本文選題：遙感監(jiān)測(cè) + 過(guò)程標(biāo)準(zhǔn)化　； 參考：《成都理工大學(xué)》2013年碩士論文

【摘要】：數(shù)據(jù)質(zhì)量是保證項(xiàng)目所生產(chǎn)出的數(shù)據(jù)具有價(jià)值的關(guān)鍵，是數(shù)據(jù)的基本屬性之一。數(shù)據(jù)質(zhì)量若不明是不能被使用的，更不能構(gòu)建數(shù)據(jù)庫(kù)在大范圍內(nèi)進(jìn)行共享。因此，空間數(shù)據(jù)在生產(chǎn)完成之后都須進(jìn)行質(zhì)量檢查與驗(yàn)收，鑒定數(shù)據(jù)的質(zhì)量，為之后對(duì)該數(shù)據(jù)的使用提供質(zhì)量保證。 土地變更調(diào)查作為一項(xiàng)全國(guó)性的大型項(xiàng)目，其遙感監(jiān)測(cè)階段所生產(chǎn)的數(shù)據(jù)，是這個(gè)項(xiàng)目能否順利進(jìn)行之后的變更調(diào)查、數(shù)據(jù)統(tǒng)計(jì)、成果驗(yàn)收等階段的基礎(chǔ)。故遙感監(jiān)測(cè)階段生產(chǎn)數(shù)據(jù)質(zhì)量是否有保證，對(duì)整個(gè)國(guó)有土地變更所更新數(shù)據(jù)的準(zhǔn)確性，是十分重要的。要保證遙感監(jiān)測(cè)項(xiàng)目的成果數(shù)據(jù)即要達(dá)到必要的質(zhì)量要求，又不能浪費(fèi)生產(chǎn)力重復(fù)加工，只能通過(guò)科學(xué)合理的對(duì)數(shù)據(jù)質(zhì)量進(jìn)行控制來(lái)達(dá)到。然而，最終的數(shù)據(jù)檢查主要分為數(shù)據(jù)精度檢查，數(shù)據(jù)規(guī)范性檢查兩類(lèi)。故本文針對(duì)土地變更調(diào)查多源遙感監(jiān)測(cè)項(xiàng)目，提出在項(xiàng)目進(jìn)行的各個(gè)階段需要使用標(biāo)準(zhǔn)及科學(xué)的數(shù)據(jù)生產(chǎn)流程，結(jié)合階段性數(shù)據(jù)檢查，來(lái)對(duì)整體的數(shù)據(jù)質(zhì)量進(jìn)行控制。并提出針對(duì)該項(xiàng)目數(shù)據(jù)各個(gè)生產(chǎn)階段及整體數(shù)據(jù)的質(zhì)量建立一個(gè)評(píng)價(jià)體系，將一個(gè)項(xiàng)目中龐大的數(shù)據(jù)成果按照其成果符合質(zhì)量要求的情況，用一種清楚且明了的評(píng)價(jià)方法展現(xiàn)，這樣就便于更直觀的了解數(shù)據(jù)質(zhì)量情況。為此，本文開(kāi)展了以下工作： 1）在生產(chǎn)過(guò)程中實(shí)驗(yàn)多種方法，設(shè)計(jì)出分別針對(duì)遙感監(jiān)測(cè)項(xiàng)目中的四個(gè)階段（數(shù)據(jù)接收階段、影像制作階段、遙感目視解譯階段、數(shù)據(jù)整理階段）的標(biāo)準(zhǔn)化生產(chǎn)流程，使生產(chǎn)效率更高，生產(chǎn)出的數(shù)據(jù)質(zhì)量更高，返工率更低。 2）通過(guò)研究數(shù)據(jù)質(zhì)量控制的相關(guān)方法，針對(duì)土地變更調(diào)查多源遙感監(jiān)測(cè)項(xiàng)目的各個(gè)階段及整體設(shè)計(jì)合理的數(shù)據(jù)質(zhì)量檢查方法。在生產(chǎn)過(guò)程中的分階段成果產(chǎn)生處，設(shè)置針對(duì)該階段數(shù)據(jù)特征的數(shù)據(jù)質(zhì)量檢查方法。在整個(gè)項(xiàng)目完成之后設(shè)置針對(duì)整體數(shù)據(jù)特征的質(zhì)量檢查方法。 3）對(duì)已有的數(shù)據(jù)質(zhì)量評(píng)價(jià)體系進(jìn)行研究，以此為基礎(chǔ)推導(dǎo)出針對(duì)數(shù)據(jù)生產(chǎn)的各個(gè)階段及整體所產(chǎn)生數(shù)據(jù)的數(shù)據(jù)特征，設(shè)計(jì)一套簡(jiǎn)單合理的數(shù)據(jù)質(zhì)量評(píng)價(jià)體系結(jié)構(gòu)，，以及建立質(zhì)量評(píng)價(jià)模型。從這一體系中可直觀的看到各個(gè)階段及整體完成的數(shù)據(jù)質(zhì)量情況。
[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.
【學(xué)位授予單位】：成都理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：P237;P271

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