博碩士論文 102022004 詳細資訊




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姓名 方鋐亦(Hong-Yi Fang)  查詢紙本館藏   畢業系所 遙測科技碩士學位學程
論文名稱 融合高時空解析度影像於水稻判釋 -以台灣為例
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摘要(中) 稻米為台灣的主要經濟糧食作物,多種植於台灣的西部平原與東部花東縱谷。衛星影像為近年用於農作監測常用的資料,高時間解析度影像能捕捉稻作的生長情形,有利於稻作判釋,然而高時間解析度影像其空間解析度並不高,對於平均坵塊面積較小且破碎的台灣並不適用。目前衛星感測器難以同時具有兩種特性,因此需要結合不同的衛星進行影像融合,產製高時空時序融合影像。
本研究目的為因應台灣的小塊稻作坵塊,結合MODIS影像的8天時間解析度與Landsat影像的30公尺空間解析度,產製2012、2013年於研究區的多時序融合影像,並基於稻作物候特性判釋一期、二期稻作,以此檢核影像融合成果。主要流程分為五個步驟:第一步驟,對參與使用的衛星影像進行影像前處理,如幾何校正等。第二步驟,以STARFM (Spatial Temporal Adaptive Reflectance Fusion Model)融合改進方法對研究區MODIS與Landsat影像進行融合,產生高時空融合影像。第三步驟,以融合資料建構常態化植生指標 (Normalized Difference Vegetation Index, NDVI)的時序影像,並以小波轉換 (Wavelet Transform)濾除時序資料上的雜訊,保留稻作資訊。第四步驟,使用支援向量機 (Support Vector Machine, SVM)分類一期、二期稻作。第五步驟,以地真資料與統計資料對分類成果評估精度。
分類結果顯示與地真資料有高度一致性,整體而言,總體精度都在80%以上,Kappa值在0.65以上。與統計資料相比,R^2在0.85以上,RMSE (Root Mean Square Error)最多占統計面積的3%以內,分類成果多數的鄉鎮為誤判 (Commission)。因此以STARFM的融合改進方法產製多時序融合影像判釋稻作,約有80%的精度。
摘要(英) Rice is the main food crop in Taiwan, mostly grown in western plains and eastern Tai-wan. In recent years, satellite data are used for crop monitoring. High temporal resolution data can provide information of crop phenology. However, only high temporal resolution data are not sufficient for rice mapping in Taiwan, because rice fields here are generally small and fragmented. In this case, it is necessary to combine different satellite image, get-ting a high spatial resolution and high temporal resolution fusion image for rice mapping.
The study aims to identify rice fields in areas in Taiwan using time-series MODIS (8-day)-Landsat (30m) fusion data in 2012 and 2013. The study consists of five steps: (1) Correct geometric and radiometric errors of Landsat data in data pre-processing; (2) Use the spatial temporal adaptive reflectance fusion model (STARFM) to blend the fusion data; (3) Construct smoothed normalized difference vegetation index (NDVI) time-series data by wavelet transform function; (4) Use support vector machine (SVM) to classify data; (5) Es-timate major rice crop area and assess mapping accuracies.
The results indicate a high correlation between the mapping results and ground truth data. The overall accuracies are upper than 80%, and Kappa values are upper than 0.65. Compared with the government rice statics, the R2 are upper than 0.85, and the root mean square error (RMSE) are up to 3% of total rice statics. Most of the mapping results of town-ship level are commission. It means using time series fusion data to mapping rice is useful, it’s about 80% accuracy.
