基于JPEG2000无损压缩的DEM网络渐进传输方法

针对网络GIS海量DEM数据与有限带宽之间的矛盾,根据DEM数据特点和网络多分辨率渐进的应用需求,提出了一种在DEM各级分辨率具有良好精度性能、基于改进的JPEG2000高效无损压缩的DEM网络渐进传输方法。选用2/6整数小波分解DEM数据,利用辖区渐进压缩方法、压缩码流的索引文件检索码流实现了DEM的渐进传输。实验证明,2/6小波比标准中的5/3小波能够更好地在每级分辨率保持原始地形精度,相比传统方法,网络渐进传输时每级分辨率传输的数据量平均减少了90.29%。     

一种新型的遥感影像压缩质量评价指标

针对遥感影像的特性,提出了一个用于压缩质量评价的多维结构模型,该结构模型由影像特征畸变、纹理畸变和相关性损失三个“维”组成,在此基础上提出一种新的构像质量综合性评价指标。实验证明,该指标与传统的PSNR指标相比,与主观评价结果具有较好的吻合性。     

彩色印刷复制中色差公式加权系数的计算和可接受阈值的评价

对印在有光泽的铜版纸上的9个颜色中心、共216种颜色色样进行了视觉评价和客观测量,得出了每种颜色中心的色差的可接受阈值;然后,应用视觉评价标准确定了可用于CIE94、CMC和CIE2000中的最佳l∶c加权系数,并将ΔE94(l∶c)、ΔEcmc(l∶c)、DE2000(l∶c)与ΔEab进行了比较。     

全国及部分省市地区高精度、高分辨率大地水准面的研究及其实施

结合我国重力和地形资料及国内外较优的重力场模型,研制了适合我国重力场特征的360阶重力场模型WDM94,建立了中国新一代包括全部陆海国土的dm级(似)大地水准面CQG2000,建立了中国以GPS/水准为基础的高程异常控制网,利用海洋卫星测高数据进行我国海洋大地水准面的计算、我国陆地重力(似)大地水准面的研制及我国陆海(似)大地水准面的拼接;研制了江苏省、海南省、深圳市、大连市、南京市及南水北调西线工程具有cm级精度的省市地区(似)大地水准面模型;结合GPS技术和高精度(似)大地水准面模型,研制了GPS测图软硬件一体化系统。     

过去2000年典型暖期北半球温度变化特征及成因分析

过去2000年包含了罗马暖期（Roman Warm Period,简称RWP）、中世纪气候异常期（Medieval Climate Anomaly,简称MCA）和现代暖期（Present Warm Period,简称PWP）这3个典型暖期,前人对罗马暖期的关注相对较少。为了更好地对比自然暖期和叠加了人类活动的暖期的温度变化特征及成因,文章利用通用地球系统模式（Community Earth System Model,简称CESM）的过去2000年气候模拟试验资料,在与重建资料和同化资料（Last Millennium Reanalysis,简称LMR）进行对比验证的基础上,对这3个典型暖期北半球的温度变化特征和成因机制进行了初步探讨。结果表明：CESM的全强迫试验能很好地模拟出重建资料与LMR所反映的两个自然暖期（RWP和MCA）以及PWP,PWP相较于RWP和MCA北半球增温幅度明显更大。通过对比单因子敏感性试验结果发现,RWP时期主要受土地覆盖变化的影响,同时太阳活动、火山活动强迫对地表增温有一定调节作用;而MCA时期的火山活动频率相比RWP时期更小,且太阳活动稳定,此时土地覆盖的调节作用相比RWP时期减弱;PWP时期在温室气体强迫驱动下,地表温度增加显著,其贡献远超过火山活动、太阳活动两个外强迫因子,此时土地利用/覆盖强迫对增温显示出负向影响,同时北极涛动增强,进一步加剧PWP时期的增温。

     

2000年下半年全球地震活动

2000年下半年全球共发生Mw≥6．5地震27次，其中23次为浅源地震，深源地震4次。发生Mw≥7．0地震5次，最大震级达Mw8．0。11月16日和17日，在俾斯麦群岛和所罗门群岛交界地区，发生了3次Mw≥7．8地震。2000年，全球地震活动处于1976年以来的较高水平。     

