Leaf Area Index Estimation Using Time-Series MODIS Data in Different Types of Vegetation

The aim of this study is to estimate leaf area index (LAI) in different type of plants using vegetation indices (VIs) and neural network algorithms retrieved from MODIS data. Four VI were calculated, and neural networks were built up based on MODIS surface reflectance products. Among the tested VIs, normalized difference vegetation index (NDVI) and chlorophyll index (CI) appeared to be the best candidate indices in estimating LAI across sites with different vegetation types. The models having the highest accuracy were CI for grassland and deciduous broad leaf forest with determination coefficients (R-square above 0.70, and NDVI for crop R-square?=?0.78). Neural network showed better results than VI methods except in grassland sites. The added VI information showed no significant improvement of model accuracy for the neural networks in most sites.     

基于波谱知识库的MODIS叶面积指数反演及验证

目前用物理模型反演叶面积指数普遍存在缺少先验知识的状况，如何获得准确的先验知识是遥感走向应用的一个关键环节。中国典型地物标准波谱数据库就是结合国家重大行业中的应用需求，研究制定地物波谱获取与分析的技术规范和数据标准，建立典型地物标准波谱数据库。从波谱数据库提取模型反演所需要的先验知识，实现了基于SAIL模型的MODIS数据（经过几何纠正与大气纠正）叶面积指数的反演。另外，基于TM数据，对MODIS混合像元进行了分解，用纯像元的叶面积指数与实测数据进行对比验证，同时，反演结果与NASA的LAI产品也进行了对比，结果表明基于波谱库的先验知识可以有效的提高叶面积指数的反演精度。     

2003—2019年邯郸市叶面积指数时空变化特征

研究和掌握叶面积指数(LAI)时空变化特征,对区域植被保护、植树造林和环境保护具有重要的参考意义.本文以邯郸市为例,基于MCD15A3H遥感影像数据、DEM数据和土地利用等多元数据,引入Sen趋势与Mann-Kendall趋势检验分析方法,系统分析了邯郸市像素尺度上的LAI数值的变化特征,并基于不同的土地利用类型、不同...     

基于SAR数据的鄱阳湖水体提取及变化监测研究

以C波段Envisat ASAR和L波段ALOS PALSAR交替极化模式的数据为数据源,分析了鄱阳湖主要地物的散射特性,并分别引入纹理特征和不同极化通道间的极化差和极化比等参数增强地物的表征;应用主成分变换对地物的参数向量进行特征提取,增强水体与其他地物的差异,并在第一主成分中选择适当阈值,准确提取出不同时期的鄱阳湖水体信息。实验表明,用上述方法提取水体信息的精度比直接使用地物后向散射系数的监督分类法提取精度要高得多。通过分析和对比上述不同波段SAR数据中水体与其他类别间的Jeffries-Matusita距离可以看出,C波段SAR数据提取鄱阳湖水体的精度比L波段高。并给出了鄱阳湖水体在2007年春、夏和冬3个季节中水域面积的动态变化情况。     

MODIS遥感数据辅助的鄱阳湖水体范围变化数值模拟

针对水体范围高动态变化的鄱阳湖,充分发挥数值模拟和遥感各自的优势,使用从MODIS影像上提取的水体范围初始化鄱阳湖水体范围数值模拟边界和率定模型参数,并与模拟的水体范围结果进行交叉验证分析。对鄱阳湖2001-07-08～11-30水体范围动态变化数值模拟的结果显示,水位模拟平均绝对误差小于15cm,数值模拟获取的水体范围与MODIS无云影像提取的湖泊水体范围具有较高的一致性,水体面积平均相对误差为5.7%。     

鄱阳湖地区洪涝灾害遥感分析

鄱阳湖是一个吞吐型,季节性的浅淡水湖,高水湖相,低水河相。有“高水是湖,低水似河”,“洪水一片,枯水一线”的独特景观。洪涝灾害发生时,给周边地区造成巨大损失。利用TM遥感卫星图片,以特征最明显的1998年特大洪涝灾害为例,对鄱阳湖地区洪涝灾害症结和防洪策略提出几点见解。     

