基于神经网络方法的芦苇叶面积指数遥感反演

提出了一种从TM图像上获取芦苇冠层叶面积指数的方法:首先对芦苇的生长背景进行分类;然后,对不同的背景光谱利用冠层反射率(FCR)模型计算得到查找表;最后,利用实测数据和查找表中的数据作为参数进行BP神经网络模型训练,从而得到芦苇冠层LAI。结果表明,人工神经网络方法有很强的非线性拟合能力,能够消除背景对反演结果的影响,有效提高LAI反演的精度。     

基于植被信息遥感反演的东亚飞蝗监测研究

植被是东亚飞蝗发生和成灾的重要指示因子。运用遥感技术对植被生长进行监测,对东亚飞蝗的预测和防治具有重要意义。以河北省黄骅市为研究区,利用实地获取的植被冠层孔隙度数据反算的LAI数据以及Landsat-5 TM影像提取的各种VI数据,进行了LAI(LAI-2000改进型算法的反算结果)与TM影像上反演的VI之间的相关分析。结果表明,RDVI最适合反映研究区植被生长状况。分析RDVI与飞蝗发生面积的关系,发现两者呈负线性相关,即随着RDVI减小,飞蝗的发生面积呈线性增大。     

山西霍山植物群落主要层LAI垂直分布规律

在山西霍山七里峪林场，采用间接的光学测量方法对沿着海拔分布的植物群落主要层叶面积指数（LAI）进行了测量，从不同的角度对LAI的垂直分布规律进行分析。结果表明：1．海拔不同，LAI表现出很大的差异，海拔1750m左右的LAI值大于较高与较低海拔的；对LAI和海拔之间的关系进行回归，得到LAI分布的拟合方程：y=b0＋b1x＋b2x^2＋b3x^3（R=0．712，P〈0．01）。2．同一海拔样带，阴坡LAI均大于阳坡，但对同种种群来说，阴坡树种平均胸径并不一定均大于阳坡。3．植被类型LAI比较表现为：低山针叶林〈低山灌丛〈落叶阔叶林〈落叶针叶林〈常绿针叶林；而主要群系LAI比较表现为：油松林（0．38）〈落叶松林（0．78）〈山杨林及其混交林（1．09）〈白桦林（2．00）〈辽东栎林及其混交林（3．73）。4．典型群落LAI值变化分析和人工林与天然林以，比较表明，LAI值在一定海拔达到最大值，这对于山西霍山人工林栽培和丰产林培育等具有重要意义。     

叶面积指数(LAI)的遥感定量方法综述

总结了当前遥感定量研究叶面积指数(LAI)的两种主要方法:统计模型法和光学模型法,阐述了各自的机理和研究进展,在此基础上,讨论了两种方法的优缺点及未来的发展趋势。     

基于新型机载多角度传感器AMTIS的LAI反演

以实地测量数据为先验知识,利用AMTIS数据对顺义地区的一块小麦地进行了叶面积指数(LAI)反演实验研究,并用实地LAI数据进行了验证。通过利用实测数据作为模型参数,以及对干湿土壤分类和匹配表的调整,使反演结果和反演速度得到了提高。     

水稻叶面积指数的高光谱遥感估算模型

通过不同氮素营养水平的水稻田间试验 ,采用单变量线性与非线性拟合模型和逐步回归分析 ,用1 999年试验数据为训练样本 ,建立水稻LAI的高光谱遥感估算模型 ,用 2 0 0 0年试验数据作为测试样本数据 ,对其精度进行评价和验证。结果表明 ,高光谱变量与LAI之间的拟合分析中 ,蓝边内一阶微分的总和与红边内一阶微分的总和的比值和归一化差植被指数是最佳的变量     

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.     

中国区域MuSyQ叶面积指数产品验证与分析

对多源遥感数据协同生产的2010年—2015年中国区域1 km空间分辨率5天合成的MuSyQ（Multi-source data Synergized Quantitative remote sensing production system）叶面积指数LAI产品进行验证。参考现有的LAI产品（MODIS c5，GLASS LAI）和中国生态系统研究网络部分农田和森林站点可用的LAI地面测量数据，从时空连续性、时空一致性、精度和准确性等方面对中国区域的MuSyQ LAI产品进行定性和定量分析与评价。结果表明：（1） MuSyQ LAI产品在保证精度优于MODIS产品的情况下，时间分辨率和时空连续性均有提高。MuSyQ LAI与其他LAI产品（MODIS c5，GLASS LAI）在整体上有很好的一致性（RMSE=1.0，RMSE=0.81），但对常绿阔叶林高值处的描述不稳定；（2） 与LAI地面测量数据相比，MuSyQ LAI产品与地面参考图对比结果较好（最高相关性（R²=0.54）和较低总体误差（RMSE=0.96）），其在阔叶作物生长季高值处有些许低估且在某些阔叶林站点有些高估。整体上，MuSyQ LAI产品呈现出较高的精度，可靠的空间分布和连续稳定的时间分布，且对森林LAI的描述具有更可靠的动态范围。     

On the relationship between historical land‐use change and water availability: the case of the lower Tarim River region in northwestern China

Natural ecosystems in the region of the lower Tarim River in northwestern China strongly deteriorated since the 1950s due to an expanding desertification. As a result, the downstream Tarim River reaches became permanently dry land. This historical evolution in land‐use change is typically the result of the anthropogenic impact on natural ecosystems. On the basis of a spatially distributed hydrological catchment model bidirectionally linked with a fully hydrodynamic MIKE11 river model, land‐use changes characterized by historical changes in leaf area index (LAI) of vegetation, as well as the evolution of irrigated surface areas, can be causally related to changes in water resources (groundwater storage and surface water resources). An increased surface area of irrigated (agricultural) land, together with a majority of inefficient irrigation methods, did lead to a strong increase of water resources consumption of the farmlands located in the upper Tarim River area. Evidently, this evolution influenced available water resources downstream in the Tarim basin. As a result, farmland has been gradually relocated to the upstream regions. This has led to reduced flows from the upper Tarim stream, which subsequently accelerated the dropping of the groundwater level downstream in the basin. This study moreover demonstrates that land surface biomass changes (cumulative LAI) along the lower Tarim River are strongly related to the changes in groundwater storage. Copyright © 2012 John Wiley & Sons, Ltd.     

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R² = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.