地理科学进展 ›› 2004, Vol. 23 ›› Issue (3): 27-33.doi: 10.11820/dlkxjz.2004.03.004

• 遥感与地理信息技术应用 • 上一篇    下一篇

用相关分析法约简MCSs空间数据库

方兆宝1,2,3, 林 珲2, 吴立新1, 江吉喜4   

  1. 1. 中国矿业大学,北京 100083;
    2. 香港中文大学中科院地球信息科学联合实验室,香港;3. 中国人民解放军91561部队测绘处, 广州 510320;
    4. 中国气象局国家卫星气象中心,北京 100081
  • 收稿日期:2003-12-01 修回日期:2004-03-01 出版日期:2004-05-25 发布日期:2004-05-25
  • 作者简介:方兆宝(1962-),男,浙江省义乌市人,博士,现任中国人民解放军91561部队高级工程师,上校军衔。主要从事海洋水文气象、3S集成与应用、空间数据挖掘等工作与研究。E-mail:fzbdr@263.net
  • 基金资助:

    香港特区政府研究资助项目(CUHK4132/99H)。

To Reduce MCSs Spatial Data Database Using Correlation Analytical Method

FANG Zhaobao1,2,3, LIN Hui2, WU Lixin1, JIANG Jixi4   

  1. 1. China University of Mining &|Technology,Beijing 100083;
    2. Joint Laboratory for Geoinformation Science, Chinese University of Hong Kong,HongKong;3. The P.L.A.91561 Command, Guang Zhou 510320;
    4. Natinal Satellite Meteorological Center, China Weather Bureau,Beijing 100081
  • Received:2003-12-01 Revised:2004-03-01 Online:2004-05-25 Published:2004-05-25

摘要:

长江流域出现致洪大暴雨与青藏高原上中尺度对流系统(MCSs)的东移密切相关。为了寻找MCSs移动和传播的规律,我们将MCSs的移动路径与其中心附近一定范围内的环境物理量场之间建立联系,构造出MCSs东移空间数据挖掘数据库。在这个数据库中,包含由9个环境物理量生成的18个属性项,除此,还包括由MCSs本身的空间特征量构成的5个属性项,即TBB强度、面积、地理位置、形状等,共计23个属性项。利用1998年6月至8月日本地球静止气象卫星(GMS)的青藏高原逐时红外遥感云图计算出的云顶黑体辐射温度(TBB)及青藏高原高分辨率有限区域数值分析预报值系统(HLAFS)环境场物理量数据, 构造出上述空间数据挖掘数据库,运用空间相关分析技术对其进行约简,结果表明:在高度(H)、温度(T)、涡度(VOR)、散度(DIV)、水汽通量散度(IFVQ)、垂直速度(W)、假相当位温(θse)、K指数(K)、相对湿度(RH)等9个因素中,高度、涡度、散度、水汽通量散度、垂直速度及k指数6个因素相对独立;而温度(T)、假相当位温(θse)、相对湿度(RH)之间相关性较强,而且与高度等其它6个因素密切相关。根据数据库约简原则,可将温度(T)、假相当位温(θse)、相对湿度(RH)3个因素生成的6个属性项从数据库中删除,以便提高数据挖掘效率。

关键词: 红外遥感, 空间数据挖掘, 青藏高原, 相关分析法, 中尺度对流系统(MCSs)

Abstract:

Several heavy rainfalls in Changjiang River Basin are considered to be highly related to the moving out of the mesoscale convective systems (MCSs) from the Tibetan Plateau to the east. To discover the rules of MCSs moving and promulgating, the relationship is established between moving trace of MCSs and its surrounded environmental physical field. And the database of spatial data mining is designed to the MCSs moving out to east from Tibetan Plateau. In the database of spatial data mining, there are not only 18 attribute terms brought by 9 environmental physical variables, but also some spatial character terms of MCSs, such as area, position, shape, and intension of MCSs. By analyzing the cloud-top’s temperature of black body (TBB) from the hourly GMS infrared images and the data of the High Resolution Limited Area Forecast System (HLAFS) of the Tibetan Plateau from June to August in 1998, the database of spatial data mining is built. It is studied that the database is reduced using correlation analytical method. The study reveals that the height(H), the vortex (VOR), the divergent(DIV), the water vapor flux divergent(IFVQ), the wind aplomb speed(W) and the K-index are relatively independent parameters among the nine environment physical variables around the MCSs, while the temperature(T), the fake correspond potential temperature (θse) and the relative humidity(RH) are highly related to each other,as well as to the Height. Hence, we suggest that the temperature(T), the fake correspond potential temperature(θse) and the relative humidity(RH) be not considered for the construction of the data base of MCSs spatial data mining, so as to increase the efficiency of the MCSs spatial data mining and to reduce the data redundancy.

Key words: correlation analytical method, infrared remote sensing, mesoscale convective systems (MCSs), spatial data mining, Tibetan Plateau