關鍵字(中) ★ 影像融合
★ Landsat
★ MODIS
★ 稻作
★ 時間序列
★ 台灣
關鍵字(英) ★ Data fusion
★ Landsat
★ MODIS
★ Rice Crop
★ Time series
★ Taiwan
論文目次 第一章 緒論 1
1-1 研究動機 1
1-2 研究目的 2
1-3 論文架構 3
第二章 文獻回顧 4
2-1 應用時序資料判釋稻作之研究 4
2-2 影像融合 5
第三章 研究區及資料收集 7
3-1 研究區域概述 7
3-1-1 台灣西部研究區域 7
3-1-2 台灣東部研究區域 9
3-2 衛星影像 10
3-2-1 MODIS影像特性 10
3-2-2 Landsat影像特性 12
3-2-3 影像選擇 14
3-3 研究參考資料 15
3-3-1 稻作調查資料 15
3-3-2 地真與統計資料 15
3-3-3 數值高程模型 16
第四章 研究方法 17
4-1 資料前處理 18
4-1-1 Landsat-7影像填補 18
4-1-2 影像鑲嵌與投影轉換 22
4-1-3 影像再取樣與幾何校正 23
4-1-4 輸入影像選取 24
4-2 影像融合方法 29
4-2-1 STARFM 29
4-2-2 時序融合 33
4-3 NDVI時序資料計算 33
4-3-1 濾除雜訊 35
4-3-2 影像遮罩 36
4-4 稻作分類 38
4-4-1 SVM (Support Vector Machine)分類法 40
4-4-2 訓練樣區選擇 41
4-5 精度評估 41
4-5-1 誤差矩陣 43
4-5-2 RMSE與R2 44
第五章 研究成果與討論 45
5-1 融合成果分析 45
5-1-1 西部研究區影像分析 45
5-1-2 東部研究區影像分析 55
5-1-3 影像融合成果討論 65
5-2 影像分類成果與精度評估 66
5-2-1 影像分類-精度評估 66
5-2-2 影像分類-面積檢核 82
5-2-3 影像分類成果討論 90
第六章 結論與建議 98
6-1 結論 98
6-2 建議 100
參考文獻 101
參考文獻 工研院,(2001),"遙測與資訊技術應用於精準農業技術之建立-結合遙測與GIS建置水稻田辨識系統 (3/4) ",工研院能資所第063-90-Q010號報告。
石月嬋,(2014),"融合多源遙感數據生成高時空分辨率數據的方法對比",紅外與毫米波學報。
任玄,(2013),"高解析度多光譜影像於森林資源調查之應用",行政院農業委員會林務局102年度科技計畫研究報告。
李盈潔,(2013),"台灣西部海岸平原土地使用變遷對農地景觀與其生態系統服務影響之研究",臺北大學都市計劃研究所學位論文。
周天穎,(2012),"空間資訊技術原理及其應用",儒林圖書。
陳正儒,(2014),"以衛星影像物候資訊進行稻作分區之研究",國立中央大學土木工程學系研究所博士論文。
陳青,(2010),"應用經驗模態分解法分析多時期SPOT衛星影像上一年兩期之稻作",國立中央大學土木工程學系研究所碩士論文。
陳映璇,(2011),"應用衛星影像估算稻作田之植生參數與二氧化碳通量",臺灣大學生物環境系統工程學研究所學位論文。
陳益凰、曾義星,(1999),"應用多時段衛星影像辨識水稻田之研究",航測及遙測學刊,Vol.4 (3),1-16。
黃則林、廖閱郎、王賢杰,(1982),"稻作光譜特性之探討",林務局農林航空測量所,Vol.35 (7)。
黃思維,(2010),"應用經驗模態分解法分析多時期SPOT衛星影像上一年兩期之稻作",國立中央大學土木工程學系研究所碩士論文。
楊德文,(2010),"Landsat-7 影像兩階段式空隙像元填補方法之研究",國立中央大學土木工程學系研究所碩士論文。
羅健文,(2009),"以道路路網為基礎之綠廊道網絡規劃模式",臺北大學都市計劃研究所學位論文。
Bastiaanssen, W. G. M., Molden, D. J., Makin, I. W., (2000). Remote sensing for irrigated agriculture: examples from research and possible applications. Agricultural Water Management, 46(2), 137-155.
Busetto, L., Meroni, M., Colombo, R., (2008). Combining medium and coarse spatial resolu-tion satellite data to improve the estimation of sub-pixel NDVI time series. Remote Sensing of Environment, 112(1), 118-131.
Bhandari, S., Phinn S., Gill T., (2012). Preparing Landsat Image Time Series (LITS) for Monitoring Changes in Vegetation Phenology in Queensland, Australia. Remote Sensing, 4(6), 1856-1886.
Chen, C.F., Son, N.T., Chang, L.Y., (2012). Monitoring of rice cropping intensity in the upper MeKong Delta, Vietnam using time-series MODIS data. Advance Space Research, 49, 292-301.
Chen, C.F., Son, N.T., Chen, C.R., Chang, L.Y., (2012). Wavelet filtering of time-series mod-erate resolution imaging spectroradiometer data for rice crop mapping using support vector machines and maximum likelihood classifier. Journal of Applied Remote Sens-ing, vol.5.
Gao, F., Masek, J., Schwaller, M., Hall, F., (2006). On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. Geoscience and Remote Sensing, IEEE Transactions on, 44(8), 2207-2218.
Galford, G. L., Mustard, J. F., Melillo, J., Gendrin, A., Cerri, C. C., Cerri, C. E. P., (2008). Wavelet analysis of MODIS time series to detect expansion and intensification of row- crop agriculture in Brazil. Remote Sensing of Environment, 112(2), 576-587.
Gao, F., Morisette, J.,T., Wolfe, R., E., Ederer, G., Pedelty, J., Masuoka, E., Myneni, R., Tan, B, Nightingale, J., (2008). An algorithm to produce temporally and spatially continuous MODIS-LAI time series. IEEE Geoscience and Remote Sensing Letters, 5(1), 60-64.
