兖州矿区地表水体和煤堆固废占地变化的遥感检测
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摘要
遥感在矿区环境监测中发挥了重要作用。兖州矿区地处鲁西南平原,年产原煤超过3000万t。多年高强度的地下采矿活动对矿区地表环境产生了很大影响,主要表现为塌陷区大面积积水和煤堆及固体废弃物占地。本文以美国陆地卫星(LandSat) TM/ETM+图像为信息源,选用1987年9月的TM图像和2002年5月的ETM+图像,对兖州矿区15年间地表水域(主要为塌陷区积水)和煤堆及固废占地的变化信息进行研究。
先对两类地物的光谱曲线进行分析,进而找出区分两类地物的特征波段,分别对其进行提取。具体方法是先利用NDWI提取出两类地物信息,再利用5波段取适当阈值将两类信息区分开。根据温度变化特征及热辐射特性均不同,反演了矿区的温度图像对提取信息进行验证。显然,由于存在较大的温度差异(至少10K以上),使本来混在一起的水体和煤堆及固废很容易区分开。对1987年兖州矿区的TM数据采用同样方法进行处理,将两个时相的结果进行对比,2002年兖州矿区的固废堆场占地和地表塌陷区积水面积分别是1987年的1.90倍和3.87倍。塌陷区积水面积变化主要集中在矿区的南屯、兴隆庄、东滩三个煤矿,煤堆及固废堆场变化主要集中在东滩、鲍店和济二矿等地。
Satellite remote sensing plays an important role in environmental monitoring for mining area. Yanzhou coal mining area, which lies in Luxinan Plain of Shandong Province, has an annual yield of 3000×104t. It makes a strong environmental and ecological impact on surface because of high-intensity mining for many years. Mining subsidence resulted surface water body and coal and solid-waste dump, which take a large area of farmland, are the two main aspects of the impact. This paper selects a group of multi-temporal TM/ETM+images (acquired in 1987 and 2002 respectively) from LandSat as the information source to study the change information of the two aspects during the past 15 years.
The images acquired in 2002 are taken as an example. Normalized Difference Water Index (NDWI) is got firstly; then, water information could be extracted with appropriate threshold value according to NDWI. What is mixed in water is coal and solid-waste dump including coal gangue, and fly ash and so on. After analyzing the spectral characteristics, DN value 40 in band 5 is chosen as threshold value to distinguish coal and solid-waste from water. Mining subsidence resulted water body and coal and solid-waste dump are of different characteristics in temperature change and heat radiation. Using some formula-transformation, the ground brightness temperature is retrieved from DN in thermal infrared band (band 6 of TM/ETM+ images) which could reveal the difference of thermal field of land surface. The result shows that because of great temperature difference (more than 10K), the mixed information of water body and coal and solid-waste dump is easy to be specified. The methods are also applied for the satellite remote sensing images of Yanzhou coal mining area acquired in 1987. It is founded that in Yanzhou mining area, the area of solid-waste dump and mining subsidence resulted water body in 2002 is 0.90 times and 2.87 times greater than that in 1987 respectively. The main changed areas of mining subsidence resulted water bodies are located nearby Nantun coal mine, Xinglongzhuang coal mine and Dongtan coal mine. The main change areas of solid-waste dump are around Dongtan, Baodian and Jier coal mine.
先对两类地物的光谱曲线进行分析,进而找出区分两类地物的特征波段,分别对其进行提取。具体方法是先利用NDWI提取出两类地物信息,再利用5波段取适当阈值将两类信息区分开。根据温度变化特征及热辐射特性均不同,反演了矿区的温度图像对提取信息进行验证。显然,由于存在较大的温度差异(至少10K以上),使本来混在一起的水体和煤堆及固废很容易区分开。对1987年兖州矿区的TM数据采用同样方法进行处理,将两个时相的结果进行对比,2002年兖州矿区的固废堆场占地和地表塌陷区积水面积分别是1987年的1.90倍和3.87倍。塌陷区积水面积变化主要集中在矿区的南屯、兴隆庄、东滩三个煤矿,煤堆及固废堆场变化主要集中在东滩、鲍店和济二矿等地。
Satellite remote sensing plays an important role in environmental monitoring for mining area. Yanzhou coal mining area, which lies in Luxinan Plain of Shandong Province, has an annual yield of 3000×104t. It makes a strong environmental and ecological impact on surface because of high-intensity mining for many years. Mining subsidence resulted surface water body and coal and solid-waste dump, which take a large area of farmland, are the two main aspects of the impact. This paper selects a group of multi-temporal TM/ETM+images (acquired in 1987 and 2002 respectively) from LandSat as the information source to study the change information of the two aspects during the past 15 years.
The images acquired in 2002 are taken as an example. Normalized Difference Water Index (NDWI) is got firstly; then, water information could be extracted with appropriate threshold value according to NDWI. What is mixed in water is coal and solid-waste dump including coal gangue, and fly ash and so on. After analyzing the spectral characteristics, DN value 40 in band 5 is chosen as threshold value to distinguish coal and solid-waste from water. Mining subsidence resulted water body and coal and solid-waste dump are of different characteristics in temperature change and heat radiation. Using some formula-transformation, the ground brightness temperature is retrieved from DN in thermal infrared band (band 6 of TM/ETM+ images) which could reveal the difference of thermal field of land surface. The result shows that because of great temperature difference (more than 10K), the mixed information of water body and coal and solid-waste dump is easy to be specified. The methods are also applied for the satellite remote sensing images of Yanzhou coal mining area acquired in 1987. It is founded that in Yanzhou mining area, the area of solid-waste dump and mining subsidence resulted water body in 2002 is 0.90 times and 2.87 times greater than that in 1987 respectively. The main changed areas of mining subsidence resulted water bodies are located nearby Nantun coal mine, Xinglongzhuang coal mine and Dongtan coal mine. The main change areas of solid-waste dump are around Dongtan, Baodian and Jier coal mine.
