摘要
随着经济的不断发展,传统的一次性能源如煤炭、石油等出现了全球性的短缺。地热资源作为一种廉价、清洁的绿色新能源,己被人们日益关注。因而大力开发利用地热资源,对于调整能源供应结构、缓解能源供应压力、保障能源供应安全具有重要的作用。在地热资源的勘查中,由于热红外遥感反演技术具有快速、经济、大面积研究热量资源和热场分布变化的优势,己日益成为地热资源探测与调查方面的一种新趋势。
本文选取西藏羊八井地区作为运用热红外反演方法探测地热资源的研究区。具体内容如下:
(1)收集地表温度反演有关资料,确定研究区的反演算法,利用气象站的水汽含量和近地面气温来确定大气透射率和大气平均作用温度;
(2)对研究区影像进行大气校正,通过归一化植被指数的方法求解地表比辐射率,将估计的大气透射率、大气平均作用温度和地表比辐射率值代入确定的反演算法,进行地表温度反演并分析反演结果;
(3)根据Landsat 5 TM影像的特点和图像特征选取对研究最有利的TM影像数据,然后对图像进行校正、镶嵌、增强、融合等处理,提取对地热研究最有利的地质信息。
(4)结合研究区解译出的活动断层特征与地表温度异常图,确定研究区控制地热的主要构造。
(5)通过研究区主要地热构造与地表温度异常分析,根据区域地热背景确定的地热异常集中区。
研究表明,羊八井地区的地热异常与活动断层有关,主要集中于北东向与相应的北西向活动断层的交叉复合部位,地热异常的分布受活动断层控制。同时表明,单窗算法作为热红外遥感反演方法的一种行之有效的地表温度反演算法。它所取得的热图像资料具有直观、形象、速度快、不受交通条件限制等许多优点,在探测地热异常区,尤其对高原无人区的地热异常检测,有着重要的意义。
As the economical rapid development, the traditional energy like coal, petroleum and so on is in short at global scale. As one kind of inexpensive、clean green new energy, terrestrial heat resource has been paid greatattention day by day by the people. So full exploitation of terrestrial heat resource plays a Important role to adjust energy supply structure and alleviate the energy supply pressure. Because of its fast, economical, big area research to the heat resources and the hot field distribution change, thermal infrared inversion of remote sensing has become the Terrestrial heat resource survey and the investigation aspect one kind of new tendency day by day.
This article selects the Yangbajing Region of Tibet as the research area to apply thermal infrared inversion of remote sensing technique survey heat resource. As follows:
(1) Collect the information of land surface temperature, then determine inversion algorithm of research area and atmospheric transmission ratio and mean temperature by using vapor content of weather station and near ground temperature;
(2) Carry on atmospheric correction of images of study area, acquire LSE through the method of NDVI, input the estimate atmospheric transmission, mean temperature and surface ratio radiance to the decided inverse ground temperature and analyze the results.
(3) According to the characteristics of Landsat 5 TM images and image feature, select TM image data of the most favorabl Study,Then,through remote sensing images of the best band combinations, geometric correction, image enhancement, such as pre-processing , Extraction of this study the most favorable geological information.
(4) Interpretation of a combination of an active fault zone characteristics and surface temperature anomaly map of the study area to determine the main structural control of geothermal.
(5) Study area, mainly through structural and thermal analysis of surface temperature anomalies, the background of regional geothermal identified anomaly geothermal focus areas.
The research shows that geothermal anomaly of Yangbajain region and active faults were mainly concentrated in North East to the north west and the corresponding cross-composite parts of active faults, geothermal anomalies in the control by the active faults. Also shows that the single-window algorithm as a method of thermal infrared inversion of remote sensing is an effective surface temperature inversion. Thermal image data of its obtained has visual, image, speed, free from traffic conditions, and many other advantages, in particular, no man's land on the plateau geothermal anomaly detection, has an important significance .
引文
[1]顾小白.世界能源问题[M].北京:经济科学出版社.1985
[2]中国地质大学(武汉)水文地质工程系.山西省地下热水及饮用天然矿泉水研究[M].北京:地质出版社,1993
[3]王桥,杨一鹏,黄家柱.环境遥感[M].北京:科学出版社.2005
[4]李小文,王俊发,王锦地.多角度与热红外对地遥感[M].北京:科学出版社.2001
[5]佟伟,章铭陶.西藏地热[M].北京:科学出版社.1987
[6]丁凤,徐涵秋.基于LandsatTM的3种地表温度反演算法比较分析[J].福建师范大学学报,2004,24(2):91~96.
