ENGLISH

5卷/4期

5卷/4期

華藝線上圖書館

Pages:

1-22

論文名稱

遙測與GIS結合應用於水稻田辨識

Title

Combined Remote Sensing and GIS Data for Rice Paddy Landuse Interpretation

作者

蕭國鑫 , 劉治中 , 史天元

Author

Kuo-Hsing Hsiao , Chi-Chnung Lau , Tian-Yuan Shih

中文摘要

本研究利用多時SPOT衛星影像,判釋以坵塊為單元的水稻田分佈,進而更新農地坵塊土地利用GIS資料。方法是以鹿港一帶為先期研究區,採用單一時期與多時段組合影像,利用非監督式 (unsupervised)及監督式(supervised)分類方法,藉由逐像元(pixel-by-pixel)及區塊(parcel-based)單元分類方式,以改良式的坵塊網格化資料(網格大小 2.5X2.5m2)對應相對的SPOT影像進行區塊分類。比較水稻田判釋分類優劣後,選擇最佳分類精度與 指標的NDVI指數差值影像之監督式區塊單元分類法,施行彰化地區南、北端兩個地區的測試;證實可行後,再推展到較大範圍同一期水稻的分類判釋。 推廣應用結果,彰化全區1997年二期稻以相同判釋準則分類的全體精度為88.71%, 指標為0.77;考慮生長條件不同,調整北、中、南三區的判釋標準後,全區分類精度為89.01%, 指標為0.78。另以同樣的判釋方法及判釋規則庫設定條件,分析1999年一期稻的水稻分佈後,相同判釋標準的全體精度為85.64%, 指標為0.71;微調北、中、南區判釋區間後,全體精度提昇至86.44%, 指標昇為0.73。因此,結合GIS資料的遙測影像水稻田分類與快速更新農地坵塊GIS資訊,可供實際應用參考。

Abstract

Multi-temporal images and cadastral parcels were combined in a pilot study for detecting rice crops and updating the GIS database of landuse parcels. Both unsupervised and supervised classification scheme in a pixel-by-pixel mode and a parcel-based mode that using a sing1e time or combined multi-temporal images were adopted in Lu-Kang study area. Cadastral parcels were rasterized into a 2.5m grid for the classification. It is shown that the best result was obtained by applying the parcel-based supervised classification with NDVI difference images, evaluated on basis of clssification accuracy and index. Images from two other test areas in Chang-Hwa County are analyzed using this method for verifying the possibilities of adopting common criteria. Results include: (1) A classification accuracy of 88.71 % with 0.77 can be achieved for the 2nd crop period in 1997. An accuracy of 89.01% with 0. 78 was obtained if the interpreted criteria was adjusted according to the growing period of North, Middle, South area of Chang-Hwa. (2) The classification accuracy was 85. 64% with 0.71 for the 1st crop period in 1999 using the same classification method. A improvement of accuracy of 0.8% was obtained by using three different interpreted creteria.

關鍵字

遙測、水稻辨識、植生指數、多時段影像

Keywords

Remote sensing, Rice paddy identification, NDVI, Multi-temporal images

附件檔名

華芸線上圖書館

N / A

備註說明

200012-5-4-1-22

Pages:

23-38

論文名稱

方位參數最佳化於空載SAR影像之應用

Title

Orientation-Parameter Optimization Applied to Airborne SAR Imagery

作者

劉家鈞 , 吳究

Author

Chia-Jun Liu , Joz Wu

中文摘要

本文是以多項式描述時變SAR載具的飛行軌跡,先說明單張SAR影像雷達測量條件式之推導及利用混合平差求解方位參數,再利用 τ 統計檢定之方法,對觀測資料進行錯誤偵測,以確保觀測資料之品質。以往的研究,常以二階多項式描述方位參數,而本文選擇一適當之高階多項式,再利用統計檢定之方法,進行多項式參數數目之最佳化。最後利用檢核點評估經最佳化後載具方位參數之定位精度。檢核成果顯示,平面精度方面約為4.5-5.5m,高程方面約為5.0m,均較二次多項式者有所改善,對於後續影像正射化之精度提升極有幫助。

