College of Ecology and Environment,Xinjiang University
Institute of Arid Eco-Environmental Sciences,Xinjiang University
Key Laboratory of Oasis Ecology of Education Ministry

以准南煤田四棵树火区煤火为研究对象,选取2006—2020年覆盖研究区的Landsat系列影像,采用像元二分法及温度反演算法反演得到该区域的植被覆盖度和地表温度的分布,分析结果表明:低植被覆盖度的区域占比由38.6%降低至13.9%,高植被覆盖度区域占比由15.6%增长至29.0%;高温区域呈东北—西南直线分布,低温区域主要分布在西向山坳及山坳西侧,阈值提取最高温度为48.62℃。选取2014—2019年29景SAR影像进行SBAS-InSAR分析,融合植被覆盖度及地表温度反演,确定火区烟气逸散通道及空气渗入通道位置与数量,分析结果表明:在2014—2019年烟气逸散通道由7个增加至68个,空气渗入通道数量由58个增加至84个;整体裂隙数量呈现增加的趋势,且烟气逸散通道数量增加较快,地下煤火燃烧加剧。

Taking coal fires in Sikeshu sealed fire area of Zhunnan coal field as the research object,the images of the study area during the period 2006-2020 were selected from the Landsat series,and the vegetation coverage and surface temperature distribution in this area were retrieved by pixel dichotomy and temperature inversion algorithm. The results show that the proportion of low vegetation cover area decreases from 38. 6% to 13. 9%,and the proportion of vegetation coverage increases from 15. 6% to 29. 0%. The high temperature area is distributed in a straight line from northeast to southwest. The low temperature area mainly exists in the west-facing depression and the west side of the depression; the maximum temperature of the threshold extraction is 48. 62 ℃. 29 SAR images from 2014 to 2019 were selected for SBAS-InSAR analysis,and the regetatio coverage and surface temperature inversion was integrated to determine the location and quantity of the smoke escape channels and air inflltration channels in the sealed fire area. The results show that the number of air escape channels increases from 7 to 68 and the number of air infiltration channels increaes from 58 to 84 between 2014 and 2019. The number of cracks in the whole shows an increasing trend,and the number of flue gas escape channels increases rapidly, and the underground coal fire combustion intensifies.

新疆科技厅“煤火灾害治理”天山创新团队项目(2021D14018)

刘小姣,曾强. 融合遥感技术在四棵树火区煤火识别中的应用[J]. 矿业安全与环保,2023,50(6):104-110.

LIU Xiaojiao,ZENG Qiang. Application of fusion remote sensing technology for coal fire identification in the Sikeshu sealed fire area[J]. Mining Safety & Environmental Protection,2023,50(6):104-110.