基于植被指数的喀斯特流域赋水动态变化遥感监测研究——以贵州省为例 |
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引用本文: | 贺中华,陈晓翔,梁虹,黄法苏,赵芳. 基于植被指数的喀斯特流域赋水动态变化遥感监测研究——以贵州省为例[J]. 国土与自然资源研究, 2012, 0(4): 48-51 |
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作者姓名: | 贺中华 陈晓翔 梁虹 黄法苏 赵芳 |
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作者单位: | 1. 中山大学地理科学与规划学院,广东广州510275;贵州师范大学地理与环境科学学院,贵州贵阳550001 2. 中山大学地理科学与规划学院,广东广州,510275 3. 贵州师范大学地理与环境科学学院,贵州贵阳,550001 4. 贵州省水文水资源局,贵州贵阳,550002 5. 贵州省贵阳市白云区职业技术学校,贵州贵阳,550014 |
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基金项目: | 贵州省教育厅基金,贵州省科技厅基金,贵州省水利厅基金 |
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摘 要: | 喀斯特流域具有特殊的双重含水介质,形成独特的地表—地下水系结构。因此,喀斯特流域水资源影响因素复杂多样,除气候、地貌、岩性等因素外,流域植被覆盖率也起到决定性的作用。本文在贵州省内选择20个流域作为研究样区,根据Landsat TM的植被光谱特征,流域赋水光谱特征,利用遥感技术,对TM影像进行光谱辐射亮度计算处理、表观反射率计算处理,并构建TVI、RDVI、EVI。根据现代数学分析方法的原理,借助Spss、MATLAB软件,探讨、建立喀斯特流域水资源监测、预测模型,并通过方差分析和样区检验,得出很好的预测效果。
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关 键 词: | 喀斯特 流域赋水 LandsatTM影像 TVI/RDVI/EVI 监测预测模型 |
Study of Remote Sensing Monitoring of Karst Basin Water-holding Dynamic Changing Based On Vegetation Indices-Taking Guizhou Province as a Case |
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Affiliation: | HE Zhong-hua1,2 et al(1.School of Geography and Planning,Sun Yat-sen University,Guangzhou 510275,China;2.School of Geographic and Environmental Science,Guizhou Normal University,Guiyang Guizhou 550001,China) |
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Abstract: | Karst basin has a special double aquifer medium,forming a unique surface-groundwater systems structure.Therefore,the factors of influencing karst water resources complex and diverse,in addition to climate,geomorphology,lithology and other factors,watershed vegetation cover also play a decisive role.This paper in Guizhou province selected 20 watershed area as the study sample,according to Landsat TM spectral characteristics of vegetation and Spectral characteristics of the water basin,to compute the spectral radiance and apparent reflectance of the TM images by using remote sensing techniques,and build TVI,RDVI,EVI.According to the principles of modern mathematical analysis,using Spss,MATLAB software to explore and establish the monitoring and forecasting models of karst water resources,and through analysis of variance and sample testing,obtained a good prediction. |
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Keywords: | Karst Basin Water-holding Landsat TM Images TVI/RDVI/EVI monitoring and forecasting models |
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