地质灾害数据处理与质量控制研究

发布时间：2018-02-17 02:07

本文关键词： 地质灾害数据处理数据质量　出处：《成都理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：我国是一个地质灾害多发的国家,灾害类型多样、分布广泛,对群众的生产生活和社会经济发展造成了巨大的影响。在地质灾害监测与预警过程中,收集处理地质灾害数据是重要步骤之一,因此数据质量可以说是地质灾害项目的灵魂与核心,与能否取得预期成果息息相关。由于地质灾害的特性,地质灾害数据不仅包括发生地的地质地理条件,还包括社会经济条件,日新月异的信息变化为地质灾害数据的收集与处理增加了难度,带来了挑战。如何保证地质灾害数据的质量、做出科学的决策、开展防灾减灾活动,是地质灾害项目中需要思考的问题。对此,需要提出数据质量检查和控制方面的问题,并加以研究和解决。以西藏阿里普兰县地质灾害数据为例,对如何开展地质灾害数据质量控制与处理工作进行了研究,旨在检验数据质量问题,优化数据精度,开展后续工作。依照地质矿产行业标准等相关资料,数据质量检查包括数据完整性、空间数据定位准确性、逻辑一致性等方面。在研究中,将地质灾害数据分为属性数据和空间数据:属性数据主要表达地质灾害点的资料收集和调查情况,并作出初步推断和预测;空间数据主要对属性数据的地理位置、地形地貌、地物类型等内容进行细化补全,得到地质灾害点在空间上的反映结果。依照标准对二者分别检查,并优化数据质量,主要研究内容为:(1)依托于地质灾害调查等方面的理论基础和行业标准,进行了属性数据完整性和准确性检查。由于地质灾害点的灾害类型不同,需要检查的内容也有所不同,对不同类型的灾害点依照不同的质检标准进行检查,补全了缺失的属性数据项,删除了多余的数据项,并将属性数据依照AHP层次分析法进行筛选整合处理,为关联检查做好准备工作;(2)对空间数据进行了数据采集精度和空间数据定位准确性的检查,发现了等高线断线、地理配准不够精确等质量问题,并加以校正,根据空间内插运算的原理,结合TIN和反距离权重法,对等高线数据进行了较为科学准确的补全重连;对空间数据进行ISODATA非监督分类法,利用已有影像图验证分类精度;根据图形特征点提取的相关理论,提取了以形状特征为主的控制点,进行栅格到矢量的地理配准,校正地质灾害点定位上存在的细微偏差;(3)将属性数据与空间数据结合起来进行关联检查,通过对比地形、覆被等因素,得到关联检查验证表,发现质量问题,并提出可行的工作建议。
[Abstract]:China is a country prone to geological disasters, which has a variety of types and wide distribution, which has a great impact on the production and life of the masses and the development of social economy. In the process of monitoring and early warning of geological disasters, The collection and processing of geological hazard data is one of the important steps, so data quality can be said to be the soul and core of geological disaster project, which is closely related to whether or not the expected results can be achieved. Geological hazard data include not only the geological and geographical conditions of the place where they occur, but also social and economic conditions. The ever-changing information makes it more difficult to collect and process geological hazard data. This brings challenges. How to ensure the quality of geological hazard data, make scientific decisions, and carry out disaster prevention and mitigation activities is a problem to be considered in geological hazard projects. In this regard, problems in data quality inspection and control need to be raised. Taking the geological hazard data of Aliplan County in Tibet as an example, this paper studies how to carry out the quality control and processing of geological hazard data in order to test the problem of data quality and optimize the data accuracy. To carry out follow-up work. In accordance with relevant data such as geological and mineral industry standards, data quality checks include data integrity, spatial data positioning accuracy, logical consistency, and so on. The geological hazard data is divided into attribute data and spatial data: attribute data mainly express the data collection and survey of geological hazard points, and make preliminary inference and prediction; spatial data mainly relate to the geographical location, topography and geomorphology of attribute data, The types of ground objects are refined and completed, and the spatial reflection results of geological hazard points are obtained. They are checked separately according to the standards, and the quality of the data is optimized. The main research content is: 1) based on the theoretical basis and industry standards of geological hazard investigation and other aspects, the integrity and accuracy of attribute data are checked. Due to the different types of disasters in geological hazard sites, the contents that need to be inspected are also different. The different types of disaster points are checked according to different quality inspection standards, the missing attribute data items are filled, the redundant data items are deleted, and the attribute data is filtered and integrated according to the AHP Analytic hierarchy process. The accuracy of data acquisition and location of spatial data is checked, and the quality problems of contour line breaking and geographic registration are found and corrected. According to the principle of spatial interpolation, combined with TIN and inverse distance weight method, the contour data is complemented with full and accurate method, and the spatial data is classified by ISODATA unsupervised classification method, and the classification accuracy is verified by the existing image map. According to the theory of drawing feature points, the control points with shape feature are extracted, and the raster-to-vector geographic registration is carried out. The minor deviation in the location of corrected geological hazard points is used to combine attribute data with spatial data for correlation checking. By comparing terrain, covering and other factors, the associated check verification table is obtained, and the quality problems are found. And put forward feasible work suggestion.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P694

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