改进的混合像元分解法用于快速水污染遥感评价研究

该文介绍了一种改进的混合像元分解方法。利用该方法对滇池的各类污染（叶绿素,营养盐等）进行快速评价,可以直接得出滇池各个区域所受各类污染的程度,从而给出滇池全区各类污染的情况分布。     

混合光谱分解模型提取水体叶绿素含量的研究

遥感监测水体叶绿素含量是水质遥感研究的难点之一。本文通过研究不同叶绿素含量水体反射率的光谱特征，确定了提取叶绿素a含量的最佳特征波段，建立了太湖水体叶绿素a的混合光谱模型。研究发现，混合光谱模型提取的水体叶绿素a百分比浓度与同步采样分析的叶绿素a浓度之间有较好的线性相关性。并基于TM和HEPERION图像利用此模型生成了叶绿索a浓度分布图。研究结果表明，混合光谱分解模型可以作为遥感监测水体叶绿素a含量的定量模型。     

基于支撑向量机概率输出的高光谱影像混合像元分解

提出利用支撑向量机（SVM）后验概率来分解高光谱影像的混合像元，通过支撑向量机的输出值转化为两两配对的后验概率，再由两两配对的概率值求得多类后验概率，并以像元所属类别的后验概率作为地物的组分信息。实验结果表明，该方法能较好地估计出混合像元的组分比。     

基于等高线构建TIN模型的平三角形修正算法

设计了一种平三角形修正算法来修正TIN模型中可能出现的平三角形区域。该算法通过对由平三角形组成的区域进行分类,并针对不同的平区域采用交换边、增加点甚至不处理的修正方法,同时对由于等高线数据错误产生的一些特殊情况进行了分析处理。实验结果表明,该算法能够去除约束型狄洛尼三角网中所有应修正的平三角形,并生成对地形描述更为精确的三角网。     

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。     

一种多/高光谱遥感图像端元提取的凸锥分析算法

凸锥分析方法常用于多光谱和高光谱遥感图像的端元提取。遥感图像中的每个像元都可以看作一个多维向量,整幅影像看作由离散的非负向量构成的凸锥,通过寻找凸锥的角点来自动获取图像的端元。本文提出了一种自动选择最佳凸锥角点的方法,应用到传统的凸锥分析方法中,提高了凸锥分析方法的效率。利用模拟数据和真实数据实验验证了算法的可行性。     

An integrated wavelet concept of physical geodesy

For the determination of the earth's gravity field many types of observations are nowadays available, including terrestrial gravimetry, airborne gravimetry, satellite-to-satellite tracking, satellite gradio-metry, etc. The mathematical connection between these observables on the one hand and gravity field and shape of the earth on the other is called the integrated concept of physical geodesy. In this paper harmonic wavelets are introduced by which the gravitational part of the gravity field can be approximated progressively better and better, reflecting an increasing flow of observations. An integrated concept of physical geodesy in terms of harmonic wavelets is presented. Essential tools for approximation are integration formulas relating an integral over an internal sphere to suitable linear combinations of observation functionals, i.e. linear functionals representing the geodetic observables. A scale discrete version of multiresolution is described for approximating the gravitational potential outside and on the earth's surface. Furthermore, an exact fully discrete wavelet approximation is developed for the case of band-limited wavelets. A method for combined global outer harmonic and local harmonic wavelet modelling is proposed corresponding to realistic earth's models. As examples, the role of wavelets is discussed for the classical Stokes problem, the oblique derivative problem, satellite-to-satellite tracking, satellite gravity gradiometry and combined satellite-to-satellite tracking and gradiometry. Received: 28 February 1997 / Accepted: 17 November 1997     

煤炭地下气化区高密度三维地震勘探技术研究

地下煤层气化的燃烧范围,气化燃烧热力影响边界、形态、方向,气化区冒落带的发展高度及气化煤层裂隙发育程度,是开展煤炭地下气化工程迫切需要解决的问题。基于煤炭地下气化工程试验区地震地质情况,从地震响应入手,在分析煤炭地下气化后地震波场响应特征的基础上,提出了运用高密度三维地震采集技术结合全三维地震属性解释技术,高精度识别煤炭地下气化燃烧范围、气化热力影响边界的方法。实际勘探成果表明,本方法地震成像清晰,预测精度高,与钻探结果吻合较好。     

Quantifying uncertainty in remote sensing-based urban land-use mapping

Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at sub-pixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map – indicating absence of bias in the mapping process – it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth.