ENGLISH

10卷/3期

10卷/3期

華藝線上圖書館

Pages:

225-238

論文名稱

應用空間排列法於都市土地利用判釋之研究

Title

Spatial Arrangement Algorithm Applied on Urban Land Use Identification Study

作者

周天穎,郭靜怡

Author

Tien-Yin Chou,Ching-Yi Kuo

中文摘要

都市地區之土地利用類別是由一群複雜的土地覆蓋型態所組成的,本研究運用空間後分類演算法(Spatial Post-Classification Algorithm)以高解析度衛星影像判釋都市土地利用類別,第一階段利用高斯最大概似法將土地覆蓋(land cover)類別分成小型結構物、大型結構物、林地、作物、草地、裸露地、以及水體等七個類別,獲得整體精度92.72%。第二階段,則針對土地覆蓋分類結果進行3*3、5*5、7*7、9*9、11*11、21*21、31*31等不同視窗尺寸之空間後分類處理,將土地使用(land use)分為低密度住宅區、中密度住宅區、工業區、耕地、牧草地、林地、裸露空地、以及水體等八個類別,獲得整體精度可達89.64%。結果顯示在土地使用較複雜及破碎之都市地區,11*11的視窗矩陣最適合進行空間後分類,這代表此視窗矩陣大小可以涵蓋不同土地利用類別的空間變化,且可將平滑化的程度減至最小。

Abstract

Specific satellite image spectrum can well perform automatically classification for monitoring agricultural land cover, but the obstacle for urban area land use classification application is still under research stage. The fundamental barrier is due to the fact that land use for urban area is composed by several groups of complex land cover types which reflect differently from any single land cover. Traditional pixel based classification assign each pixel a certain land cover type from its spectrum reflectance value and through statistical analysis. The process ignores neighboring relationship between each pixel spectrum reflectance which cause the main reason for poor land use classification for urban area. This study applied Spatial Post Classification Algorithm on high resolution satellite image for urban land use classification. The classification can be disaggregated into two stages, the first stage is standard per pixel based classification. At this stage, the land cover was identified as seven types (large construction, small construction, forest, crop, grass, bare, and water) by Gauss Maximum Likelihood method. The results showed an overall accuracy to 92.7% with 0.91 Kappa value. The second stage applied seven different window matrix sizes (3*3, 5*5, 7*7, 9*9, 11*11, 21*21, and 31*31) as post classification from first stage outcomes. The land use can then be identified as eight types (high density housing, middle density housing, industrial, farm, pasture, forest, open space, and water). The result showed an optimum window matrix size was 11*11 for complicated and fractal urban area land use type classification. This window size can well describe spatial changes of land cover through entire study area, and can minimize smooth effect from large window matrix size. The final land use classification can reach overall accuracy to 89.6% with 0.86 Kappa value.

關鍵字

後分類、都市特徵、高解析度衛星影像

Keywords

Reclassification; Urban Characteristic; High Resolution Satellite Image

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-225-238

Pages:

239-254

論文名稱

利用LAI 及NDVI 預測水稻產量之最佳時期

Title

Determining the Optimal Timing for Using LAI and NDVI to Predict Rice Yield

作者

陳榮坤, 楊純明

Author

Rong-Kuen Chen,Chwen-Ming Yang

中文摘要

本文研究追蹤調查稻株之葉面積指數(LAI)及植被光譜遙測計算之標準差植被指數(NDVI,或稱標準差植生指數)在水稻品種臺農67號 (Oryza sativa L. cv. NG 67)生育過程中的變化,並於收穫時稱取產量,據以分析NDVI 與LAI 之關係,同時探討利用此二種參數預測產量之最佳時期。其中NDVI係由近地面量測之水稻植被反射光譜中,經由動態篩檢紅光波段(640-740 nm)最低點及近紅外光波段(740-2300 nm)最高點之反射比計算。田間水稻栽培係在位於臺中縣霧峰鄉之行政院農業委員會農業試驗所農場進行,包括2001年及2002年之兩期稻作,藉由施用不等量氮肥來產生不同的LAI、NDVI及產量。根據試驗結果,發現一、二稻作之氣象環境明顯有別,而一期稻作之生長表現及產量均優於二期稻作者。LAI與NDVI在全生育期間皆呈現凸形曲線走向,其最大值在一期作約出現於抽穗前,在二期作則在抽穗前後。NDVI與LAI之關係為一指數函數,由此函數關係連結了光譜遙測資料與生長數據。產量與LAI 之關係乃為曲線函數,於移植後50天起兩者即達顯著之相關,決定係數(determining factor, R2)高於0.73 (P<0.01)。經計算不同期間之累積與平均LAI數值,分析其等與產量之關係,發現無論係累積LAI或平均LAI,抽穗前15天至抽穗後15天為預測一期稻作之最佳時期,抽穗前15天至抽穗後10天則為預測二期稻作之最佳時期。本文研究結果建立起利用LAI直接預測水稻產量及NDVI間接預測產量之機制,開拓了以光譜遙測資訊預測水稻生產的用途。

