基于结果验证的信息量法地质灾害易发性评价——以贵州省开阳县为例
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摘要
传统信息量法将所有评价因子的信息量值进行综合,未对评价因子作优化选择,选择带有主观性。鉴于此,采用结果验证对信息量法进行改进,选取工程岩组、断层、河流、道路、坡度、坡向、剖面曲率7个评价因子。首先利用地质灾害编录数据与评价因子进行空间叠加分析,计算单因子信息量,然后利用成功率曲线法评价单因子评价结果的模型拟合能力,按照模型拟合能力从高到低将单因子信息量排序,并依次进行总信息量试算,得到7组试算结果。最后对7组试算结果进行模型拟合能力评价,确定AUC为前4的因子组合为最优的因子组合。
The traditional information quantity model synthesizes all the evaluation factors without optimization,which is subjective. Therefore,the results validation is adopted to improve the information quantity model by selecting seven evaluation factors,namely lithology,fault,stream,road,slope ratio,slope direction and profile curvature. Firstly,the geological logging data and the evaluation factors are employed to carry out an overlay analysis,so the information value of single factor is obtained. Secondly,the success ratio curve method is used to evaluate the model fitting capacity of the single factor; the information quantity of evaluation factors are ranked according to the model fitting capacity,and seven sets of total information quantity are obtained by trial calculation. Finally,the calculation results are evaluated so as to provide an assessment to the model fitting capacity,and the combination of top 4 AUC factors is determined as the best.
The traditional information quantity model synthesizes all the evaluation factors without optimization,which is subjective. Therefore,the results validation is adopted to improve the information quantity model by selecting seven evaluation factors,namely lithology,fault,stream,road,slope ratio,slope direction and profile curvature. Firstly,the geological logging data and the evaluation factors are employed to carry out an overlay analysis,so the information value of single factor is obtained. Secondly,the success ratio curve method is used to evaluate the model fitting capacity of the single factor; the information quantity of evaluation factors are ranked according to the model fitting capacity,and seven sets of total information quantity are obtained by trial calculation. Finally,the calculation results are evaluated so as to provide an assessment to the model fitting capacity,and the combination of top 4 AUC factors is determined as the best.
引文
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[2]阮沈勇,黄润秋.基于GIS的信息量法模型在地质灾害危险性区划中的应用[J].成都理工学院学报,2001,(1):89-92.
[3]吴柏清,何政伟,刘严松.基于GIS的信息量法在九龙县地质灾害危险性评价中的应用[J].测绘科学,2008,(4):146-147,131.
[4]汤连生,周萃英.基于信息量法的斜坡破坏概率预测与制图[J].中山大学学报:自然科学版,1995,(4):100-105.
[5]陈广洲,徐晓春,汪家权.一种信息量和专家证据权重法耦合的成矿预测方法[J].测绘科学,2013,(1):146-149.
[6]魏冠军,党亚民,章传银,等.GIS的信息量法在澜沧老厂成矿预测中的应用[J].测绘科学,2010,(6):217-218,246.
[7]方国柱,张正禄,章传银.工程高边坡稳定性评价的信息量法[J].武汉测绘科技大学学报,1996,(4):38-43.
[8]光磊.基于GIS的信息量法在滑坡危险性评价中的应用[J].地质与资源,2005,(3):231-233.
[9]邓辉,何政伟,陈晔.信息量模型在山地环境地质灾害危险性评价中的应用[J].自然灾害学报,2014,23(2):67-75.
[10]罗真富,蒲达成,谢洪斌,等.基于GIS和信息量法的泥石流流域滑坡危险性评价[J].中国安全科学学报,2011,(11):144-150.
[11]杜娟,殷坤龙,陈丽霞.基于GIS的巴东县新城区滑坡灾害危险性区划[J].自然灾害学报,2011,(1):149-155.