GNSS控制网坐标移动转换的三次曲面拟合法

针对2000国家大地坐标到海南独立坐标系需要保密参数的局限性,该文利用三次曲面拟合坐标移动转换法进行2000国家大地坐标系到海南独立坐标转换,解决了在没有海南独立坐标系参数的情况下无法进行坐标转换的困扰,确保参数保密性。测试比较结果表明,三次曲面拟合法移动坐标转换法能够提高坐标转换精度。     

基于CGCS2000地心独立坐标系基准确定方法探讨

国家坐标系的独立坐标系建立后,原国家坐标系的控制点不能直接应用于独立坐标系中,需要确定并计算得出独立坐标系的基准。独立坐标系的基准确定直接关系到独立坐标系的精度及其与国家坐标系间的转换。随着测绘技术的发展,一些原有的传统基准确定方法已不能满足高精度地心坐标系的要求,因此本文对地心坐标系的独立坐标系的基准确定方法进行了探讨。     

Classification of vegetation in an open landscape using full-waveform airborne laser scanner data

Airborne laser scanning (ALS) is increasingly being used for the mapping of vegetation, although the focus so far has been on woody vegetation, and ALS data have only rarely been used for the classification of grassland vegetation. In this study, we classified the vegetation of an open alkali landscape, characterized by two Natura 2000 habitat types: Pannonic salt steppes and salt marshes and Pannonic loess steppic grasslands. We generated 18 variables from an ALS dataset collected in the growing (leaf-on) season. Elevation is a key factor determining the patterns of vegetation types in the landscape, and hence 3 additional variables were based on a digital terrain model (DTM) generated from an ALS dataset collected in the dormant (leaf-off) season. We classified the vegetation into 24 classes based on these 21 variables, at a pixel size of 1 m. Two groups of variables with and without the DTM-based variables were used in a Random Forest classifier, to estimate the influence of elevation, on the accuracy of the classification. The resulting classes at Level 4, based on associations, were aggregated at three levels — Level 3 (11 classes), Level 2 (8 classes) and Level 1 (5 classes) — based on species pool, site conditions and structure, and the accuracies were assessed. The classes were also aggregated based on Natura 2000 habitat types to assess the accuracy of the classification, and its usefulness for the monitoring of habitat quality. The vegetation could be classified into dry grasslands, wetlands, weeds, woody species and man-made features, at Level 1, with an accuracy of 0.79 (Cohen’s kappa coefficient, κ). The accuracies at Levels 2–4 and the classification based on the Natura 2000 habitat types were κ: 0.76, 0.61, 0.51 and 0.69, respectively. Levels 1 and 2 provide suitable information for nature conservationists and land managers, while Levels 3 and 4 are especially useful for ecologists, geologists and soil scientists as they provide high resolution data on species distribution, vegetation patterns, soil properties and on their correlations. Including the DTM-based variables increased the accuracy (κ) from 0.73 to 0.79 for Level 1. These findings show that the structural and spectral attributes of ALS echoes can be used for the classification of open landscapes, especially those where vegetation is influenced by elevation, such as coastal salt marshes, sand dunes, karst or alluvial areas; in these cases, ALS has a distinct advantage over other remotely sensed data.     

Equilibrium trading of climate and weather risk and numerical simulation in a Markovian framework

We consider financial markets with agents exposed to external sources of risk caused, for example, by short-term climate events such as the South Pacific sea surface temperature anomalies widely known by the name El Nino. Since such risks cannot be hedged through investments on the capital market alone, we face a typical example of an incomplete financial market. In order to make this risk tradable, we use a financial market model in which an additional insurance asset provides another possibility of investment besides the usual capital market. Given one of the many possible market prices of risk, each agent can maximize his individual exponential utility from his income obtained from trading in the capital market, the additional security, and his risk-exposure function. Under the equilibrium market-clearing condition for the insurance security the market price of risk is uniquely determined by a backward stochastic differential equation. We translate these stochastic equations via the Feynman–Kac formalism into semi-linear parabolic partial differential equations. Numerical schemes are available by which these semilinear pde can be simulated. We choose two simple qualitatively interesting models to describe sea surface temperature, and with an ENSO risk exposed fisher and farmer and a climate risk neutral bank three model agents with simple risk exposure functions. By simulating the expected appreciation price of risk trading, the optimal utility of the agents as a function of temperature, and their optimal investment into the risk trading security we obtain first insight into the dynamics of such a market in simple situations.