ENGLISH

13卷/1期

13卷/1期

華藝線上圖書館

Pages:

1-18

論文名稱

利用遙測資料估算水稻田蒸發散量

Title

Using Remote Sensing to Estimate Evapotranspiration of Paddy Field

作者

簡子杰,劉說安,張子瑩

Author

Tzu-Chieh Chien,Yuei-An Liou, Tzu-Yin Chang

中文摘要

蒸發散在水文循環、區域氣候中扮演重要角色,如何能獲得其觀測值,成為重點課題。以水稻田為 例,水稻田區能吸收與儲存大量的熱能,經由蒸發散作用釋放出來,以調節周圍環境的溫度,因此在都 市化的區域中,得有效降低熱島效應強度。本研究的目的,在於建立遙測資料估算水稻田蒸發散量的反 演模式,以利未來應用於長時間、大面積的監測水稻田蒸發散量,及進行蒸發散作用調節熱島效應的評 估及研究。所提出的反演模式是以地表能量平衡為基礎,利用遙測資料配合地面氣象站的氣象資料,進 行地表熱通量的估計。首先,利用大氣不穩定的修正模式,推估潛熱通量和可感熱通量的初始值,再以 迭代方式自動取得乾濕控制點,獲得乾、濕控制曲線,進而重新分配淨可用能量,以推估最終的潛熱通 量和可感熱通量,而潛熱通量即水稻田的蒸發散量。研究中先應用空載影像進行改良模式的測試,在反 演水稻田的蒸發散量結果上與地面測站比對,蒸發散量比值的偏差僅有6.8%,因而將此方法推廣至較高 時間解析度衛載的MODIS影像加以分析。比較MODIS影像所推估的潛熱通量與地面測站真值,相關係數 為0.66,均方根差為97.81(Wm-2);可感熱通量方面,相關係數可達0.76,均方根差為124.33(Wm-2)。結果 顯示,利用本研究所提出的反演方法結合MODIS衛星資料,進行水稻田蒸發散量的估算為可行的,期望 未來能推廣至各地,利用於進行水稻田長時期蒸發散量之監測。

Abstract

Evapotranspiration is an important factor in hydrology cycle and regional climate. For example, rice paddy field absorbs and stores huge amount of energy, which is released to the air through evapotranspiration. As a result, ambient temperature is adjusted and the strength of the heat island effect is mitigated in the urbanization areas. The aim of the current study is to develop an evapotranspiration retrieval algorithm for rice paddy field by remote sensing technique in order to provide long-term and large-area observation and to investigate its role in heat island effect. The proposed retrieval algorithm is based on energy balance at the land-air interface. Surface heat fluxes are estimated by remote sensing data with in situ surface meteorological measurements. The initial values of latent heat and sensible heat fluxes are obtained using an unstable atmospheric correction method. By iterating the energy balance equation, radiation and evaporation controlled lines are determined, and hence, the net available energy is redistributed into latent and sensible heat fluxes, respectively. In this study, both airborne and satellite imageries are utilized. The former imagery covers a small area with high spatial resolution. The satellite imagery acquired by MODIS is utilized to estimate the evapotranspiration over the entire Taiwan. The proposed retrieval algorithm has provided a fairly good estimate of evaporation fraction by airborne imagery with bias of 6.8% when compared with the in situ measurements, while performed poorly with the satellite imagery. To improve the evapotranspiration estimate by satellite imagery, the Paulson and Dyer’s corrections to unstable atmosphere were modified. The correlation coefficients for latent heat flux and sensible heat flux and the corresponding in situ observations were found to be 0.66 and 0.76, respectively. The root mean square errors for latent heat flux and sensible heat flux were 97.81 Wm-2 and 124.33 Wm-2, respectively.