利用eCognition进行高分一号卫星数据土地利用现状解译能力测试

土地利用现状解译能力是卫星数据在土地资源领域应用的重要指标之一。本文以内蒙古自治区包头市石拐区和江苏省徐州市贾汪区作为研究区,利用eCognition软件采用面向对象分类的方法,通过初步影像分割、构建土地利用分类系统、标准化最邻近分类及对分类结果整理修改与分析,从中随机选取了不同地类、不同面积的图斑,以更高分辨率影像分类结果作为真值,进行了典型地类的属性精度、面积精度评价,从而对高分一号卫星数据的土地利用现状解译能力进行了测试与评定。     

基于高光谱数据和RBF神经网络方法的草地叶面积指数反演

基于中国农业科学院在呼伦贝尔草原实测的120组草地冠层光谱反射率及相应的叶面积指数(LAI)数据,在进行主成分分析(PCA)实现降维处理的基础上,利用径向基函数(radial basis function,RBF)神经网络方法对草地LAI进行了高光谱反演研究.PCA结果表明,前9个主成分的累积贡献率达到了99.782％,能包含原光谱数据的绝大部分信息.将120组LAI及相应的9个主成分样本数据随机分为校正集数据(90组)和预测集数据(30组),分别用于神经网络模型的建立和LAI的预测.所构建的神经网络模型的模拟结果表明,RBF神经网络模型对校正集样本的模拟准确率达到100％(RMSE =0.009 6,R2 =0.999);预测集样本的实测LAI和模拟LAI之间的均方误差和决定系数分别为0.218 6和0.839,取得了较好的模拟效果,有效提高了传统的多元线性回归方程(RMSE =0.416 5,R2=0.570)的计算精度.     

Integration of Landsat ETM+ Data with Field Measurements for Mapping Leaf Area Index in the Grasslands of Central Kazakhstan

A fine-resolution leaf area index (LAI) data set over a 150 km × 150 km region in central Kazakhstan is retrieved using Landsat ETM+ imagery and ground-based LAI inferred from hemispherical photography and direct measurements. Regression analysis and geostatistics are applied for developing empirical models of LAI from Landsat ETM+ data. The best accuracy is achieved using a model employing a canonical index that combines all the contributions of individual Landsat ETM+ bands into a single index (R ² = 0.67; RMSE = 0.21). This model is then applied for mapping LAI at a regional scale.     

利用多源影像数据进行建筑物变化监测的方法研究

城市内加盖、扩建违法建筑物现象严重,如何快速准确地获取城市建筑物的基本情况,监测出违法建筑物信息,成为城市规划、建设部门的一个迫切问题;根据不同时期数字表面模型(DSM)差值比对可以获取建筑物高度变化的原理,通过对雷达及光学卫星影像各自特征的对比,提出了利用多源影像数据,快速准确的发现建筑物变化信息的方法。     

Spatially Explicit Estimation of Leaf Area Index Using EO-1 Hyperion and Landsat ETM+ Data: Implications of Spectral Bandwidth and Shortwave Infrared Data on Prediction Accuracy in a Tropical Montane Environment

This study evaluated the utility of narrowband (EO-1 Hyperion) and broadband (Landsat ETM+) remote sensing data for the estimation of leaf area index (LAI) in a tropical environment in Sulawesi, Indonesia. LAI was inferred from canopy gap fraction measurements taken in natural tropical forest and cocoa plantations. Single and multiple spectral bands and spectral indices were used as predictor variables in reduced major axis (RMA) and ordinary least squares (OLS) regression models. The predictive power of most regression models was notably higher when employing narrowband data instead of broadband data. Highly significant relationships between LAI and spectral reflectance were observed near the red-edge region and in most shortwave infrared (SWIR) bands. In contrast to most near-infrared (NIR) narrow bands, the correlation between SWIR reflectance and LAI was not confounded when including both vegetation types and did not suffer from saturation. The results demonstrate that leaf area index of a challenging tropical environment can be estimated with satisfactory accuracy from hyperspectral remote sensing data.     

