空间数据质量控制方法在土地变更遥感监测项目上的应用

发布时间：2018-04-13 10:05

本文选题：遥感监测 + 过程标准化　；参考：《成都理工大学》2013年硕士论文

【摘要】：数据质量是保证项目所生产出的数据具有价值的关键，是数据的基本属性之一。数据质量若不明是不能被使用的，更不能构建数据库在大范围内进行共享。因此，空间数据在生产完成之后都须进行质量检查与验收，鉴定数据的质量，为之后对该数据的使用提供质量保证。土地变更调查作为一项全国性的大型项目，其遥感监测阶段所生产的数据，是这个项目能否顺利进行之后的变更调查、数据统计、成果验收等阶段的基础。故遥感监测阶段生产数据质量是否有保证，对整个国有土地变更所更新数据的准确性，是十分重要的。要保证遥感监测项目的成果数据即要达到必要的质量要求，又不能浪费生产力重复加工，只能通过科学合理的对数据质量进行控制来达到。然而，最终的数据检查主要分为数据精度检查，数据规范性检查两类。故本文针对土地变更调查多源遥感监测项目，提出在项目进行的各个阶段需要使用标准及科学的数据生产流程，结合阶段性数据检查，来对整体的数据质量进行控制。并提出针对该项目数据各个生产阶段及整体数据的质量建立一个评价体系，将一个项目中庞大的数据成果按照其成果符合质量要求的情况，用一种清楚且明了的评价方法展现，这样就便于更直观的了解数据质量情况。为此，本文开展了以下工作： 1）在生产过程中实验多种方法，设计出分别针对遥感监测项目中的四个阶段（数据接收阶段、影像制作阶段、遥感目视解译阶段、数据整理阶段）的标准化生产流程，使生产效率更高，生产出的数据质量更高，返工率更低。 2）通过研究数据质量控制的相关方法，针对土地变更调查多源遥感监测项目的各个阶段及整体设计合理的数据质量检查方法。在生产过程中的分阶段成果产生处，设置针对该阶段数据特征的数据质量检查方法。在整个项目完成之后设置针对整体数据特征的质量检查方法。 3）对已有的数据质量评价体系进行研究，以此为基础推导出针对数据生产的各个阶段及整体所产生数据的数据特征，设计一套简单合理的数据质量评价体系结构，，以及建立质量评价模型。从这一体系中可直观的看到各个阶段及整体完成的数据质量情况。
[Abstract]:Data quality is the key to ensure the value of the data produced by the project and one of the basic attributes of the data.If the data quality is unknown, it cannot be used, nor can the database be built and shared on a large scale.Therefore, after the completion of production, spatial data must be checked and accepted, and the quality of the data should be identified, which can provide quality assurance for the later use of the data.As a national large-scale project, the data produced in the remote sensing monitoring stage is the basis of the change survey, data statistics, results acceptance and so on after the project can be carried out smoothly.Therefore, it is very important for the accuracy of the updated data in the whole state-owned land change to ensure the quality of the production data in the stage of remote sensing monitoring.In order to ensure that the result data of the remote sensing monitoring project should meet the necessary quality requirements and cannot waste the productivity of repeated processing, it can only be achieved through the scientific and reasonable control of the data quality.However, the final data check is divided into two types: data precision check and data normative check.Therefore, in view of the multi-source remote sensing monitoring project of land change investigation, this paper puts forward that the standard and scientific data production flow should be used in each stage of the project, combined with periodic data inspection, to control the overall data quality.An evaluation system is proposed to evaluate the quality of each production stage and the whole data of the project data. The huge data results in a project are displayed by a clear and clear evaluation method according to the condition that the results meet the quality requirements.This will facilitate a more intuitive understanding of data quality.To this end, the following work has been carried out:1) in the process of production, the standardized production flow is designed for the four stages of remote sensing monitoring project (data receiving stage, image making stage, remote sensing visual interpretation stage, data sorting stage).Higher production efficiency, higher data quality and lower rework rate.2) by studying the relevant methods of data quality control, a reasonable data quality inspection method is designed for each stage and whole of multi-source remote sensing monitoring project of land change investigation.The data quality checking method is set up for the stage data characteristics at the place where the stage results are generated.Set up a quality check method for overall data characteristics after the completion of the project.3) the existing data quality evaluation system is studied, based on which the data characteristics of each stage of data production and the whole data are deduced, and a set of simple and reasonable data quality evaluation system structure is designed.And establish the quality evaluation model.From this system, the data quality of each stage and whole can be seen intuitively.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：P237;P271

【参考文献】