基于MSA特征的遥感图像多目标关联算法

遥感图像中多目标关联存在以下两个问题:一是低时间分辨率观测使得目标状态信息无法准确估计,基于Kalman滤波的多目标关联算法不再适用;二是基于图像特征的目标关联算法又无法处理大场景观测中多个目标关联引起的模糊性.针对上述问题,提出一种基于多尺度自卷积特征匹配和关联代价矩阵最优化的多目标关联算法.实验表明该算法对遥感图像中多目标关联问题具有一定的适用性.     

多尺度空间线状实体形状相似关系的表达与度量

本文对空间数据多尺度表达中线状实体综合前后的形状相似性进行了描述、分析和研究。通过调查统计,得出了衡量线状实体形状相似程度的两个重要参量SIMⅠ、SIMⅡ,基于这两个参量给出了空间线状实体形状相似性的定义以及在不同尺度下线状实体形状相似性的度量方法,并用实例进行验证。为空间数据多尺度表达时线状实体的形状表达提供了一种分析和评价手段。     

空间索引与多尺度表达的一体化模型研究

在分析各种常用索引的基础上,依据各自的适用范围,提出了对点对象建立格网索引,对线、面对象建立改进四叉树索引的组合优化策略。设计的改进四叉树索引避免了传统四叉树的重复索引,提高了数据访问的效率。     

Multi-Scale Texture Modeling

Patterns of crystallographic preferred orientation are referred to as texture. The specific subject of texture analysis is the experimental determination and interpretation of the statistical distribution of orientations of crystals within a specimen of polycrystalline material, which could be metals or rocks. The objective is to relate an observed pattern of preferred orientation to its generating processes and vice versa. In geosciences, texture of minerals in rocks is used to infer constraints on their tectono-metamorphic history. Since most physical properties of crystals, such as elastic moduli, the coefficients of thermal expansion, or chemical resistance to etching depends on crystal symmetry and orientation, the presence of texture imparts directional properties to the polycrystalline material. A major issue of mathematical texture analysis is the resolution of the inverse problem to determine a reasonable orientation density function on SO(3) from measured pole intensities on , which relates to the inverse of the totally geodesic Radon transform. This communication introduces a wavelet approach into mathematical texture analysis. Wavelets on the two-dimensional sphere and on the rotational group SO(3) are discussed, and an algorithms for a wavelet decomposition on both domains following the ideas of Ta-Hsin Li is given. The relationship of these wavelets on both domains with respect to the totally geodesic Radon transform is investigated. In particular, it is shown that the Radon transform of these wavelets on SO(3) are again wavelets on . A novel algorithm for the inversion of experimental pole intensities to an orientation density function based on this relationship is developed.     

多尺度TIN管理及表达算法探讨

为实现大规模地形的多分辨率显示与实时绘制,基于LOD技术给出了多尺度TIN的管理和表达算法。探讨该算法相关的数据组织、LOD层次表达、实时刷新等关键问题。该算法使用分级策略,在不影响视觉效果前提下对TIN进行分级表达;使用分区策略,在可视化过程中对TIN进行局部更新。采取不同分辨率TIN模型间逐步过渡策略,基本上消除了视图变换时的跳跃感。实验结果表明,这种紧凑有效的TIN表示方法实现简单,内存开销较少,CPU耗费小,大大缩短了视图刷新切换时间,能够在普通机器上实现大规模地形的实时漫游。     

电子地图中多尺度地图数据显示的研究

将计算机三维模型简化中的LOD思想引入到电子地图的组织和显示中,提出了同一比例尺数字地图不同详细程度的分层显示方法和不同比例尺数字地图嵌套显示方法,实现了电子地图的多级缩放。     

A multi-scale study on land use and land cover quality change: The case of the Yellow River Delta in China