植被冠层光谱和叶片光谱的尺度转换

叶面积密度可以表征冠层内部叶面积的垂直分布,是作物生长发育、营养诊断和育种研究的重要结构参数。激光雷达通过发射多脉冲和接收多回波信号可以探测到作物冠层内部信息。首先基于无人机激光雷达获取60个小区多航线的玉米点云数据,采用基于接触频率的体素法对叶面积密度进行估算,再对多个体素大小进行分析得到最优体素大小（0.2 m）;其次对各航线以及航线叠加效果进行对比,得到无人机激光雷达获取点云数据的最优激光脉冲入射角（-30°~52°）;然后结合玉米叶倾角和激光脉冲入射角对叶面积密度估算模型进行校正,从而提高叶面积密度估算精度;最后通过对不同种植密度和不同品种的玉米叶面积密度分布进行分析,得到不同品种玉米的发育快慢、株型特点以及最合理的种植密度。以上结果可为基于无人机激光雷达数据估算叶面积密度提供指导,并为玉米育种和科学管理提供参考。     

Intercomparison and validation of MODIS and GLASS leaf area index (LAI) products over mountain areas: A case study in southwestern China

The validation study of leaf area index (LAI) products over rugged surfaces not only gives additional insights into data quality of LAI products, but deepens understanding of uncertainties regarding land surface process models depended on LAI data over complex terrain. This study evaluated the performance of MODIS and GLASS LAI products using the intercomparison and direct validation methods over southwestern China. The spatio-temporal consistencies, such as the spatial distributions of LAI products and their statistical relationship as a function of topographic indices, time, and vegetation types, respectively, were investigated through intercomparison between MODIS and GLASS products during the period 2011–2013. The accuracies and change ranges of these two products were evaluated against available LAI reference maps over 10 sampling regions which standed for typical vegetation types and topographic gradients in southwestern China.The results show that GLASS LAI exhibits higher percentage of good quality data (i.e. successful retrievals) and smoother temporal profiles than MODIS LAI. The percentage of successful retrievals for MODIS and GLASS is vulnerable to topographic indices, especially to relief amplitude. Besides, the two products do not capture seasonal dynamics of crop, especially in spring over heterogeneously hilly regions. The yearly mean LAI differences between MODIS and GLASS are within ±0.5 for 64.70% of the total retrieval pixels over southwestern China. The spatial distribution of mean differences and temporal profiles of these two products are inclined to be dominated by vegetation types other than topographic indices. The spatial and temporal consistency of these two products is good over most area of grasses/cereal crops; however, it is poor for evergreen broadleaf forest. MODIS presents more reliable change range of LAI than GLASS through comparison with fine resolution reference maps over most of sampling regions. The accuracies of direct validation are obtained for GLASS LAI (r = 0.35, RMSE = 1.72, mean bias = −0.71) and MODIS LAI (r = 0.49, RMSE = 1.75, mean bias = −0.67). GLASS performs similarly to MODIS, but may be marginally inferior to MODIS based on our direct validation results. The validation experience demonstrates the necessity and importance of topographic consideration for LAI estimation over mountain areas. Considerable attention will be paid to the improvements of surface reflectance, retrieval algorithm and land cover types so as to enhance the quality of LAI products in topographically complex terrain.     

The Second Modified Perpendicular Drought Index (MPDI1): A Combined Drought Monitoring Method with Soil Moisture and Vegetation Index

Since soil moisture and vegetation index are direct and important indicators for surface drought status, a new drought monitoring method (MPDI1) is developed in NIR-Red reflectance space. It is a combination of two satellite-derived variables—a soil moisture component using the Perpendicular Drought Index (PDI), and a vegetation component using the Perpendicular Vegetation Index (PVI). Enhanced Thematic Mapper Plus (ETM+) image and in-situ ground observation are introduced to validate the accuracy of the proposed method. Results indicate that MPDI1 is highly consistent to the in-situ ground observation with the coefficient of determination (R²?=?0.49) between MPDI1 and 5–20 cm mean soil moisture, which is slightly higher than the coefficient of determination (R²?=?0.42) between MPDI1 and 10 cm soil moisture. Compared with drought indices such as PDI and the Modified Perpendicular Drought Index (MPDI), MPDI1 provides quite similar trends for bare soil or lower vegetated surface, but it demonstrates a better performance in measuring densely vegetated surface. This paper concludes that MPDI1 provides correct and sufficient information on surface drought status in soil-plant continuum, which appears to have robust available and great potential for surface drought estimation in China and other countries.     

基于HJ-1A/B CCD数据的东湖叶绿素a浓度反演可行性研究

以武汉东湖为研究区域,利用HJ-1A/B CCD数据和地而准同步叶绿索a浓度实测数据,建市适合东湖水体的叶绿素a浓度遥感定量估算模型,从而分析HJ-1A/B CCD数据应用于内陆湖泊水体叶绿素a浓度反演的可行性.     