[7]覃志豪,ZhangMinghua,Arnom Karnieli.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4), 456~466.
[8]Jiménez-Munoz J C, Sobrino J A.A generalized single channelmethod for retr ieving land surface temperature from remote sensing data [J].Journal of eophysical Research, 2003, 108 (D22): 1~9.
[9]周彦儒.热红外遥感技术在地热调查中的应用与潜力[J].国土资源遥感.1998,38(4): 24~28.
[10]杨锋杰,韩震,江涛等.地热资源的热红外遥感[J].矿山测量,1998,(3),25~27.
[11]乔玉良.应用红外遥感寻找地下热水初探[J].航天返回与遥感,2003,23(1):33~35
[12]杨波,关德文,赖健清,唐攀科.遥感技术在腾冲西南地区地热资源研究预测中的应用[J].国土资源遥感,2003(2):23~26
[13]戴文晗.西安地区隐伏构造-热红外场遥感信息及三维建模与应用[J].遥感信息,2005 (1):40~43.
[14]刘培洵,刘力强,陈顺云,陈国强.从红外遥感图像提取地下热信息的透热指数法[J].地震地质,2004,26(3):519~526.
[15]张元生,郭晓,张小美,李明永.应用静止卫星热红外遥感亮温资料反演地表温度的方法研究[J].西北地震学报,2004,26(2):113~117.
[16]田国良.热红外遥感[M].北京:电子工业出版社.2006
[17]赵英世.遥感应用分析模型与方法[M].北京:科学出版社.2003
[18]徐希儒.遥感物理[M].北京:北京大学出版社.2005
[19]柳钦义,徐希儒,陈家宜.遥测地表温度与比射率的迭代反演算法[J].遥感学报, 1998,2(1):1~8
[20]陈良福.非同温混合像元热辐射方向性模型[D]. 1995博士论文,北京大学遥感所
[21]Para A J.Land surface temperature derived from the AVHRR and the ATSR expenmental results and validation of AVHRR algothms[J].Joural of geophysical research ,1994(D6): 13025~13058.
[22]梅新安,彭望绿,秦其明,刘慧平.遥感导论[M].北京:高等教育出版社,2001.
[23]宁书年等.遥感图像处理与应用[M].北京:清华大学出版社,1995.
[24]曹广真.多元数据融合入在金矿成矿预测中的应用[硕士论文].青岛.山东科技大学.2003.
[25]杨永兴.国际湿地科学研究的主要特点、进展与展望[J].地理科学进展. 2002(2):111~118
[26]党安荣,王晓栋等. ERDAS IMAGING遥感图像处理方法[M].北京:清华大学出版社. 2003:111~112
[27]覃志豪,Liwenjun ZhangMinghua etc.单窗算法的大气参数估算方法[J].国土资源遥感,2003,56(2):37~43.
[28]陈华慧.遥感地质学[M].北京:地质出版社,1984.
[29]张樵英,闻立峰.遥感图像目视地质解译方法[M].北京:地质出版社,1986: 10~11.
[30]陈华慧.遥感地质学[M].北京:地质出版社,1984:85
[31]成永生.桂北区带九万大山成矿区遥感找矿预浏研究:[硕士学位论文].长沙:中南大学,2005..
[32]李国填.天山阿拉沟地区地质地球化学ETM+遥感图像处理与找矿靶区圈定[硕士论文].西安:长安大学,2006.
[33]杨期隆,辛奎德.西藏羊八井地热田简介[J].地质评论,1991,37(3):283~287.
[34]吴钦.西藏羊八井地热田物探新成果研究[J].物探与化探,1996,20(2):131~137
[35]魏斯禹,腾吉文,杨秉平,胡忠义.西藏高原地热活动、温泉分布与地球物理场特征.长衫.西北地震学报.1981,3(4);17~24
[36]中国地质科学院地质力学研究所.当雄幅1:25万区域地质调查报告[R].2003.
[37]吴珍汉,叶培盛,胡道功.青藏高原腹地的地壳变形与构造地貌形成演化过程〔M〕.北京:地质出版社,2003
[38]葛碧如.用诺阿卫星探察隐伏地下构造、地热及水资源〔J〕.中国航天. 1997(1):8~10