This paper presents a case study of the Yellow River Delta in China, to trace land use and land cover changes during the past 20 years, with an emphasis on land quality changes. Three sets of data are used in this case study: remote sensing data derived from satellite images; crop yield data from statistics; and soil data collected by the researchers in the field. Our study reveals that at the regional scale, LUCC has taken place in a positive direction: vegetation cover has been expanding and crop yields per hectare have been on rise. However, while the overall eco-environment has improved, the improvement is uneven across the Delta region. At local levels, some areas show signs of increased salinization and declining organic content. Both natural forces and human activities are responsible for the LUCC, but human activities play a more important role. While some impacts of human activities are positive, the damages are often long-lasting and irreversible. We also conclude that it is necessary to use both macro data (such as remote sensing data) and micro data (data collected in the field) to study land quality change. The former are efficient in examining land quality changes at the regional scale, the latter can serve to verify ground patterns revealed from macro data and help to identify local variations, so as to get a comprehensive understanding of LUCC and promote sustainable land use and land management. This revised version was published online in July 2006 with corrections to the Cover Date.     

我国9大气候区降水特性及其物理成因的研究Ⅰ——基本特性分析

首先利用旱涝Z指数对全国9大气候区的旱涝进行了评定，并给出我国9大气候区旱涝Z指数的分布图。分析结果表明，1950年代我国除新疆地区处于偏早期外，其它几个区都处于多雨量期，1960年代由多雨向少雨转变的时期，1970年代——1980年代中期我国大部分地区处于雨量偏少期；1990年之后我国各个区的雨量都有所增加。此外，还应用Morlet小波变化对我国9大气候区降水的旱涝周期变化、旱涝分型及变化趋势进行了分析。研究结果表明：在16年、32年层次变化上，各气候区在不同时间段上，8年层次上降水的变化出现了一定的规律：东北、华北在1980年之后存在1年位相差；而长江中下游、江南及华南三者之间在1951～1970年时段上依次有着2年的位相差；长江中下游、内蒙及新疆之间依次存在着3年位相差。     

Variographic analysis of tropical forest cover from multi-scale remotely sensed imagery

Tropical forest mapping is one of the major environmental concerns at global and regional scales in which remote sensing techniques are firmly involved. This study examines the use of the variogram function to analyse forest cover fragmentation at different image scales. Two main aspects are considered here: (1) analysis of the spatial variability structure of the forest cover observed at three different scales using fine, medium and coarse spatial resolution images; and (2) the study of the relationship between rescaled images from the finest spatial resolution and those of the medium and coarse spatial resolutions. Both aspects are analysed using the variogram function as a basic tool to calculate and interpret the spatial variability of the forest cover. An example is presented for a Brazilian tropical forest zone using satellite images of different spatial resolutions acquired by Landsat TM (30 m), Resurs MSU (160 m) and ERS ATSR (1000 m). The results of this study contribute to establishing a suitable spatial resolution of remotely sensed data for tropical forest cover monitoring.     

时间尺度重构EEMD-GRNN改进模型预测PM2.5的研究

合理构建PM_2.5浓度预测模型是科学、准确地预测PM_2.5浓度变化的关键。传统PM_2.5预测EEMD-GRNN模型具有较好的预测精度,但是存在过于关注研究数据本身而忽略其物理意义的不足。本研究基于南京市2014-2017年PM_2.5浓度时间序列数据,分析PM_2.5浓度多尺度变化特征及其对气象因子和大气污染因子的尺度响应,基于时间尺度重构进行EEMD-GRNN模型的改进与实证研究。南京市样本数据PM_2.5浓度变化表现为明显的天际尺度和月际尺度,从重构尺度（天际、月际）构建GRNN模型更具有现实意义;同时,PM_2.5对PM₁₀、NO₂、O₃、RH、MinT等因子存在多尺度响应效应,以其作为GRNN模型中的输入变量更具有时间序列上的解释意义。改进后的EEMD-GRNN模型具有更高的PM_2.5浓度预测精度,MAE、MAPE、RMSE和R²分别为6.17、18.41%、8.32和0.95,而传统EEMD-GRNN模型的模型有效性检验结果分别为8.37、27.56%、11.56、0.91。对于高浓度天（PM_2.5浓度大于100 μg/m³）的预测,改进模型更是全面优于传统EEMD-GRNN模型,MAPE为12.02%,相较于传统模型提高了9.03%。