Abstract

Changes in normalized difference vegetation index (NDVI), which calculated from ground-based canopy hyperspectral reflectance data, and leaf area index (LAI), which measured at the time of spectral measurements, were monitored during rice (Oryza sativa L. cv. TNG 67) growth and yields were harvested at maturity so as to determine the NDVI-LAI relationships and the optimal timing to use these two parameters for yield prediction. Field experiments were conducted at the experimental farm of Taiwan Agricultural Research Institute (Wufeng, Taiwan) in the first and the second cropping seasons of 2001-2002. Different levels of nitrogen fertilizer, from 0 to 180 kg ha-1 with 30 kg ha-1 intervals, were applied to produce various scales of grain yield and values of LAI and NDVI. Results showed that there were differential weather conditions between two cropping seasons, and plants grown in first crops had a better growth and yield. Both LAI and NDVI were found curvilinearly distributed during the growing periods, with the maximum values occurred before heading in First Crops and near or after heading in Second Crops. These two parameters can be mutually estimated through an exponential function, which linked spectral remote sensing data with plant growth information. Correlation between yield and LAI was best fitted to a nonlinear function, from about 50 days after transplanting (DAT) with the determining factor (R2) higher than 0.73 (P<0.01). By further analyzing the relations of the cumulative and the mean values of LAI to yield, it indicated that both the accumulated and the mean values of LAI from 15 days before heading (DBH) to 15 days after heading (DAH) can well predict rice yield for the first cropping seasons, while values calculated from 15 BH to 10 DAH can predict yield for the second cropping seasons.

關鍵字

水稻、葉面積指數、標準差植被指數、產量預測、最佳時期

Keywords

Rice, LAI, NDVI, Yield prediction, Optimal timing.

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-239-254

Pages:

255-264

論文名稱

利用卡爾曼濾波與區段技術擷取與偵測鋪面裂縫

Title

Using Kalman Filtering and Segmentation Techniques to Capture and Detect Cracks in Pavement

作者

許峻榕,陳繼藩

Author

C. J. Hsu,C. F. Chen

中文摘要

本研究利用車載CCD攝影機垂直於地面擷取影像,透過電腦連線即時擷取鋪面資料,CCD攝影機本身固定每秒擷取10~30幅不等數位影像,車載設備在行駛過程中,由於速度過快或過慢的影響,易造成數位影像資料重複記錄或無法連續等問題,故使用差分全球定位系統(DGPS)與車輪計數器(odometer)設備,並結合卡爾曼濾波(Kalman Filtering)來輔助CCD攝影機地面影像的擷取,來改善上述的問題。在鋪面影像裂縫偵測部分,大部分地面影像擷取多半在夜晚進行,由於光源照射的不均勻情況下,所擷取的地面影像在影像處理上易造成失敗,故必須將影像照度不均勻進行補償動作,本研究使用二次多項式配合最小二乘法來補償光源反射不均問題,然後使用區段法(Segmentation)之模糊墒(FuzzyEntropy)原理找出裂縫與背景之影像門檻值,然後進行二元化處理,最後使用物件標示法(Object Labeling)方式將鋪面裂縫影像中的裂縫與以物件化,最後由影像的物件形狀來辨別裂縫種類與大小,並可濾除影像上的雜訊,最後將上述的理論進行測試與驗證,最後討論其成果與未來展望。