Abstract

This paper begins with elaborating the deduction and solutions of Radargrammetric Condition Equations on a single SAR (Synthetic Aperture Radar) image, which is the time-varying SAR airborne flight locus represented with polynomial collaborating with the mixed adjustment method. As for the blunder detection in observation data, in order to apply τ -test in detecting the possible blunder in observation data to assure its quality, the orientation parameter used to be described with two-order polynomial in previous researches. In this paper, one appropriate high-order polynomial is chosen in the first place to proceed with the optimization of the orientation parameter originally presented by two-order polynomial. The result of the experiment has shown that the check point precision is 4.5-5.5 meter horizontally and 5.0 meter vertically, which proves to be better than two-order polynomial. This is going to make positive contributions toward the precision promotion in the subsequent researches on geocoding of SAR image.

關鍵字

雷達測量條件、錯誤偵測、參數最佳化、統計檢定

Keywords

Radargrammetric conditions, Blunder detection, Parameter optimization, statistical test

附件檔名

華芸線上圖書館

N / A

備註說明

200012-5-4-23-38

Pages:

39-54

論文名稱

「科技短文」Kodak DCS210數位相機量測特性之探討

Title

An Evaluation for the Metric Properties of Kodak DCS 210 Digital Camera

作者

龔健彬 , 史天元

Author

Chien-Bin Kung , Tian-Yuan Shih

中文摘要

本研究使用設立於新竹市交通大學光復校區內一建築物之外部檢驗場,檢驗Kodak DCS210數位相機量測特性,以為應用該類相機進行攝影測量之參考。檢驗場之控制點為在建築物上選取之自然點位,各點位之三維坐標以全測站經緯儀量測獲得,各點坐標值之精度根據推估應在1cm以內。在使用合適模式時,DCS210率定之像面坐標精度可以達到次像元等級(0.15 pixel),物間相對精度可達平均物距之1/330。鏡頭畸變差方面,短焦距較長焦距為大,而且畸變差之量均甚大,其量級達數像元。

Abstract

A Kodak DCS210 digital camera is calibrated with the test field established in the exterior of a building in National Chiao-Tung University, Hsin-Chu. The three dimensional coordinates of 79 points located on the building are measured with a total station. The accuracy of the coordinates is within 1 cm. All these points are chosen from the corner or the intersection of edges. The experiments indicate that the sub-pixel level accuracy (0.15 pixel) can be achieved with proper mathematical modelling. In the object space, the relative accuracy of 1/330 with respect to the average object distance can be achieved. Regarding to the lens distortion, radial distortion is the largest to the magnitude of several pixels.

關鍵字

Keywords

附件檔名

華芸線上圖書館

N / A

備註說明

200012-5-4-39-54

Pages:

55-63

論文名稱

「科技短文」地形圖掃描影像之特徵萃取

Title

Feature Extraction from a Scanned Thematic Map

作者

陳家堂 , 陳錕山 , 陳繼藩 , 洪耀山

Author

Chia -Tang Chen , K. S. Chen , C. F. Chen , Yao- Shan Hun g

中文摘要

本研究的目的為地形圖掃描影像之特徵萃取,其目標特徵為城鎮、道路、河流及湖泊等四種目標。各類目標物的特徵包括了色調及幾何特性。本研究所利用的方法是先將地形圖的色調以類神經網路分類器加以分離,接著將分類二元影像中的細小區塊濾除及圖案資料庫填補法等方法來進行幾何特性的萃取。本研究的結果顯示出,利用這些方法能將大部份的目標物萃取出來,而有一小部份面積較小的目標物則因本方法的先天限制而無法萃取。

Abstract

The purpose of this paper is to develop a new method to extract features from the scanned thematic map. Features to be extracted are the urban, road, river, and lake. The method is divided into two parts. One is the color classification, and the other is the feature extraction of binary classification image. To perform color classification, a supervised neural classifier, called Dynamic Learning Neural Network (DLNN), is used, while feature extraction is done by means of segmentation and erosion. The test data is a scanned image of 1/50000 thematic map in Southern Taiwan. Results demonstrate that the method is both effective and efficient in extracting features of interest in the scanned image.

關鍵字

地形圖掃描、特徵萃取、影像分類

Keywords

Scanned Thematic Map, Feature Extraction, Classification

附件檔名

華芸線上圖書館

N / A

備註說明

200012-5-4-55-63

更多活動學刊