叶面积指数(leaf area index,LAI)是反映植物冠层结构和光能利用的重要指标.随着遥感技术的不断发展,利用遥感数据获取大面积LAI已经成为监测作物生长和估产的重要手段.基于物理模型的LAI遥感反演方法经常假设作物冠层结构是均匀分布,然...叶面积指数(leaf area index,LAI)是反映植物冠层结构和光能利用的重要指标.随着遥感技术的不断发展,利用遥感数据获取大面积LAI已经成为监测作物生长和估产的重要手段.基于物理模型的LAI遥感反演方法经常假设作物冠层结构是均匀分布,然而,作为典型的垄行结构,作物冠层被公认为是介于连续植被与离散植被之间的一种过渡形式,而简单的均匀假设必然会给反演带来偏差.本文以农作物玉米为研究对象,首先重建了玉米三维冠层结构,并定量对比分析了一维辐射传输模型PROSAIL和三维辐射传输模型LESS在玉米冠层不同生长期的反射率差异,确定了玉米冠层的非均匀分布特征是引起PROSAIL模型模拟和反演误差的主要因素;然后,考虑到玉米冠层生长过程中聚集指数的变化特征,利用LESS模型定量计算了不同生育期玉米冠层结构对应的聚集指数,建立了聚集指数和有效叶面积指数(LAI_(e))之间的关系;进而,利用该关系对基于PROSAIL模型反演得到的LAI进行修正.结果表明,修正后的LAI精度有明显提高,R^(2)从0.27提高到了0.55.该方法有望提高中高分辨率遥感数据在农作物LAI反演精度.展开更多
山地森林叶面积指数(Leaf Area Index,LAI)的准确获取对评估森林生态系统的生产力和碳循环至关重要。遥感手段是当前获取面尺度LAI的主要方法,植被指数(Vegetation Indices,VIs)因其简便性和鲁棒性,广泛用于LAI反演。然而,复杂地形会导...山地森林叶面积指数(Leaf Area Index,LAI)的准确获取对评估森林生态系统的生产力和碳循环至关重要。遥感手段是当前获取面尺度LAI的主要方法,植被指数(Vegetation Indices,VIs)因其简便性和鲁棒性,广泛用于LAI反演。然而,复杂地形会导致VIs反演结果存在不确定性。本研究基于地面实测LAI和无人机高光谱数据,选择40种主流VIs,按波段和数学构成分为4类,评估其在坡度、高程和天空可视因子(Sky View Factor,SVF)变化下的反演精度。结果表明:1)红光和近红外波段的严格比值型VIs与LAI具有最优的建模精度,以NDVI为例,不同坡度变化下R^(2)在0.450~0.681之间浮动,不同高程变化下R^(2)在0.507~0.824之间浮动,不同SVF变化下R^(2)在0.311~0.765之间浮动。2)坡度变化对反演精度的影响可通过波段比值部分削弱;高程变化通过影响植被分布影响建模精度;目前无VIs能有效消除SVF变化带来的影响。3)不同季节VIs的适用性不同,GCC适用于初春,R^(2)最优为0.657,SIPI适用于夏季高温期,R^(2)最优为0.558,kNDVI在秋季表现最佳R^(2)最优分别为0.578,NDVI在冬季表现最佳,R^(2)最优为0.708。本研究对VIs在山地森林LAI反演时的地形效应进行了系统评估,可为准确评估森林生态系统碳循环及实现“碳达峰碳中和”做出一定的贡献。展开更多
Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Scien...Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.展开更多
Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Scien...Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.展开更多
Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Scien...Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.展开更多
Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Scien...Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.展开更多
文摘叶面积指数(leaf area index,LAI)是反映植物冠层结构和光能利用的重要指标.随着遥感技术的不断发展,利用遥感数据获取大面积LAI已经成为监测作物生长和估产的重要手段.基于物理模型的LAI遥感反演方法经常假设作物冠层结构是均匀分布,然而,作为典型的垄行结构,作物冠层被公认为是介于连续植被与离散植被之间的一种过渡形式,而简单的均匀假设必然会给反演带来偏差.本文以农作物玉米为研究对象,首先重建了玉米三维冠层结构,并定量对比分析了一维辐射传输模型PROSAIL和三维辐射传输模型LESS在玉米冠层不同生长期的反射率差异,确定了玉米冠层的非均匀分布特征是引起PROSAIL模型模拟和反演误差的主要因素;然后,考虑到玉米冠层生长过程中聚集指数的变化特征,利用LESS模型定量计算了不同生育期玉米冠层结构对应的聚集指数,建立了聚集指数和有效叶面积指数(LAI_(e))之间的关系;进而,利用该关系对基于PROSAIL模型反演得到的LAI进行修正.结果表明,修正后的LAI精度有明显提高,R^(2)从0.27提高到了0.55.该方法有望提高中高分辨率遥感数据在农作物LAI反演精度.
文摘Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.
文摘Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.
文摘Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.
文摘Editor-in-Chief Yuanming Lai,Academician of Chinese Academy of Sciences,director of Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,China,Associate Editor of Cold Regions Science and Technology.