Abstract

For this study we used a CCD video camera to capture the pavement image information via the computer. During investigation processing, the CCD video camera captured 10~30 images per second. If the vehicle velocity is too fast, the collected images will be duplicated and if the velocity is too slow there will be a gapped between images. Therefore, in order to control the efficiency of the image grabber we should add accessory tools such as the Differential Global Positioning System (DGPS) and odometer. Furthermore, Kalman Filtering can also solve these problems. After the CCD video camera captured the pavement images, we used the Least-Squares method to eliminate images of gradation which have non-uniform surfaces due to the illumination at night. The Fuzzy Entropy method calculates images of threshold segments and creates binary images. Finally, the Object Labeling algorithm finds objects that are cracks or noises from the binary image based on volume pixels of the object. We used these algorithms and tested them, also providing some discussion and suggestions.

關鍵字

卡爾曼濾波、最小二乘法、區段、模糊墒、物件標示法

Keywords

Kalman Filtering, Least-Squares, Segmentation, Fuzzy Entropy

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-255-264

Pages:

265-274

論文名稱

利用IKONOS 立體影像進行數值地表模型重建之研究

Title

DSM Generation from IKONOS Stereo Imagery

作者

饒見有,陳良健

Author

Jiann-Yeou RAU,Liang-Chien CHEN

中文摘要

利用IKONOS衛星立體影像重建數值地表模型在航測領域中為一具有挑戰性的研究,尤其是當衛星公司未提供原始衛星影像、衛星軌道參數與其他輔助資料時,欲進行軌道定位便具有相當的困難度。IKONOS衛星公司所提的立體像對,已經經過初步幾何改正成為準核影像幾何模式。也就是說兩張影像套疊後,在影像橫軸方向仍存在著地形之高差移位視差量。由於此種幾何前處理的結果,已經不適合採用嚴密軌道求解方式來獲取軌道方位參數。基於此種原因,本文提出利用IKONOS 衛星視野角很小的特性,將其攝像過程視為平行投影,同時利用衛星詮釋資料中之方位角與仰角等資訊,來修正控制點高差移位量,再配合線性幾何轉換來進行定位。影像匹配是採用多重解析度區域影像匹配技術來完成共軛點之搜尋,接著再利用三角幾何關係進行前方交會得到地面點三維空間座標,也就是數值地表模型。經過實際資料測試後,本文所採用之方法在幾何定位方面其均方根誤差可小於兩公尺,說明了應用平行投影的概念在利用IKONOS立體影像製作數值地表模型上,具有相當高的潛在精度。

Abstract

Digital surface model generation from IKONOS stereo imagery is a new challenge in photogrammetric community, especially when the satellite company does not provide the raw data as well as their ancillary data. The IKONOS stereo images are provided in a quasi-epipolar geometry reference where only the terrain parallax in the scanner direction remains. A rigorous solution for orbit modeling is not practical. In this paper we utilized an estimated relief displacement azimuth and the nominal collection elevation data included in the metadata file to correct the relief displacement of GCPs, together with a linear transformation for geometric modeling of IKONOS imagery. Conjugate point correspondence problem is solved by a multi-resolution template-based image matching technique. Space intersection is performed by the trigonometric intersection assuming a parallel projection of IKONOS imagery due to its small FOV and frame size. In the experiment, less than 2-meters of RMSE is achieved denoting the potential positioning accuracy of the IKONOS stereo imagery.

關鍵字

軌道定位、數值地表模型、影像匹配

Keywords

Orbit Modeling, Digital Surface Model, and Image Matching

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-265-274

Pages:

275-286

論文名稱

利用GPS 觀測重建三維大氣濕折射度結構

Title

Reconstruction of 3-D Wet Refractivity Structure of the Troposphere Using Simulated GPS Measurements

