本文選題：水體信息提取　切入點：歸一化差異植被指數　出處：《華南農業(yè)大學》2016年碩士論文

【摘要】：隨著經濟的快速發(fā)展,城市化、工業(yè)化對水體、水系污染的環(huán)境問題越來越突出,嚴重威脅著社會可持續(xù)發(fā)展。水體信息的準確獲取對水資源調查、河流綜合治理、水利規(guī)劃、洪澇旱災監(jiān)測以及災害評估等領域具有重要意義。從衛(wèi)星遙感影像中快速準確地提取水體信息已成為眾多水資源調查與監(jiān)測的一種重要手段。但目前已有方法中,對一些背景地物較為復雜繁多的地區(qū)提取水體信息時,單一的提取方法無法有效的抑制非水體地物,從而導致水體提取精度不高。這主要原因是單一的水體提取方法往往只針對一種地物進行抑制,其他容易混淆的地物仍然存在于被提取的結果中。同時,在不同地區(qū)以及不同時期的影像提取水體結果時,往往需要人為地進行閾值的篩選,不利于計算機大范圍,多時相地對影像進行水體提取。如何達到這一目的,正是本文研究的主要內容。本文選取了背景地物較為復雜的珠三角入海口西岸地區(qū)為研究區(qū),同時選取三個不同時相的Landsat TM/ETM+影像作為數據源,在對典型的遙感水體信息提取方法進行深入分析的基礎上,提出一種新的水體信息提取模型----地表水體信息提取漸進增強模型。最后,運用目視判讀及人機交互矢量化解譯的方法對地表水體信息提取漸進增強模型的提取結果與其他典型的遙感水體信息提取結果進行精度評價。從數據的預處理,到地表水體信息提取漸進增強模型的建立展開了一系列的研究工作,主要內容及成果如下:(1)常規(guī)的水體信息提取指數法(歸一化差異植被指數、歸一化差異水體指數、修正歸一化差異水體指數),是利用水體及其他地物在不同波段的光譜差異的特征,從而達到水體提取的目的。但是,歸一化差異植被指數對植被與水體區(qū)分不明顯;歸一化差異水體指數提取的水體容易與建筑物混淆;修正歸一化差異水體指數為三者中最優(yōu),但仍有部分水體信息夾帶著山體陰影,提取結果不夠精確。(2)鑒于以上三種水體信息提取方法存在問題,本文提出遙感地表水體信息提取漸進增強模型。漸進增強模型首先對三個指數(歸一化差異植被指數、歸一化差異水體指數、修正歸一化差異水體指數)進行處理;然后通過閾值設定,逐一隔離出水體信息;再對隔離結果進行二值化處理;最后進一步對三個隔離結果進行增強式的疊加,漸進增強了水體的信息,使水體提取信息達到更高的準確率、更快的提取速度,并解決了三種水體提取方法中存在的問題。(3)通過漸進增強模型與三種常規(guī)方法的比較試驗,結果表明:以陸地三大類水體為試驗對象,在湖泊、魚塘水體試驗中漸進增強模型比三種常規(guī)的方法總體精度提高了13%以上、總體kappa系數提高了0.26以上,在河流水體試驗中增強模型比三種常規(guī)的方法總體精度和總體kappa系數都有所提高。遙感地表水體信息漸進增強模型可應用理論的分割閾值,為海量遙感地表水體信息提取過程的全自動化提供支持。本文使用的TM和ETM空間分辨率較低,混合像元較多,影響水體提取精度,在以后研究中,將考慮混合像元分解來進一步解決此問題。
[Abstract]:With the rapid development of economy, the city, the industrialization of water pollution, water environmental problems are becoming increasingly prominent, a serious threat to the sustainable development of the society. The investigation of water resources to obtain accurate information of water, water conservancy planning comprehensive management of rivers, plays an important role of flood drought monitoring and disaster assessment. From satellite remote sensing images fast accurately extract water body information has become an important means of investigation and monitoring of many water resources. But the existing methods, some of the more complex background area extracting water body information extraction method, a single can not effectively suppress the non ground water, resulting in water extraction accuracy is not high. The main reason is the water the extraction method is often only for a single object to suppress other confusing features still exist in the extracted results. At the same time, in the The water extract the same area as well as images of different periods, often require the screening threshold artificially, is not conducive to a wide range of computer, for water extraction of multitemporal images. How to achieve this goal, it is the main content of this paper. This paper chooses the background features more complex in the Pearl River Delta estuary West Bank as the study area, and selecting three different Landsat TM/ETM+ images as the data source, in-depth analysis based on remote sensing of water typical information extraction methods, proposes a new model to extract the information of water - surface water information extraction model of progressive enhancement. Finally, using visual interpretation and interactive vector solution the method of information extraction model of progressive enhancement of surface water extraction results to evaluate the accuracy and other typical water remote sensing information extraction results from the data. The pretreatment to the surface water information extraction model of progressive enhancement has launched a series of research work, the main contents and results are as follows: (1) water information extraction index method (normalized difference vegetation index, normalized difference water index, modified normalized difference water index), is characterized by water and other objects the spectral differences of different bands, so as to achieve the purpose of water extraction. However, normalized difference vegetation index of vegetation and water is not obvious; normalized difference water index to extract the water easily and building confusion; modified normalized difference water index is the best of the three, but there are still some water information extraction with the shadow of the mountain, the result is not precise enough. (2) in view of the above three kinds of water information extraction method has the problem, in this paper the water information extraction of remote sensing model gradually progressive enhancement. In the first three to enhance the model index (normalized difference vegetation index, normalized difference water index, modified normalized difference water index) for processing; then the threshold set, one by one to isolate the water information; isolation results of binarization processing; finally three isolation results were enhanced superposition, progressive enhancement the water information, the water information extraction to achieve higher accuracy, faster extraction, and solve the problems in existing methods of three kinds of water extraction. (3) through the progressive enhancement test, model and three kinds of conventional methods. The results showed that three kinds of land to water as the test object, in Lake, fish pond water test in progressive enhancement model than the three conventional method improves the overall accuracy by more than 13%, the overall kappa coefficient is improved by more than 0.26 in the water body test in enhanced model than the three General methods for the overall accuracy and kappa coefficient are improved. The overall surface water remote sensing information model of progressive enhancement threshold theory, automatic extraction process to provide support for the remote sensing information of surface water. TM and ETM spatial resolution using low mixed pixels more, affecting the accuracy of extraction of water, in the future in the study, considering the mixed pixel decomposition to solve this problem.

【學位授予單位】：華南農業(yè)大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：P237

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