高光谱遥感森林叶面积指数估测研究现状

文中简要概述了叶面积指数和高光谱遥感的概念, 分析比较了高光谱遥感与传统的宽波段遥感估测森林叶面积指数的优势, 以及利用高光谱遥感数据估测森林叶面积指数的常用方法, 并对目前高光谱遥感估测森林叶面积指数存在的问题行了讨论。     

水曲柳阔叶混交林冠层光分布与天然更新相关性研究

探讨甘肃小陇山林区阔叶混交林冠层光分布对水曲柳天然更新的影响。以水曲柳为研究对象，采用大田试验和样地调查法，使用Hemi View数字植物冠层分析仪测定水曲柳阔叶混交林冠层的光照指标及LAI，建立DSF、ISF与LAI回归分析。结果表明，水曲柳在幼苗期适宜于在遮荫度<50%的环境下生长，当遮荫度>50%时，其苗高生长明显下降且与对照差异显著；水曲柳阔叶混交林中，林分冠层的郁闭度与叶面积指数（LAI）之间存在显著的正相关关系；散射光立地系数（ISF）、直射光立地系数（DSF）、散射光立地系数（GSF）、冠下总辐射（TotBe）随叶面积指数（LAI）的增大，呈明显的负相关关系，当郁闭度<0.66，散射光分布较多，更有利于水曲柳幼苗的生长与天然更新；对于种子扩散繁殖，距离母树0~5 m种子数量最多，随着距离的增加而减少，扩散半径因风向风不同而异，最远可达20 m。混交林冠层光分布对水曲柳幼苗期的天然更新有很大的影响。     

叶面积指数间接测量方法分析

叶面积指数(LAI)被定义为植物所有叶片表面积总和与植株所占的土地面积的比值,是表征植物生长趋势的重要参数。总结了当前LAI间接测量研究中的2个重要分支:遥感定量法和LIDAR测量法;详细地介绍了这2个分支下的3种方法:统计模型法、光学模型法、LIDAR测量法,阐述了各自的原理和研究进展;在此基础上,讨论了3种方法的优缺点及未来的发展趋势。     

Determining transpiration coefficients of Sahelian vegetation barriers

Vegetation barriers along contour lines are an appropriate measure for runoff management. An essential element of their design is minimisation of competition for water between the agricultural crop and the vegetation barrier. This requires the evapotranspiration of the vegetation barrier to be known. In 1998 FAO (the Food and Agricultural Organisation of the United Nations) presented a method to estimate the evapotranspiration of natural vegetation. The method includes a dual crop coefficient approach, distinguishing soil evaporation and canopy transpiration. The transpiration coefficient can be obtained from either the LAI (leaf area index) or the fractional ground cover. This paper reports the results of a study conducted in Burkina Faso in 1998. Transpiration coefficients of three vegetation barriers were obtained by directly measuring transpiration and soil evaporation during the mid-season growing stage. Measured values were compared with those obtained from the FAO estimation method, using both the LAI and the ground cover approach. In most cases the FAO approach overestimated the transpiration coefficient. To overcome overestimation FAO proposes a reduction factor based on the stomatal resistance of vegetation with high stomatal control. This factor is difficult to obtain, however, and complicates the relatively simple method of estimation. Even if this reduction factor is taken into account, an overestimation of transpiration coefficients when using the LAI approach should still be acknowledged.This revised version was published online in November 2005 with corrections to the Cover Date.     

Testing the performance of ORYZA1, an explanatory model for rice growth simulation, for Mediterranean conditions

ORYZA1 is an explanatory model to simulate rice growth, development and leaf area index (LAI) under potential production. The present study aims at testing the performance of ORYZA1 for Mediterranean conditions (farming practices, cultivars, weather) for fully irrigated direct-seeded rice. ORYZA1 was calibrated and validated with field data of two cultivars, a short-grain (Tebre) and a long-grain cultivar ( -202), grown in various years in the Ebro Delta of Spain. Phenological development of the rice crop, daily dry matter production and leaf area development were calibrated. Tebre and L-202 had no significant differences in the total length of the development period. The pre-heading period, however, was longer and the post-heading period shorter in L-202 than in Tebre. This induced differences in translocation characteristics, spikelet number per unit area, weight of the grains and harvest index. The following crop characteristics were similar between cultivars: extinction coefficient (increased with development stage), dynamics of nitrogen distribution, partitioning of assimilates, relative death rate of leaves, relative growth rate of leaf area during exponential growth, specific leaf area and a strongly decreasing specific stem green area. The simulated curve fitted much better the observations, which was clear from a strongly reduced value of RMSE, when considering that LAI comprises the leaf blade area only, without a photosynthetic contribution by stem green area. The model simulated rice growth very accurately until flowering. After flowering, however, divergences appeared and increased especially at the yellow ripe stage. From then on the crop did not grow much more, whereas it continued in the simulation. This reduction of growth rate was usually accompanied by an increase in the relative death rate of leaves and the drying of the grains. The main source of error may be a limited understanding of the ripening and sink limitation processes. A considerable yield gap between potential and observed yield remained. A climatic variability assessment over 10 years, from 1987 to 1996, showed a small but correlated variation (r=0.7) in both simulated and measured rice yields.     

