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
株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株...株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株高与可见光植被指数,使用逐步回归、偏最小二乘、随机森林、人工神经网络四种方法建立LAI估测模型,并对株高提取及LAI估测情况进行精度评价。结果显示:(1)株高提取值Hc与实测值Hd高度拟合(R^(2)=0.894,RMSE=6.695,NRMSE=9.63%),株高提取效果好;(2)与仅用可见光植被指数相比,基于株高与可见光植被指数构建的LAI估测模型精度更高,且随机森林为最优建模方法,当其决策树个数为50时模型估测效果最好(R^(2)=0.809,RMSE=0.497,NRMSE=13.85%,RPD=2.336)。利用无人机可见光遥感方法,高效、准确、无损地实现冬小麦株高及LAI提取估测可行性较高,该研究结果可为农情遥感监测提供参考。展开更多
A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irri...A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irrigation （W0）, irrigation once at jointing （W1j） or at booting （W1b）, irrigation twice at jointing and booting （W2）, and irrigation three times at jointing, booting and grain-filling （W3） and three planting densities, such as 180 （D1）, 300 （D2） and 450 （D3） seedlings per square meter. The results indicated that irrigation significantly improved population photosynthesis. The relationship between population photosynthesis and irrigation time/volume was to some extent parabolic. Improvements in population photosynthesis （resulting from more irrigation time/volume） were mainly related to increase in leaf area index and population light interception. Population photosynthesis exhibited a significantly negative correlation with canopy light transmittance. Population photosynthesis at grain filling stage was significantly positively correlated with dry matter accumulation at post-anthesis and grain yield. Main effects and partial correlation analysis showed that population photosynthesis of W0, W1j, W1b and W3 were regulated by canopy light transmittance and leaf area. On the other hand, population photosynthesis of W2 was mainly influenced by flag leaf photosynthetic rate. On this basis, planting 300 seedlings per square meter was the optimum combination. The combination of W2D2 increased population photosynthesis during mid-late growth stages and extended high population photosynthesis duration, which ultimately increased grain yield.展开更多
叶面积指数(leave area index,LAI)是表征植被冠层结构和生长状况的关键参数,采用遥感技术进行LAI反演是遥感反演领域的热点和难点之一。利用小麦关键生育期的高光谱数据,计算其一阶和二阶导数,并构建植被指数(RVI,NDVI,EVI,DVI和MSAVI...叶面积指数(leave area index,LAI)是表征植被冠层结构和生长状况的关键参数,采用遥感技术进行LAI反演是遥感反演领域的热点和难点之一。利用小麦关键生育期的高光谱数据,计算其一阶和二阶导数,并构建植被指数(RVI,NDVI,EVI,DVI和MSAVI)及三边变量参数等高光谱变量;将上述参数与小麦LAI数据进行相关性分析,并利用交叉验证法进行多种回归分析,确定反演小麦LAI的敏感参数,选择反演模型;最后使用敏感参数构建所有样本的小麦LAI反演模型,并比较其拟合效果。研究结果表明:经过交叉验证的反演建模,其拟合结果的均方根误差(RMSE)整体上较未经交叉验证反演建模结果的RMSE小;在用敏感参数构建的回归模型中,RVI立方回归模型是用遥感数据反演小麦LAI的最优模型。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.
文摘株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株高与可见光植被指数,使用逐步回归、偏最小二乘、随机森林、人工神经网络四种方法建立LAI估测模型,并对株高提取及LAI估测情况进行精度评价。结果显示:(1)株高提取值Hc与实测值Hd高度拟合(R^(2)=0.894,RMSE=6.695,NRMSE=9.63%),株高提取效果好;(2)与仅用可见光植被指数相比,基于株高与可见光植被指数构建的LAI估测模型精度更高,且随机森林为最优建模方法,当其决策树个数为50时模型估测效果最好(R^(2)=0.809,RMSE=0.497,NRMSE=13.85%,RPD=2.336)。利用无人机可见光遥感方法,高效、准确、无损地实现冬小麦株高及LAI提取估测可行性较高,该研究结果可为农情遥感监测提供参考。
基金Supported by China and CAS Main Direction Program of Knowledge Innovation (KSCX2-EW-B-1)China and CAS Knowledge Innovation Project(KSCX1-YW-09-06)
文摘A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irrigation （W0）, irrigation once at jointing （W1j） or at booting （W1b）, irrigation twice at jointing and booting （W2）, and irrigation three times at jointing, booting and grain-filling （W3） and three planting densities, such as 180 （D1）, 300 （D2） and 450 （D3） seedlings per square meter. The results indicated that irrigation significantly improved population photosynthesis. The relationship between population photosynthesis and irrigation time/volume was to some extent parabolic. Improvements in population photosynthesis （resulting from more irrigation time/volume） were mainly related to increase in leaf area index and population light interception. Population photosynthesis exhibited a significantly negative correlation with canopy light transmittance. Population photosynthesis at grain filling stage was significantly positively correlated with dry matter accumulation at post-anthesis and grain yield. Main effects and partial correlation analysis showed that population photosynthesis of W0, W1j, W1b and W3 were regulated by canopy light transmittance and leaf area. On the other hand, population photosynthesis of W2 was mainly influenced by flag leaf photosynthetic rate. On this basis, planting 300 seedlings per square meter was the optimum combination. The combination of W2D2 increased population photosynthesis during mid-late growth stages and extended high population photosynthesis duration, which ultimately increased grain yield.
文摘叶面积指数(leave area index,LAI)是表征植被冠层结构和生长状况的关键参数,采用遥感技术进行LAI反演是遥感反演领域的热点和难点之一。利用小麦关键生育期的高光谱数据,计算其一阶和二阶导数,并构建植被指数(RVI,NDVI,EVI,DVI和MSAVI)及三边变量参数等高光谱变量;将上述参数与小麦LAI数据进行相关性分析,并利用交叉验证法进行多种回归分析,确定反演小麦LAI的敏感参数,选择反演模型;最后使用敏感参数构建所有样本的小麦LAI反演模型,并比较其拟合效果。研究结果表明:经过交叉验证的反演建模,其拟合结果的均方根误差(RMSE)整体上较未经交叉验证反演建模结果的RMSE小;在用敏感参数构建的回归模型中,RVI立方回归模型是用遥感数据反演小麦LAI的最优模型。
