运用归一化光谱混合模型分析城市地表组成

运用归一化光谱混合分析(NSMA)方法,用ETM 数据调查广州市海珠区城市地表组成,采用亮度标准化方法减小亮度变化。通过标准化,使亮度差异在每个植被-非渗透性表面-土壤-水体(V-I-S-W)组成中减小或者消除,这样使得一个单一的端元能够代表一种地表组分。在此基础上,通过归一化影像,选择了植被、非渗透性表面、土壤和水体4种端元,运用一种约束光谱混合分析(SMA)模型,分解了不同种类的城市地表组成。通过与已有模型计算结果比较,认为本文所构建的模型较优,其对研究区非渗透性表面估计的均方根误差为12.6%。     

基于植被-土壤二向反射模型的土壤含水量遥感

以北京地区为例，利用像元信息分解法，定量提取出区域植被盖度，由植被盖度得到区域叶面积指数，在只考虑一次散射的情况下，利用植被-土壤二向反射模型，提取出下层湿润土壤反射率。通过引入粗糙度因子建立起粗糙地表下土壤反射率与叶面积指数的函数关系，进而得出土壤含水量。     

Spectral scaling in Mars topography: effect of craters

Extensive computer simulations aimed at testing a hypothesis that impact craters may explain the scaling behaviour of surface spectra are presented. The simulations show that indeed crater effects alone may explain the spectral scaling of Mars’ topography revealed from MOLA data. The range of the scaling exponents obtained for a wide range of simulation parameters does not exceed the limits observed for Mars. The simulations suggest that the shape of large craters is the key factor leading to the two scaling ranges in the surface spectra. Particular values of the scaling exponents may additionally depend on the depth-diameter relationship and the crater size distribution.     

微物理过程分档处理的三维对流云模式研究

在三维完全弹性冰雹云参数化模式动力框架和二维面对称分档模式(微物理过程分档处理)的基础上,建立粒子全分档的三维对流云分档模式.利用建立的分档模式对2000年6月29日美国堪萨斯州的一次超级单体风暴进行了模拟,并将模拟结果与三维冰雹云参数化模式的模拟结果作了对比.结果表明:分档模式可以较好地模拟出强对流云中两支上升气流,模拟得到的最大上升气流速度大于参数化模式;分档模式模拟得到的雷达回波强度、顶高和回波宽度更接近实测.     

基于MATLAB COM组件的变形监测与分析软件开发

论述了桥梁变形自动监测系统数据的频谱分析以及小波分析方法,并利用MATLAB编译的COM组件,实现了在VC中调用该COM组件以实现脱离MATLAB环境的变形分析软件开发。     

混沌功率谱熵方法在识别水淹低阻油层中的应用

储集层孔隙度和电阻率曲线间微差形态波形的复杂程度隐含着储集层含油气性的信息,可以用混沌动力学系统加以刻划。油层相空间庞加莱截面明显具有自相似结构,呈现混沌特性;而水淹层和水层的相空间庞加莱截面显示,其混沌性呈显著减弱之势,系统趋于简单有序。其功率谱密度不论水淹程度如何,整体为一随频率增大其能量按指数递减连续频谱;随水淹程度逐渐减弱,递减幅度减小,整体能量逐渐降低,某些频率成分被吸收削弱,由光滑状逐渐演变成锯齿起伏状,其功率谱熵逐渐增大。基于测井信息的混沌特征和功率谱熵特征识别水淹层的方法,对利用传统测井解释理论判别比较困难的低阻油层有较强的识别能力。     

陆相沉积的天文地层研究方法简介——以井下地层为例

通过对我国大陆三十余口井的测井资料研究成果,归纳出对陆相地层进行天文地层研究的方法。介绍了所用的新的天文周期理论值、测井资料的选取及预处理方法,重点说明谱分析的数据点数的选定、不同参数(自然伽玛、自然电位和岩屑)的测井资料谱分析结果的对比,以实例说明如何选定主要优势旋回和AR值,以及FIR数字滤波器的基本性质和数字滤波结果,小波分析的特点和通过小波图进行调频的方法,并介绍了地层单位的延续时间计算和年龄确定方法。     

Non-destructive estimation of potato leaf chlorophyll from canopy hyperspectral reflectance using the inverted PROSAIL model

Optimizing nitrogen (N) fertilization in crop production by in-season measurements of crop N status may improve fertilizer N use efficiency. Hyperspectral measurements may be used to assess crop N status by estimating leaf chlorophyll content. This study evaluated the ability of the PROSAIL canopy-level reflectance model to predict leaf chlorophyll content. Trials were conducted with two potato cultivars under different N fertility rates (0–300 kg N ha⁻¹). Canopy reflectance, leaf area index (LAI) and leaf chlorophyll and N contents were measured. The PROSAIL model was able to predict leaf chlorophyll content with reasonable accuracy later in the growing season. The low estimation accuracy earlier in the growing season could be due to model sensitivity to non-homogenous canopy architecture and soil background interference before full canopy closure. Canopy chlorophyll content (leaf chlorophyll content × LAI) was predicted less accurately than leaf chlrophyll content due to the low estimation accuracy of LAI for values higher than 4.5.     

基于高光谱遥感数据提取森林结构参数的研究

以位于三峡库区的龙门河森林自然保护区为研究区,综合利用线性光谱混合模型和几何光学模型,基于高光谱遥感数据提取森林结构参数是本文研究的重点。在研究区地面调查数据的基础上,通过高光谱数据和混合光谱分解法,获得反演几何光学模型所需的四分量参数,根据背景光照分量与森林植被冠层各参数间的关系,反演得到森林冠层郁闭度及平均冠幅的定量分布图,并利用37个野外实测样本进行结果验证。     

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise.In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical–empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections.The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.