Estimating vertical vegetation density through a SPOT5 imagery at multiple radiometric correction levels

There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces.A widely used parameter for such density,i.e.,leaf area index (LAI),was measured in situ in Nanjing,China and then correlated with two vegetation indices (VI) derived from multiple radiometric correction levels of a SPOT5 imagery.The VIs were a normalized difference vegetation index (NDVI) and a ratio vegetation index (RVI),while the four radiometric correction levels were i) post atmospheric correction reflectance (PAC),ii) top of atmosphere reflectance (TOA),iii) satellite radiance (SR) and iv) digital number (DN).A total of 157 LAI-VI relationship models were established.The results showed that LAI is positively correlated with VI (r varies from 0.303 to 0.927,p < 0.001).The R 2 values of "pure" vegetation were generally higher than those of mixed vegetation.The average R 2 values of about 40 models based on DN data (0.688) were higher than that of the routinely used PAC (0.648).Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction levels,indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion.The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images,thus improving accuracies of LAI estimation.     

高寒矮嵩草草甸地上生物量和叶面积指数的季节动态模拟

基于2007年中国科学院海北高寒草甸生态系统定位站植被和气象观测资料,探讨了高寒矮嵩草草甸群落叶面积指数、地上生物量的季节动态变化及其数学模型,分析了叶面积指数与地上生物量的相互关系,以及气象条件对叶面积指数和地上生物量的影响。结果表明,高寒矮嵩草草甸群落植被生长期地上生物量的季节动态变化可以用Logistic回归模型拟合;植被叶面积指数的季节动态变化可以用三次函数曲线拟合,叶面积指数受温度和降水量的影响明显,与植物生长期日平均气温≥3℃的积温和降水累积量分别有三次函数的拟合关系,而考虑与积温和降水累积量的综合关系可用二元二次函数拟合;同时,叶面积指数与地上生物量之间有二次函数的拟合关系。     

基于PROSAIL模型及TM与实测数据的MODIS LAI精度评价

利用PROSAIL模型和TM影像反演的叶面积指数LAI及地面实测数据,从空间和时间序列上分别对吉林省主要玉米种植带的MODIS LAI产品精度进行验证分析,为准确评价和科学准确应用MODIS数据提供科学依据。研究结果表明,MODIS LAI产品精度因玉米生长时期和植被类型而异,混合像元是造成MODIS LAI产品低估玉米作物LAI值的主要原因之一;不同年份不同生长时期,MODIS LAI和实测数据表现出不同的关系;在玉米生长灌浆期之后,MODIS LAI产品与同期地面实测玉米LAI相比,约低估了33%～53%左右,MODIS LAI产品值明显低于TM影像反演的LAI值,约低估玉米LAI值约30%～69%左右。因MODIS LAI产品值与实际值有较大偏差,非常有必要对农作物MODIS LAI产品值进行验证分析,研究结果可为准确利用MODIS LAI产品及其算法改进后产品精度提供一种评价途径。     

基于反射光谱的不同播期冬小麦LAI监测研究

为利用遥感技术快速、无损伤监测不同播期冬小麦LAI,通过大田和室内试验,对5个不同播期处理的冬小麦LAI进行了测定,并在此基础上建立了基于反射光谱的不同播期冬小麦LAI监测模型。结果表明,在4个播期处理和一个所有播期组合下所建立的LAI监测光谱模型中,以播期3条件下的PVI(1460,460)和LAI相关性最好,决定系数可达0.8296,播期3是监测冬小麦LAI的最适播期,依此所建立的冬小麦LAI监测光谱模型是可行的。同时,所有播期组合的LAI与PVI(1460,460)也有较高的相关性,说明在此基础上所建立的模型具有较好的普适度,这为冬小麦品质的大尺度遥感监测和小麦生产的宏观管理调控提供理论依据。     

黑河流域叶面积指数的遥感反演

以黑河流域为研究区 ,探寻基于TM影像提取的植被指数 (VIs)与野外实测数据间叶面积指数 (LAI)的反演研究。结果表明 ,各植被指数与LAI均具有较高的相关性 ,整个研究区土壤调整植被指数 (SAVI)具有最高的LAI反演精度 ;把研究区分成绿洲区和山区 ,各种植被指数与LAI的相关系数和反演精度均有很大程度提高 ,同时得到绿洲区SAVI最适于反演LAI ,山区SR最适于反演LAI ,通过这种方式估算出黑河流域叶面积指数图。