作者

黃成勇,劉說安,江振慶,林祐任

Author

Cheng-Yung Huang, Yuei-An Liou, Chen-Ching Chiang, Yu-Jen Lin

中文摘要

同化GPS觀測的濕折射度於數值氣象模式中,具有改善氣象預報的潛在助益。地面GPS接收器接收來自四面八方的GPS衛星訊號,當接收器數量夠多的時候,這些訊號交錯形成一個網狀的構造,提供求取網格點的變數值資訊,這樣的觀測一般稱為斷層掃描技術。本研究中,我們以多波道微波輻射計的觀測資料,建構一個大氣環境做模擬並做為參考值(真值),應用新發展的GPS斷層掃描求解技術,重建大氣濕折射度分佈。折射度為壓力、溫度及水氣的函數,而濕折射度為溫度及水氣的函數。研究中假設在一個長、寬各16公里的等高區域內,每隔4公里的長、寬距離,架設一個GPS接收器,共架設5*5=25個GPS接收器。此外,在模擬區域內,將所要研究十公里高度的大氣層切割成十等分或每隔一公里一等份,即在275(5*5*11)網格點內形成4*4*10=160個立體空間,最後利用經過每個立體空間的GPS衛星訊號,以斷層掃描技術重建大氣濕折射度三維分佈,再以真值做驗證。求解的三維濕折射度在3-5km以下,誤差僅5-10%。在引進地面氣象觀測為約制定及假設高空濕折射度為零的情況下,該誤差可以再降低。此外,我們也求解PODP值來協助結果分析。

Abstract

It is potentially helpful to improve the weather forecasting through assimilating the atmospheric wet refractivity measured with Global Positioning System (GPS) into numerical weather prediction models. In this paper, a tomographic method is developed to reconstruct the 3D wet refractivity structures of the troposphere using ground-based GPS measured slant delay based on an observing system simulation experiment (OSSE)-type approach. The slant delay is derived from a reference atmospheric temperature, pressure, and water vapor profiles (or “ground truth”) measured by a multichannel microwave radiometer, which subsequently serve as reference for comparison with the reconstructed 3D wet delay distribution. The reconstruction is possible because a ground network of many GPS receivers that record integrated slant water along the ray paths of the electromagnetic waves provide the required information. In the simulation, a network with 5 by 5 GPS receivers is uniformly distributed. Distance between two conses (5 by 5 by 11 unknown points). The GPS signals that pass through the 160 cubes intersect all over during a certain time interval of interest, and permit the reconstruction. The relative errors of the reconstructed wet refractivity can be as low as 5 to 10% below 3-5 km altitude compared with the ground truth. They can be further decreased when surface meteorological measurements and an assumption of null refractivity at a reasonable height are applied as constraints. In addition, positional dilution of precision (PDOP) factors is computed to assist in the analysis of the results.

關鍵字

全球定位系統、斷層掃描、濕折射度

Keywords

GPS, Tomography, Wet Refractivity

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-275-286

Pages:

287-298

論文名稱

空載干涉雷達系統高解析度數位高程模型精度評估

Title

Accuracy Assessment of High Resolution Digital Elevation Model Derived from Airborne InSAR System

作者

王志添,陳錕山,饒見有,施盈萱,陳哲俊

Author

C. T. Wang,K. S. Chen, J. Y. Rau, Joy Shih,A. J. Chen

中文摘要

本文評估以空載雷達系統於台灣西南區域實施干涉雷達量測獲取高解析度雷達影像資料與數位高程資料之幾何精度。實驗區涵蓋嘉義、台南、高雄、屏東等縣市,約3676平方公里。資料經處理後得解析力為1.25公尺之正射化雷達影像及網格大小為5 公尺之數位高程模型。經以內政部公佈基本控制測量成果資料之一、二等水準點資料共292點檢測干涉雷達量測高程後,發現其均方差為1.5公尺,系統偏差值為0.6公尺。誤差來源係因三角點高程為GPS樁位高程,雷達獲取高程為GPS 樁位附近地表平均高程差異。經以水位深度模擬高屏溪口附近低漥地區,與2001年7月5日颱風後獲取之RADARSAT-1影像測得溢淹區域之成果與以上結論一致,說明此一高效率、高解析與高精度數位高程模型符合環境監測實務應用之需求。

Abstract

This paper presents accuracy assessment of InSAR derived DEM acquired by Intermap’s IFSAR system. The flight area was located southwestern Taiwan covering counties of Chiayi, Tainan, Kaohsiung and Pingtung with about 3676 squared km mapping size. The output data included ortho-rectified radar image at 1.25 m resolution and digital elevation model at 5 meter posting. We compared the DEM with 292 ground control points provided by Satellite Survey Center, Department of Land Administration, MOI. It was found that the height difference standard deviation was around 1.5 m and the bias was 0.6 m. In this experiment campaign, the accuracy obtained from InSAR derived is highly acceptable for many applications. The error sources were attributed to the difference between the use of GPS point height and InSAR area (averaged over 5 squared meters) height. The relation of height difference to aspect and slope illustrated that there exist weak dependence of terrain effects. For purpose of demonstration, we overlaid the flooded area derived from RADARSAT-1 with DEM at fine and coarse resolution to illustrate the importance of high resolution DEM data in assessing the flood risk.