關鍵字

潛熱通量、可感熱通量、蒸發散量、MODIS

Keywords

Latent heat flux, Sensible heat flux, Evapotranspiration, MODIS

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-1-18

Pages:

19-28

論文名稱

墾丁國家公園四種優勢植群之地面光譜分析

Title

The Ground spectral analysis of four dominant vegetation in the Kenting National Park, Taiwan

作者

呂明倫,葉慶龍,鍾玉龍,謝依達

Author

Ming-Lun Lu, Ching-Long Yeh, Yuh-Lurng Chung, Yi-Ta Hsieh

中文摘要

本研究以墾丁國家公園為研究區,調查期間為2006年11月至2007年10月,利用地面手持光譜儀,量測 植群冠層之光譜特徵,包含區域內之銀合歡(Leucaena leucocephala )、黃荊(Vitex negundo)、相思樹(Acacia confuse)與林投(Pandanus odoratissimus )等4種優勢植群。主要目的係將每個月份所蒐集之光譜資料,擬以多 光譜與高光譜之方式,評估可見光至近紅外光之光譜區間中,4種優勢植群之辨別潛力。經多光譜分析結 果顯示,植物本身因乾季3月份與濕季7月份所產生的物候現象,可增加植群辨別的可能性,而高光譜分 析結果顯示,乾季3月份可完全有效辨別4種優勢植群。綜合以上所述,本研究建議未來進行大尺度的植 群繪圖工作時,宜集合乾、濕季多時段衛星影像,亦可採用高光譜影像,前提須考慮到植物的物候階段 來作選擇。

Abstract

The spectral characteristics of the vegetation canopy, including four dominant vegetation types, Leucaena leucocephala, Vitex negundo, Acacia confuse and Pandanus odoratissimus, were measured from November 2006 to October 2007 using a ground handheld spectroradiometer in the Kenting National Park of Taiwan. The purpose of this paper was conducted to evaluate the potential of multispectral and hyperspectral reflectance in the visible to near infrared spectral range, for discriminating four dominant vegetation types every sampling date. Differences observed in the multispectral analysis showed that four dominant vegetation types were possible to distinguish due to phenology in March 2007 (dry season) and July 2007 (wet season), and in hyperspectral were statistically significant in March 2007, which facilitates their discrimination. Our results suggest that mapping four dominant vegetation types is feasible using multi-temporal imagery, and hyperspectral sensors, taking into account the plant phenological stages.

關鍵字

光譜特徵、多光譜、高光譜、物候現象

Keywords

spectral characteristics, multispectral, hyperspectral, phenology

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-19-28

Pages:

29-42

論文名稱

貝氏統計應用於GPS定位與其信賴區域之研究

Title

GPS Positioning and Its Confidence Regions Based on Bayesian Inference

作者

李依淇,吳 究,謝吉修

Author

Yi–Chi Li, Joz Wu, Chi–Hsiu Hsieh

中文摘要

全球定位系統提供全天候的觀測量與高精度的定位成果。然而,利用載波相位觀測量進行定位時, 會產生整數與實數之混合型態未知參數的問題。本研究利用貝氏統計所推導之相位模稜的邊際後驗密度 函數,以最大後驗法求定整數相位模稜及實數幾何參數之估計值。此外,基於約制模稜之先驗分布與真 實資料狀況並不符合的概念,本文利用貝氏方法所推導之決策運作指標,即時判定是否擴大模稜搜尋空 間以求正確模稜估計值。本研究目的即為利用貝氏統計的方法與決策運作指標進行GPS 近即時定位,以 及藉由貝氏推論所導之定位估計值與協方差矩陣,以蒙地卡羅數值法獲取定位參數之信賴區域。實驗成 果顯示,利用決策指標判別是否擴大模稜搜尋空間的方法,可即時且自動化地判斷模稜搜尋空間是否恰 當,並找出正確的整數解以提升整體的定位精度,且蒙地卡羅數值法可即時以視覺化的方法呈現定位參 數之信賴區域。