Huang, M. Y., Huang, C. J., Fu, T. T., (2002). Cultivation arrangements and the cost effi-ciency of rice farming in Taiwan. Journal of Productivity Analysis, 18(3), 223-239.
Lillisand, T.M., Kiefer, R.W, Chipman, J.W., (2004). Remote Sensing and Image Interpreta-tion. Fifth Edition, John Wiley & Sons, Inc.
Lillesand, T. M., Kiefer R. W., Chipman, J. W., (2008). Remote Sensing and Image Interpre-tation, 6th Ed., John Wiley & Sons.
Ling, Y., Ehlers, M., Usery, E., Madden, M., (2008). Effects of spatial resolution ratio in image fusion. International Journal of Remote Sensing, 29(7), 2157-2167.
Liu, F., Wang, Z., (2010). Synthetic Landsat data through data assimilation for winter wheat yield estimation. Geoinformatics, 2010 18th International Conference on. IEEE, 1-6.
Liu, H., Weng, Q., (2012). Enhancing temporal resolution of satellite imagery for public health studies: A case study of West Nile Virus outbreak in Los Angeles in 2007. Re-mote Sensing of Environment, 117, 57-71.
Leinenkugel, P., Wolters, M. L., Kuenzer, C., Oppelt, N., Dech, S., (2014). Sensitivity analy-sis for predicting continuous fields of tree-cover and fractional land-cover distributions in cloud-prone areas. International Journal of Remote Sensing, 35(8), 2799-2821.
Maclean, J.L., Dawe, D.C., Hardy, B., (2002). Rice almanac: Source book for the mostim-portant economic activity on earth, CABI Publishing.
Murakami, T., Ogawa, S., Ishitsuka, K., Kumagai, K., Saito, G., (2001). Crop discrimination with multi- temporal SPOT/HRV data in the Saga Plains, Japan. International Jour-nal of Remote Sensing, 22(7), 1335-1348.
Maxwell, S., (2004). Assessment of Landsat 7 ETM+ SLC-off Data for an Agricultural Crop Type Mapping Application. USGS EROS Data Center, Sioux Falls, SD.
Maselli, F., Papale, D., Puletti, N., Chirici, G., Corona, P., (2009). Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems. Remote Sensing of Environment, 113(3), 657-667.
Pohl, C., Van, J. L., (1998). Review article multi-sensor image fusion in remote sensing: concepts, methods and applications. International journal of remote sensing, 19(5), 823-854
Rani, K., Sharma, R., (2013). Study of Different Image fusion Algorithm. Exploring research and innovations, 3(5).
Sakamoto, T., Nhan, N.V., Ohno, H., Ishitsuka, N., and Yokozawa, M., (2006). Spa-tial-temporal distribution of rice phenology and cropping systems in the Mekong delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Re-mote Sensing of Environment, 100, 1–16
Sakamoto, T., Nhan, N.V., Ohno, H., Ishitsuka, N., Yokozawa, M., (2006). Spatial-temporal distribution of rice phenology and cropping systems in the Mekong delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sensing of Environment, 100, 1–16.
Sari, D., K., Ismullah, I., H., Sulasdi W., N., Harto, A., B., (2010). Detecting Rice Phenology in Paddy Fields with Complex Cropping Pattern Using Time Series MODIS Data, ITB J. Sci., 42 A(2), 91-106
Singh, D., (2012). Evaluation of long-term NDVI time series derived from Landsat data through blending with MODIS data. ATMOSFERA, 25(1), 43-63.
Storey, J., Scaramuzza, P., Schmidt, G., (2005). Landsat-7 scan line corrector-off gap-filled product development. Global Priorities n Land Remote Sensing in Pecora 16 October 2005, 23-27.
Tzotsos, A., Argialas, D., (2008). Support Vector Machine Classification for Object-Based Image Analysis. Object-Based Image Analysis Lecture Notes in Geoinformation and Cartography 2008, 663-677.
Watts, J. D., Powell, S. L., Lawrence, R. L., Hilker, T., (2011). Improved classification of conservation tillage adoption using high temporal and synthetic satellite imagery. Re-mote Sensing of Environment, 115, 66-75.
Xiao, X., Boles, S., Frolking, S., Li, C., Babu, J., Y., Salas, W., Moore, B., (2006). Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS imag-es. Remote Sensing of Environment,100, 95 – 113.
Zhukov, B., Oertel, D., Lanzl, F., Reinhackel, G., (1999). Unmixing-based multisensor mul-tiresolution image fusion. Geoscience and Remote Sensing. IEEE Transactions on, 37(3), 1212-1226.
Zhu, X., Chen, J., Gao, F., (2010). An enhanced spatial and temporal adaptive reflectance fu-sion model for canplex heterogeneous regions. Remote Sensing of Environmen,114(11), 2610-2623.
指導教授 陳繼藩(Chi-Farn Chen) 審核日期 2015-7-29
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