關鍵字

干涉雷達、數位高程模型

Keywords

Interferometric SAR, Digital Elevation Model

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-287-298

Pages:

299-304

論文名稱

「科技短文」應用類神經網路於SPOT 自然色影像之產生

Title

The Generation of SPOT True Color Image Using Neural Network Algorithm

作者

陳繼藩,黃誌勇

Author

Chi-Farn Chen,Chih-Yung Huang

中文摘要

衛星影像具有大範圍、重複觀測等優點,因此愈來愈多資源監測工作逐漸以衛星影像來作業。資源監測工作中,判釋與顯圖是很重要的,而目前使用範圍甚廣的SPOT衛星在色彩上卻只能呈現假色的影像,無法呈現出人眼所熟悉的自然色影像。本研究目的是將SPOT假色影像轉換為自然色的影像,使用的方法為倒傳遞神經網路的演算法,而測試資料則使用Landsat及SPOT影像。測試結果顯示在目視上SPOT所呈現的色調與顏色皆與Landsat 自然色很近似,同時以統計相似性進行評估及檢核,獲得相關係數皆大於0.9的結果。此研究顯示以類神經網路產生SPOT自然色影像確實可行,其結果將有助於提升SPOT影像於展示及判釋的應用。

Abstract

Satellite images are advantageous to large-area and repetitive observation, and therefore, are gradually adopted in the tasks of resource monitoring. Their analysis and presentation for the present are important to resource monitoring, but the most widely used SPOT satellite images can only show the image of false color, not the true color that is familiar to human eyes. In an attempt to enhance the visual effect of SPOT image, this study develops a neural network algorithm to transform SPOT false color into simulated true color. The method has been tested using Landsat TM and SPOT images. The qualitative and quantitative comparisons indicate that the striking similarity can be found between the true and simulated true images in terms of the visual looks and the statistical analysis.

關鍵字

自然色影像、假色影像、類神經網路

Keywords

True color image, False color image, Neural Network

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-299-304

Pages:

305-314

論文名稱

「科技短文」以小波理論進行影像壓縮之三種實現比較

Title

The Comparison of Three Wavelet Based Image Compression Implementations

作者

吳鴻謙,史天元,劉榮寬

Author

Houn-Chien Wu,Tian-Yuan Shih,Jung-kuan Liu

中文摘要

小波理論可提供高倍數之影像壓縮,除了JPEG2000格式外,尚有多種商業軟體採用小波理論進行影像壓縮。本研究採用JPEG2000之參考軟體Jasper,與兩種商業軟體LuraWave及ECW,以一幅民國九十年在竹北地區所拍攝的五千分之一的黑白航空影像及一幅彩色風景影像進行影像壓縮品質之探討。本研究之目的不在於檢驗何種格式或軟體優於其他,而在以有限之樣本探討此三種格式之不同,並進而建立一品質檢驗之程序,提供不同影像之使用者之參考。

Abstract

Wavelet based image compression techniques can provide high compression ratio with high fidelity. Besides the JPEG2000 format, there are also several commercial software for image compression which are based on the wavelet theory. This study investigates the performance of Jasper, the reference software of JPEG2000, and two commercial software, LuraWave and ECW, with a scanned grey-scale aerial photograph and a color image. The objective of this study is not to determine which software or format is better than the others, but to visualize the difference between different formats which are all based on the wavelet theory. With the study on limited samples, this study hopes to establish an evaluation scheme for the image compression utilities.

關鍵字

小波轉換

Keywords

Wavelet Transform

附件檔名

華芸線上圖書館

N / A

備註說明

200509-10-3-305-314

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