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    Title: 應用MODIS資料估算稻作之綠水足跡
    Estimation of Green Water Footprint of Rice Paddies Using MODIS Data
    Authors: 黃姿瑜
    Huang, Tzu Yu
    Contributors: 林士淵
    Lin, Shih Yuan
    黃姿瑜
    Huang, Tzu Yu
    Keywords: 稻作
    綠水足跡
    蒸發散量
    MOD16
    逐步迴歸
    rice
    Green Water Footprint (GWF)
    evapotranspiration (ET)
    MOD16
    stepwise regression
    Date: 2016
    Issue Date: 2016-09-02 00:52:46 (UTC+8)
    Abstract:   水足跡為一新興發展之水資源消耗衡量指標,可用以估計水資源之分佈與途徑。其中「綠水足跡」係指生產過程中消耗的雨水量,包含降水的總蒸發散量及產品中所含水分;綠水能使作物成長而具生產性,然因其一部潛藏於產品中且含量甚低、另一部為蒸發散形式而致使推估不易、遭致忽略。為使作物生產用水量能被精確統計,有效估算綠水足跡至為重要。
      遙測產品─MODIS全球地表蒸發散監測資料(MOD16)具有高精度、涵蓋面積廣闊且長期監測之優勢,然若欲實際運用則將有產品釋出時間延遲及空間缺漏或低解析度等限制。故,本研究以MOD16資料為基礎,搭配可能影響稻作蒸發散量之氣象或自然因子,透過統計方法中的逐步迴歸法,建立蒸發散量之推估模型,以改進MOD16資料之時空限制、並供後續精確估算依使用者特定時間需求且完整的稻作綠水足跡。
      Water Footprint (WF) is a recently developed indicator to identify the usage and distribution of the fresh water resource. Among different types of WFs, Green WF (GWF) is referred to total rainwater evapotranspiration (ET) plus the amount of water incorporating in a product. As the water incorporated into the crop is about 0.1~1% of the evapotranspiration volume, Green WF is normally referred to as ET volume. Together with irrigation water withdrawn from ground or surface water (i.e. Blue water), they are the main indicators of contribution of water usage introduced in agricultural products. Therefore in order to comprehensively understand the total amount of water used during crop growing stage, it is essential to identify the amount of Blue and Green water. As Blue water footprint has been explored widely, this research focused on the estimation of Green WF.
      Based on the high accuracy, wide coverage and long-term extraction of rainwater evapotranspiration, a MODIS Global Terrestrial Evapotranspiration Data Set (MOD16) is applied to estimate GWF. Although the MOD16 product offers aforementioned advantages, we still encountered spatial and temporal inaccessibility. Therefore, this research aimed to overcome the drawbacks and develop a regression method considering multiple variables, including weather parameters and Normalized Difference Vegetation Index (NDVI) values, to improve the performance of GWF estimation. Through the experiments implemented in Taichung and Taitung, it was successfully demonstrated that the spatial and temporal accessibility of GWF of rice paddies calculated based on MOD 16 data was improved significantly.
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    Description: 碩士
    國立政治大學
    地政學系
    103257006
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G1032570061
    Data Type: thesis
    Appears in Collections:[地政學系] 學位論文

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