一种利用历史DLG数据辅助优化数字正射影像镶嵌线生成的方法

为了提升大面积数字正射影像图生产的效率,介绍了一种利用历史DLG数据辅助优化数字正射影像镶嵌线生成的方法,通过对DLG数据处理,提取出区域具有地物的面层,生成避让区域,在此基础上再考虑镶嵌线尽可能穿过原始DLG中较少的面及色差较小的区域,使用贪婪蛇模型算法实现了优化镶嵌线的生成。通过生产试验,证明了该方法可部分减少镶嵌线编辑的工作量。     

HJ-1光学遥感影像船只检测——以鄱阳湖为例

以具有高时空分辨率、长时间序列观测优势的国产HJ1CCD数据,在使用面向对象方法实现水面均质区域分割的基础上,改进传统的Contrastbox方法,增强了船只目标与背景像素的对比,实现了水面状况复杂的鄱阳湖船只提取。使用该方法分别对鄱阳湖枯水、丰水期HJ1CCD数据进行船只检测实验,经精度验证,船只检测率可达85%。对比传统阈值提取方法,该方法在浑浊复杂水体中船只提取的优质因数(FoM)远优于传统方法。由于采砂、运砂、航运等人为水上活动对水生态环境产生的严重影响,亟需加强船只活动的有效监管。该研究为鄱阳湖船只检测、采砂、运砂活动及水环境检测提供了有效途径,也为其他湖泊、沿海等区域的船只检测提供了方法,同时提升了国产HJ卫星在环境检测中的应用能力。     

Interferometric SAR Time Series Analysis for Ground Subsidence of the Abandoned Mining Area in North Peixian Using Sentinel-1A TOPS Data

The North Peixian mining area of China has rich coal resources, with total proven reserves of 2.37 billion tons. However, the underground coal mining activities have resulted in ground collapse, which has caused serious harm to the environment and threatened the lives and properties of local residents. In this study, 12 Sentinel-1A terrain observation by progressive scans (TOPS) mode acquisitions between 30 July 2015 and 13 May 2016 over the abandoned mining area in North Peixian were analyzed using the interferometric synthetic aperture radar (InSAR) time series method to detect the ground subsidence, with the maximum ground subsidence reaching 83 mm/a and an average value of about 12.7 mm/a. The subsidence results derived from the Sentinel-1A TOPS mode dataset were proven to be effective in investigating and monitoring the ground subsidence in the North Peixian mining area. Compared to the rapid deformation during the ongoing period of mining excavation, the ground subsides slowly in abandoned mining areas and shows a linear relationship with time over a relatively long period of time. Spatial correlation between the subsidence distribution and land cover was found, in that the magnitude of the subsidence in urban areas was smaller than that in rural areas, which is associated with the controlled coal mining activities under buildings, railways, and water bodies. The results demonstrate that Sentinel-1A TOPS SAR images can be used to effectively and accurately detect and monitor ground subsidence in a mining area, which is critically important when investigating land subsidence in a large-scale mining area.     

利用ECMWF改善射线利用率的三维水汽层析算法

针对传统水汽层析技术只能利用完整穿过研究区域射线重构三维水汽的缺陷,提出了一种利用欧洲中尺度天气预报中心格网产品改善三维水汽反演射线利用率的方法。该方法通过引入比例因子,计算出侧面穿出射线在层析区域内的水汽含量,并参与观测方程的建立。利用香港卫星定位参考站网的实测全球定位系统和气象数据,结合该区域的无线电探空站45004和ECMWF格网点数据,对该方法的可行性及精度进行验证。试验结果表明：相对于传统方法,该方法的射线利用率和网格覆盖率分别提高了55.16%和16.46%;分别以探空数据和ECMWF格网数据为参考基准,发现提出的方法其均方根误差、平均绝对偏差和相对误差等均优于传统方法。     

同时改进背景值和初始条件的一种GM(1,1)预测方法

传统GM(1,1)模型在背景值和初始条件的选取方面存在不足,为了提高灰色GM(1,1)模型的预测精度和拟合精度,本文提出了一种同时改进背景值和初始条件选取的新模型,此模型对以往单独对背景值或初始条件的优化进行了改进,将两个影响条件整合到一起。最后通过实例将该新模型与几种模型的拟合和预测数据比较,显示出了新模型的预测精度高。