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MAPPING AND RECOVERING CLOUD-CONTAMINATED AREA IN MULTISPECTRAL SATELLITE IMAGERY WITH VISIBLE AND NEAR-INFRARED BANDS
No full textDeveloping a technique for the detection and removal of cloud and haze in remote sensing images
No full text遙測技術發展的最大限制之一，便是大氣活動的干擾，尤其對地球資源衛星上裝載可見光段的光學感測器而言，雲霧的干擾最不易處理。而台灣又為多雲區，雲霧的干擾無可避免，若受遮蔽的區域恰為研究區，則會大大減低了衛星影像的價值性。另外，國內災害監測對遙測影像之需求週期幾乎以「天」為單位，更突顯災害發生時遙測影像供不應求之窘境。因此如何去除雲霧之干擾便成為相當重要的課題。本研究即針對上述課題，發展雲霧的偵測及影像鑲嵌之技術。
厚、薄雲霧兩者具有不同之光譜特性，故需個別進行處理。厚雲霧因具高反射特性，故可經由閾值的設定將可見光段呈高反射之部分偵測並去除；薄雲霧雖仍可觀測到底下地物，但已將地物本身的光譜特性扭曲，且難以用演算法偵測去除，因此本研究先將影像由RGB轉換成HIS系統，再假設薄雲霧的加入等於使影像加入白色，即R、G、B三者提高，因此僅改變光譜的亮度或飽和度值，色相並無改變，藉此可偵測並去除薄雲霧。去除厚薄雲霧後殘缺之部分再利用影像鑲嵌之方式，以鄰近日期之無雲影像補償之，並進行色差之調整，使影像資訊量損失到最小。
對於雲霧偵測之結果，本研究以專家法之方式進行檢核。結果厚雲霧部分之總體精度可達97％；在均質海面及有地形效應之區域上，薄雲霧偵測精度約為83％；極度非均質之農業區則降為80％。地物較複雜之區域，需取得較高時間精度之影像才可增加偵測精度。本研究雖因影像取得之限制而無法提升複雜區域之精度，但已證明在HIS系統中可簡化薄雲霧之偵測準則，大大提升自動化偵測雲霧之可能性。Detection and removal of cloud and haze are arduous problems in optical remote sensing imagery processing. Thick cloud and haze have the character of high reflection, so we can set the threshold to detect and remove the areas having extremely high reflection and even mosaic the images with near dates’ ones to create clear and cloudless images. Relatively, areas covered by thin cloud and haze have the spectral characteristics of both surface features and cloud and haze, thus making it difficult to separate them.
This research first processed the images with relative radiometric normalization and then transformed the images from the RGB to the HIS color model. Our assumption was that the interference of thin cloud and haze, similar to mixing a color pigment with white, would increase the color intensity and decrease the saturation of an image but would not change its hue value. Guided by this assumption, we processed the multi-temporal images and isolated areas contaminated by thin cloud and haze. The results thus suggest that an automatic method based on the HIS color model is possible for detecting thin cloud and haze on satellite images.中文摘要 I
英文摘要 II
目錄 IV
圖目錄 V
表目錄 IX
第1章 緒論 1
第一節 研究動機 1
第二節 研究目的 3
第2章 文獻回顧 7
第一節 雲霧的偵測與去除 7
第二節 RGB和HIS彩色模型間之轉換及應用 23
第三節 相對性輻射校正 28
第3章 研究方法 31
第一節 研究架構及流程 31
第二節 研究方法 33
第4章 成果與討論 50
第一節 厚雲霧之偵測及去除 50
第二節 薄雲霧之偵測及去除 54
第5章 結論與未來研究 68
第一節 結論 68
第二節 未來研究 71
參考文獻 74
附錄一 雲霧處理及誤差評估之SML語法 78
附錄二 各專家判釋雲霧之差異比較表 8
The Study on Cloud Processing in Optical Satellite Imagery
No full text在利用光學式衛星影像進行土地利用判釋或農作物產量估測時，雲層覆蓋是無法避免的干擾之一。以往研究的瓶頸在於多數去雲流程皆需要另外的無雲參考區域或是多時期影像，然而真實世界中，這些參考資訊可能難以取得；再者，對於去雲結果的優劣，通常是以質化而非量化的方式來進行視覺化評估，因此欠缺客觀性；最重要的是，去雲過程通常也會破壞原本的地物資訊，然而去雲後影像能否用來進行自動化地物判釋也欠缺探討。
