and quantitative assessments of the predicted (synthetic) Landsat-like images from different algorithms (STARFM, modified-STARFM, ESTARFM, modified-ESTARFM) indicate that the modified-ESTARFM outperforms the other fusion approaches used in this study. Considering the advantages, limitations and performance of the algorithms used, modified-ESTARFM along with STARFM can be used for surface coal fire monitoring. The study will not only contribute to remote sensing based coal fire studies but also to other applications, such as forest fires, crop residue burning, land cover and land use change, vegetation phenology, etc. 相似文献