混合像元聚集指数研究及尺度分析

本文提出了一种新的混合像元聚集指数计算方法。该方法基于高分辨率遥感数据,采用方向孔隙率公式和线性混合模型相结合的方法,详细描述了混合像元内部由于植被覆盖度(FVC)、端元聚集指数以及叶倾角分布等引起的尺度差异。利用模拟数据进行初步敏感性分析,将计算得到的混合像元聚集指数与所占面积比例最大的端元聚集指数进行比较,结果表明端元聚集指数的不均一性对计算结果影响最大,由此得到的混合像元聚集指数较最大面积端元聚集指数下降了55%;植被覆盖度的不均一性影响次之,可使聚集指数降低43%;植被叶倾角分布(G函数)的空间异质性影响最小,约12%。敏感性分析的结果同时也证明了对于空间异质性较强的混合像元进行尺度差异修正的必要性。利用本文中提出的混合像元聚集指数方法有望在提高低分辨率叶面积指数反演中发挥重要作用。     

Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region,USA

A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km² Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R² value of 0.72 and average root mean square error (RMSE) of 0.042.     

基于GF-2影像的广西茅尾海红树林物种分类及盖度估算分析

为了掌握茅尾海红树林种类和盖度情况,基于GF-2 PMS1高分辨率卫星遥感影像数据,使用支持向量机(support vector machine,SVM)和回归模型方法开展了茅尾海红树林物种分类和植被盖度估算研究,并对其分布特征展开了详细分析。研究表明:(1)广西茅尾海红树林共有4个种类,分别是桐花树(Aegiceras corniculatum)、无瓣海桑(Sonneratia apetala)、秋茄(Kandelia candel)和茳芏(Cyperus malaccensis)。桐花树作为茅尾海红树林的优势种,面积为1228.612 ha,占总面积72.5%,散布在茅尾海潮间带。秋茄面积最少,仅有1.976 ha,零星分布于茅岭乡和尖山镇沿岸,多数与无瓣海桑和桐花树混生。(2)基于GF-2 PMS1卫星影像的NDVI植被指数建立的二次多项式盖度回归模型效果最好,决定系数最大为0.7644,均方根误差RMSE最小为0.0680。(3)植被盖度分布状况与植被类型有密切关系,植被种类纯生区的盖度要明显大于植被混生区的盖度。本研究结果为茅尾海国家海洋公园和自治区级自然保护区管理部门的决策提供理论基础。     

MODIS observed snow cover variations in the Aksu River Basin,Northwest China

A major proportion of discharge in the Aksu River is contributed from snow-and glacier-melt water.It is therefore essential to understand the cryospheric dynamics in this area for water resource management.The MODIS MOD10A2 remotesensing database from March 2000 to December 2012 was selected to analyze snow cover changes.Snow cover varied significantly on a temporal and spatial scale for the basin.The difference of the maximum and minimum Snow Cover Fraction(SCF)in winter exceeded 70%.On average for annual cycle,the characteristic of SCF is that it reached the highest value of 53.2%in January and lowest value of 14.7%in July and the distributions of SCF along with elevation is an obvious difference between the range of 3,000 m below and 3,000 m above.The fluctuation of annual average snow cover is strong which shows that the spring snow cover was on the trend of increasing because of decreasing temperatures for the period of 2000-2012.However,temperature in April increased significantly which lead to more snowmelt and a decrease of snow cover.Thus,more attention is needed for flooding in this region due to strong melting of snow.     

一种基于归一化扰动模型的积雪和植被覆盖度反演方法

积雪和植被的覆盖范围对于研究气候变化和水资源平衡、生态环境状况具有重要的意义,但它们的光谱曲线具有较强的时空变异性,难以获取精确的覆盖度产品。针对线性混合像元分解算法在积雪和植被覆盖度反演中噪声和光谱变异带来的误差,本文提出了一种基于归一化扰动模型的积雪和植被覆盖度反演方法,并选用了3个不同的区域（单独的积雪覆盖区、单独的植被覆盖区、积雪和植被混合的覆盖区）来验证所提出框架的可行性。研究结果表明：① 该方法单独反演积雪覆盖度的均方根误差为0.172,单独植被覆盖度反演均方根误差为0.223,积雪和植被覆盖度混合反演的均方根误差分别为0.185和0.249,3种方案均有较高的精度;② 对影像与端元组进行归一化后,降低了光谱异质性,在此方法下的扰动混合模型可以有效地减弱MODIS影像光谱变化和噪声带来的误差;③ 针对MODIS影像,该框架获取的积雪覆盖度相对于植被覆盖度具有更高的精度。今后将进一步发展类似的积雪覆盖度与雪粒径协同反演算法。     

Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land use/land cover,vegetation cover changes estimated using multi-source satellite data

The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam.     

基于相对密度和X射线粉晶衍射技术测定硬玉岩中硬玉的含量

硬玉岩能否命名为宝石级"翡翠",其硬玉的含量是关键参数,目前测量岩石中矿物质量分数的方法多为有损分析,难以应用于珠宝玉石检测中。本文基于硬玉岩矿物组成及其质量分数的变化,建立了一种通过测量硬玉岩相对密度获得硬玉质量分数的无损分析方法。对186件相对密度在3.30~2.88之间的硬玉岩样品采用静水称重法测试,根据相对密度范围进行分组,利用X射线粉晶衍射、人工重砂分析、电子探针、红外光谱、拉曼光谱等技术确定硬玉岩的主要矿物及其质量分数,进而统计分析硬玉质量分数与硬玉岩相对密度的线性关系。研究表明:硬玉岩的主要矿物为硬玉和杂质矿物钠长石、方沸石。随着硬玉的质量分数(wA)下降,钠长石、方沸石质量分数增加,硬玉岩实测相对密度(SG)发生相应变化,两者的线性方程为wA=1.3454×SG-3.4531(相关系数为0.9814),线性关系良好。由于本方法的硬玉岩实测相对密度近似等于理论相对密度,即可通过测量相对密度获得硬玉的质量分数,这种无损测试方法适用于相对密度在3.3~3.0,硬玉含量在95%~60%,硬玉与钠长石的质量分数之和在90%~97%之间的硬玉岩样品。     

地面LiDAR数据模拟及单木LAI反演

地面激光雷达Li DAR可以快速获取高精度、高密度的点云数据,在植被结构参数获取方面的应用越来越广泛。为了定量分析地面激光雷达点云数据获取单木结构参数的能力和精度,本文提出利用光线跟踪结合植被真实结构模拟地面3维激光扫描仪的单木点云数据(以RIEGL VZ-1000为例),并结合间隙率模型反演单木叶面积指数LAI。在点云模拟过程中,充分考虑了脉冲特性,包括光斑大小、波束发射角以及回波探测强度。重点分析了光斑大小和最小探测强度对LAI反演的影响,并采用根河实测单木数据进行了验证。结果表明,光斑大小和最小探测强度的设定对于LAI反演结果存在很大影响,该结论对于提高地面激光雷达点云数据反演植被结构参数精度具有重要意义。     

联用高斯求积与连分式求和计算Hankel变换及在地球物理上的应用

光学、电磁学和地震学都需要计算Hankel变换。除少数核函数的Hankel变换有解析式,绝大多数的通常采用数值积分的方法对其近似计算。虽然数字滤波法是常规的计算方法,但由于滤波系数的不统一,导致计算结果并不完全一致,甚至在某些情况结果是错误的。为了解决这个问题,采用直接数值积分的方法计算Hankel变换。具体过程是:首先将Hankel变换分解为积分限从零到Bessel函数的第一个零点值的积分段和后续各相邻零点值作为积分限的积分段的和,然后用高斯求积计算每段积分。对高斯求积结果组成的序列采用连分式求和,无论是计算结果的精确性还是收敛速度都要优于直接求和。这里首先详细阐述了联用高斯求积与连分式求和计算Hankel变换的基本原理和相关算法,然后用Matlab编程对比了直接求和与连分式求和的计算效果,最后将此方法应用于电偶源在均匀半空间激发的地下场计算的两个实例中。应用表明:将高斯求积与连分式求和进行联用是计算Hankel变换的一种有效方法,可以广泛应用于地球物理应用中。