本文選題：生態(tài)地理分區(qū) + 知識(shí)庫(kù)　； 參考：《北京建筑大學(xué)》2017年碩士論文

【摘要】：隨著人工智能的不斷發(fā)展,知識(shí)庫(kù)和專(zhuān)家系統(tǒng)被逐漸引入到遙感領(lǐng)域中,尤其是針對(duì)遙感目標(biāo)地物的識(shí)別和分類(lèi)。當(dāng)前地表覆蓋變化檢測(cè)多是從基于像素級(jí)別的遙感影像,當(dāng)面對(duì)全球范圍內(nèi)復(fù)雜多樣的地類(lèi),會(huì)存在大量同物異譜和異物同譜的現(xiàn)象,同時(shí)由于物候原因,在變化檢測(cè)的過(guò)程中都會(huì)存在大量的偽變化。想要得到高精度的變化檢測(cè)結(jié)果,要對(duì)檢測(cè)后的變化圖斑進(jìn)行偽變化識(shí)別與剔除。目前變化檢測(cè)后的偽變化一般是利用人工來(lái)識(shí)別,不僅浪費(fèi)時(shí)間、耗費(fèi)大量資源,而且由于識(shí)別人員知識(shí)的儲(chǔ)備不足很容易造成錯(cuò)判。因此,急需建立一個(gè)地類(lèi)知識(shí)庫(kù),用來(lái)自動(dòng)識(shí)別變化檢測(cè)后的偽變化。全球生態(tài)地理分區(qū)由于其全球性、分區(qū)地類(lèi)穩(wěn)定性、地物變化規(guī)律性和信息量大等特點(diǎn),可以用來(lái)構(gòu)建知識(shí)庫(kù)輔助變化檢測(cè)。本文針對(duì)以往遙感影像變化檢測(cè)存在的問(wèn)題,提出了一種基于生態(tài)地理知識(shí)庫(kù)來(lái)實(shí)現(xiàn)偽變化識(shí)別的方法,并從知識(shí)庫(kù)的結(jié)構(gòu)、內(nèi)容設(shè)計(jì),知識(shí)的表達(dá)入庫(kù),再到知識(shí)庫(kù)管理系統(tǒng)的建立,最后設(shè)計(jì)了生態(tài)去偽插件,實(shí)現(xiàn)了利用規(guī)則庫(kù)中的規(guī)則識(shí)別偽變化,完成了整個(gè)去偽流程的結(jié)構(gòu)設(shè)計(jì)和功能實(shí)現(xiàn)。首先,設(shè)計(jì)并構(gòu)建了包括分區(qū)偽變化規(guī)則庫(kù)、地表覆蓋變化規(guī)則庫(kù)和專(zhuān)題資料庫(kù)在內(nèi)的生態(tài)地理分區(qū)知識(shí)庫(kù),并對(duì)知識(shí)庫(kù)中的偽變化規(guī)則做了部分示例,其中對(duì)生態(tài)分區(qū)偽規(guī)則庫(kù)采用面向?qū)ο蟮姆椒ㄟM(jìn)行設(shè)計(jì),有效的實(shí)現(xiàn)了規(guī)則類(lèi)之間的繼承,提高了偽變化識(shí)別的推理效率。其次,利用對(duì)象關(guān)系型數(shù)據(jù)庫(kù)PostgreSQL對(duì)知識(shí)庫(kù)采用數(shù)據(jù)庫(kù)的形式存儲(chǔ),并采用C#語(yǔ)言和ArcEngine開(kāi)發(fā)了生態(tài)地理分區(qū)知識(shí)庫(kù)管理系統(tǒng)。最后,建立生態(tài)去偽插件實(shí)現(xiàn)了利用知識(shí)庫(kù)中的規(guī)則識(shí)別偽變化,并選取北京市和杰克遜市兩個(gè)實(shí)驗(yàn)區(qū)對(duì)剔除偽變化后的變化圖斑做了精度驗(yàn)證。結(jié)果表明,利用生態(tài)地理分區(qū)知識(shí)庫(kù)來(lái)進(jìn)行偽變化的識(shí)別不僅提高了自動(dòng)化程度,而且提高了變化檢測(cè)的精度。
[Abstract]:With the development of artificial intelligence, knowledge base and expert system are gradually introduced into the field of remote sensing, especially for the recognition and classification of remote sensing objects.At present, the detection of surface cover change is mostly based on pixel level remote sensing images. In the face of complex and diverse ground species in the global scope, there will be a large number of isospectral and foreign body isospectral phenomena, at the same time, due to phenological reasons,In the process of change detection, there will be a large number of pseudo changes.In order to obtain high precision change detection results, the change pattern after detection should be identified and eliminated.At present, the pseudo-change after change detection is usually identified by manual, which not only wastes time and consumes a lot of resources, but also easily leads to misjudgment because of the lack of knowledge of recognizer.Therefore, there is an urgent need to establish a knowledge base for automatic identification of pseudo changes after change detection.The global ecogeographic zoning can be used to construct a knowledge base for aided change detection because of its global, regional stability, the regularity of ground object change and the large amount of information.In this paper, aiming at the existing problems of remote sensing image change detection in the past, a method based on ecological geographical knowledge base is put forward to realize the identification of pseudo change, and the structure of knowledge base, the content design and the representation of knowledge are put into database.Then to the establishment of the knowledge base management system, finally designed the ecological de-counterfeiting plug-in, using the rules in the rule base to identify the pseudo changes, completed the structure design and functional implementation of the whole de-counterfeiting process.First of all, the paper designs and constructs the knowledge base of ecological geography partition including partition pseudo-change rule base, surface cover change rule base and thematic database, and makes some examples of pseudo-change rule in knowledge base.Among them, the object oriented method is used to design the pseudo-rule base of ecological partition, which effectively realizes the inheritance between rule classes and improves the reasoning efficiency of pseudo-change recognition.Secondly, the object relational database (PostgreSQL) is used to store the knowledge base in the form of database, and the ecological geographical partition knowledge base management system is developed by using C # language and ArcEngine.Finally, the ecological de-counterfeiting plug-in is established to recognize the pseudo-change by using the rules in the knowledge base, and two experimental areas of Beijing and Jackson are selected to verify the accuracy of the change pattern after eliminating the pseudo-change.The results show that the recognition of pseudo-change by using the knowledge base of ecogeographic partition not only improves the degree of automation but also improves the accuracy of change detection.
【學(xué)位授予單位】：北京建筑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：P237

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