為解決以上瓶頸，降低雲層的影響並提升地物判釋的正確性，就單時期具有厚雲層的影像而言，本研究以標準差延伸加強 (standard deviation stretch enhancement) 進行影像處理，再以區域增長 (region growing) 之方式偵測並切除無法還原地物資訊的厚雲層。單時期具有薄雲的影像則以傅利葉 (Fourier) 分析建立薄雲的數學模式，再以此模型薄雲並還原薄雲底下的地物光譜資訊，雖然傅利葉分析的方法在模式建立階段仍需兩時期影像，但建立後的模式在對其它影像進行去雲處理時則僅需單時期資訊。而去雲結果的量化評估，厚雲方面以專家法評估偵測去除的範圍準確性，薄雲方面則以影像分類法以及常態化差異植被指數 (normalized difference vegetation index, NDVI) 評估雲下地物資訊還原的程度以及非雲下地物資訊的被破壞程度。
本研究證明了僅以綠、紅、近紅外波段且沒有無雲參考區或參考影像時，對於厚雲偵測來說資訊量是足夠的，在不同特性的研究區，整體精度皆可達到90%以上。而對薄雲去除而言，三個波段在視覺上能達到一些改善的效果，對於地物光譜資訊還原方面，就全幅影像來探討，薄雲過濾器提升了約4%的分類精度，而就各分區來探討，過濾器對雲區的分類精度提升最多，達到了6%，無雲無影區亦有少許提升，影區的分類精度則反而下降，雖然薄雲過濾器無法全面提升影像各區之分類精度，然而其去雲的功效已有發揮。而薄雲過濾器也減輕了薄雲對NDVI值的影響，使其接近無雲狀態下的地物光譜資訊。總體來看，薄雲過濾器對影像分類以及NDVI值的改善程度而言在統計上有達到顯著性 (p < 0.01)。本研究之成果可應用在土地利用判釋和農作物產量估測中的影像前處理程序，除能減少人工判釋和去除雲層的人力，也可增加衛星影像的利用度。Cloud cover is an inevitable interference when mapping land use/cover with optical satellite imagery. In this study, we apply region growing processing to delineate unrecoverable thick cloud and use Fourier analysis to recover ground information from hazy areas with single temporal imagery.
Several methodologies across literature successfully solve cloud problems, but most methods require additional cloud-free reference areas or imagery, which may be unavailable in the real world. Moreover, visual methods rather than quantitative methods are used for assessing results, which can be subjective and arbitrary. Most importantly, the feasibility of applying haze-off imagery to image classification is seldom discussed.
To overcome the existing limits, expert method is applied to assess the thick cloud delineation and image classification and normalized difference vegetation index (NDVI) is used to evaluate the recovery degree of ground information after the haze-off processing for quantitative verification of the results. This study revises the image enhancement and region growing algorithm to delineate unrecoverable thick cloud. Accuracy assessment shows the overall accuracy of delineation could be 90% above in each study area. For hazy areas, Fourier analysis is used to reduce haze interference and recover ground information. The proposed haze filter increases the overall accuracy of the whole scenes by about 4%. The overall accuracy of hazy areas in the imagery increases the most (by 6%), while that of shadow areas decreased slightly. The influence of haze on NDVI is also reduced with statistical significance (p < 0.01). Both thick cloud and hazy areas processing can be achieved with no cloud-free area or reference imagery required. Future applications include preprocessing of satellite imagery in land use/cover mapping, which can decrease the manpower to interpret and remove cloud areas and increase the usability of the satellite imagery
INTEGRATING REMOTE SENSING, SPATIAL ANALYSIS AND CERTAINTY FACTOR MODEL FOR WASTE DUMPING RISK ASSESSMENT
No full textMapping and Recovering Cloud-contaminated Area in Optical Satellite Imagery
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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