Abstract

GPS provides all-weather observations, and highly accurate positions. With a GPS model using carrier-phase observations containing integer-valued and real-valued unknown parameters, this paper presents a near-real-time data processing technique based on Bayesian statistics. The Bayesian approach takes the maximum–likelihood posterior solution of positioning parameters as the estimator with highest posterior density function of ambiguity. Moreover, for the sake of the fact that restricting the prior distribution of ambiguities is not consistent with the real data in Bayesian view, a theory of mixture model based on Bayesian inference was advanced and the index for decision-making was derived. The index was used here to determine whether the ambiguity search space is expanded or not. The main aims of this research are to perform the GPS positioning by using the Bayesian approach with the index for decision-making and determine the confidence regions for positioning parameter by using a Monte Carlo method based on the Bayes estimation and covariance matrix. The experimental results show that the correct solution can be obtained and the accuracy of positioning results can be improved in real time and automatically by using the Bayesian approach. Furthermore, the confidence regions for GPS positioning parameter can be determined by using the Monte Carlo method.

關鍵字

全球定位系統、後驗密度函數、貝氏統計、信賴區域

Keywords

Global Positioning System (GPS), Posterior density function, Bayesian statistics,Confidence regions

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-29-42

Pages:

43-56

論文名稱

以Boosting 法改進監督式分類於水稻田樣本特性之研究

Title

The Research on Improvement of Supervised Characteristics of the Rice Paddy

作者

楊龍士, 陳慧欣, 劉致亨,周天穎

Author

Lung-Shih Yan,Hui-Hsin Chen,Chih-Heng Liu,Tien-Yin Chou

中文摘要

資料挖掘(Data Mining)運用在衛星影像並結合機器學習理論,可從大量資料中發現知識。採用迴歸樹 (CART)法獲得水稻分類知識是應用範例之一雖然此方法仍需進行樣本選取,但可降低樣本選取因素對分 類成果的影響,如範圍狹小,特性不均勻等因素。利用機器學習集成方式Boosting,可以解決樣本重新選 取所造成的特性改變,有助於提升分類成果準確度。利用Boosting 組合分類準確度較差之樣本,分析並 獲得分類精度較佳的樣本組合,避免重新取樣的問題,再配合CART 分類法的使用,可提昇分類準確度。 研究成果顯示,在分類精度方面利用Boosting 方法比傳統最大概似法及CART 法,分別提昇了近5%及3%。

Abstract

Data Mining can be applied to the satellite images and can be combined with machine learning theory. This technology is used to discover knowledge from large mounts of data. CART is a kind of methods to acquire the knowledge of rice paddy classification. Although this method needs to select the samples, it can reduce the effects which are caused by the selection of samples on the results of classification, for example, the narrow area and the uneven characteristics. The machine learning method, Boosting, can solve the problem of characteristic changes that are caused by the re-selection of samples. This method can increase the accuracy of the classification. The samples which have the low accuracy of classification are organized by Boosting Method. Boosting Method analyzes the samples and acquires the samples that have the higher classification accuracy in order to avoid the re-selection of samples. And, Boosting method co-operates with CART classification method to improve the accuracy of classification. According to the result of this study, Boosting Method can improve the maximum likelihood method and the CART method on the classification accuracy which rise 5% and 3% individually.

關鍵字

Boosting、資料挖掘、監督式分類、樣本特性

Keywords

Boosting, Data mining, Supervised Classification, Sample Characteristic

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-43-56

Pages:

57-65

論文名稱

GNSS 於台灣地區精度與可靠度分析

Title

The Accuracy And Reliability Analysis For Future GNSS In Taiwan Region

作者

蔡孟倫, 江凱偉,楊名, 陳鶴欽

Author

Meng-Lun Tsai, Kai-Wei Chiang,Ming Yang,Ho-Chin Chen

中文摘要

全球導航衛星系統(Global Navigation Satellite System, GNSS)性能指標可區分為可得度(availability)、精度 (accuracy)、完好度(integrity)及可靠度(reliability)。未來現代化GPS、Galileo 之單一衛星導航系統或整合GPS 與Galileo 的雙系統多頻衛星導航系統,將會提供較現有GPS 系統加倍的衛星、更多的測量頻率、以及更 好的訊號品質,從而進一步提昇現有GPS 衛星定位的精度、可靠度、以及效率。這點對測量界的使用者 是相當重要的。由於GPS 與Galileo 具備較高之相容性且未來GPS 之L1/L5 會與Galileo 之E1/E5b 具備相 同之頻率。故預期未來基於成本之考量,雙系統雙頻的GNSS 會成為測量等級GNSS 接收機設計之主流。 故本研究擬利用自行研發的GNSS 模擬器針對未來GPS/ Galileo 整合式定位系統在台灣地區的三維定位精 度分佈、內可靠度(internal reliability)及外可靠度(external reliability)進行評估與分析。

Abstract

The indices of evaluating the performance of GNSS are composed of satellite availability, positioning accuracy, integrity and reliability. The future GNSS including stand alone modernized GPS, Galileo or GPS/Galileo integrated system will support more satellites, more observable frequencies and better signal quality comparing to current GPS. Therefore, the positioning accuracy, reliability and efficiency can further be enhanced. For surveying communities, those improvements are very critical. Since the compatibility between modernized GPS and Galileo is enhanced in the design phase and both of them will share two frequencies (L1/E1, L5/E5a), therefore, the receiver supporting dual-systems and dual-frequencies will dominate the geodetic grade GNSS receiver market in the future based on the accuracy enhancement and cost anticipated. This study aims at using the GNSS software simulator developed in the department of Geomatics, NCKU to analyze the three dimensional positioning accuracy, internal reliability (MDB) and external reliability (MDE) in Taiwan region based on three different scenarios including stand along modernized GPS, Galileo and GPS/Galileo integrated system.

關鍵字

全球導航衛星系統、模擬器、精度(accuracy)、可靠度(reliability)

Keywords

GNSS, Simulation, Accuracy, Reliability

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-57-65

Pages:

67-73

論文名稱

雷射入射角與空載光達穿透率關係探討

Title

On the Laser Incidence Angle and Airborne LiDAR Penetration Rate

作者

黃清美,史天元

Author

C.M. Huang,T.Y. Shih

中文摘要

空載光達原始點雲資料包含地面點與地物點,以空載光達產製數值高程模型時,地面點之密度與分 布影響其對地形描述之詳實度有絕對之關係。因此,在表現資料品質優劣時,地面點點雲密度為重要指 標之ㄧ。地面點密度高且分布均勻時,較能正確地展示地形面。地面點密度除受原始點雲密度之影響外, 穿透率為另一重要因子。穿透率受地表覆蓋物型態、雷射入射角與航高等因子影響。本研究以雷射入射 角對穿透率的影響為探討目標,使用實測航帶,依平行航向五等分,作為五種不同雷射入射角之統計單 元,分別求取各等分之穿透率。實驗結果顯示,當雷射入射角越小時,穿透率越高,反之亦然,航帶中 間分帶穿透率約是面向航向最右五分之一(右二)及最左五分之一(左二)分帶的1.6 倍,是由右方起第二個 五分之一(右一)及第四個五分之一(左一)分帶的1.3 倍。

Abstract

The point cloud obtained from airborne LiDAR is composed of ground points and non-ground points. The density of ground points is an important index for characterizing the quality of DEM. When ground point density is high and distributed evenly, topography can be presented with high fidelity. There are a number of factors which may influence the ground point density. In addition to the density of the original point cloud, penetration rate is another essential factor. Penetration rate is influenced by land-cover types, incidence angle, flying height, etc. This study investigates the influence of incidence angle on penetration rate. Partitioning a flight line into five segments along the flight direction, the penetration rates are computed. It is shown that the penetration rate is higher with smaller incidence angle. The central segment of the flight line is 1.6 times of the right most and left most sections, and 1.3 times penetration rate of next right and next left sections.

關鍵字

點雲、密度

Keywords

point cloud, density

附件檔名

華芸線上圖書館

N / A

備註說明

200803-1-1-67-73

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