引文
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4. Clark R. N. Mapping Minerals with Imaging Spectroscopy. U. S. Geological Survey, Office of Mineral Resources Bulletin,2039:141～150
5. Swayze Gregg A, et al. Using Imaging Spectroscopy to Map Acidic Mine Waste. Environmental Science and Technology,2000,34(1):47～54
6. John C. Mars, James K. Crowley. Mapping mine wastes and analyzing areas affected by selenium-rich water runoff in southeast Idaho using AVIRIS imagery and digital elevation data [J]. Remote Sensing of Environment,2003,84(3): 422-436
7. http://www2.brgm.fr/mineo
8. http://viso.ei.jrc.it/pecomines_ext/index.html
9. A. Prakash, R. P. Gupta. Land-use mapping and change detection in a coal mining area--a case study in the Jharia coalfield, India [J]. International Journal of Remote Sensing,1998,19(3):391～410
10. Richard J. Ellis, Peter W. Scott. Evaluation of hyperspectral remote sensing as a means of environmental monitoring in the St. Austell China clay (kaolin) region, Cornwall, UK [J]. Remote Sensing of Environment,2004,93 (1-2):118～130
11. Rasim Latifovic, Kostas Fytas, Jing Chen, et al. Assessing land cover change resulting from large surface mining development [J]. International Journal of Applied Earth Observation and Geoinformation,2005,7(1):29～48
12. Schmidt H., Glaesser C. Multitemporal analysis of satellite data and their use in the monitoring of the environmental impacts of open cast lignite mining areas in Eastern Germany[J]. International Journal of Remote Sensing,1998,19(12): 2245～2260
13. Prasun K Gangopadhyay, Kuntala Lahiri-Dutt, et al. Application of remote sensing to identify coalfires in the Raniganj Coalbelt, [J]. International Journal of Applied Earth Observation and Geoinformation,2006,8(3):188～195
14.孔祥生,苗放,刘鸿福等.利用多时相Landsat遥感图像数据对土法炼焦点进行动态监测——以山西省东南部地区为例[J].遥感技术与应用,2005,20(5)：460-464
15.漆小英,晏明星.多时相遥感数据在矿山扩展动态监测中的应用[J].国土资源遥感,2007(3)：85～88
16.汪宝存,苗放,晏明星等.基于遥感技术的开滦煤矿地面塌陷积水动态监测[J].国土资源遥感,2007(3)：94-97
17.甘甫平,王润生,杨苏明.西藏Hyperion数据蚀变矿物识别初步研究[J].国土资源遥感,2002(4)：44-50
18.张宗贵,王润生,郭小方等.基于地物光谱特征的成像光谱遥感矿物识别方法[J].地 学前缘,2003,10(2)：437-443
19.甘甫平,刘圣伟,周强等.德兴铜矿矿山污染高光谱遥感直接识别研究[J].地球科学,2004,29(1)：119-126
20.周强,甘甫平,王润生等.高光谱遥感影像矿物自动识别与应用[J].国土资源遥感,2005(4)：28-31
21.王晓红,聂洪峰,杨清华等.高分辨率卫星数据在矿山开发状况及环境监测中的应用效果比较[J].国土资源遥感,2004(1)：15～18
22.李成尊,聂洪峰,汪劲等.矿山地质灾害特征遥感研究[J].国土资源遥感,2005(1)：45～48
23.刘琼,聂洪峰,吕杰堂等.GIS在矿产资源开发状况遥感动态监测中的应用[J].国土资源遥感,2005(1)：61-65
24.王晓红,聂洪峰,李成尊等.不同遥感数据源在矿山开发状况及环境调查中的应用[J].国土资源遥感,2006(2)：69-71
25.迟光宇,刘新会,刘素红等.环境污染监测中的植物光谱效应研究[J].环境科学与技术,2005,28(增)：16-19
26.赵祥,刘素红,王安建等.基于卫星遥感数据的江西德兴铜矿开采环境影响动态监测分析[J].中国环境监测,2005,21(2)：68-73
27.颜春,刘素红,赵祥.矿山环境遥感综合评价指标的研究[J].遥感信息,2005(6)：29-31
28.陈华丽,陈刚, 李敬兰等.湖北大冶矿区生态环境动态遥感监测[J].资源科学,2004,26(5)：132-138
29.王广军,付梅臣,张继超.草原露天矿区草地荒漠化遥感分析与治理对策——以霍林河露天煤矿区为例[J].中国矿业大学学报,2007,36(1)：42～48
30.毕如田,白中科.基于遥感影像的露天煤矿区土地特征信息及分类研究[J].农业工程学报,2007,23(2)：77～82
31.李琳,袁春,周伟等.平朔露天矿区土地利用／覆盖变化分析[J].资源与产业,2007,9(3)：5-9
32.陈龙乾,郭达志,胡召玲等.徐州矿区土地利用变化遥感监测及塌陷地复垦利用研究[J].地理科学进展,2004,23(2)：10-15
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