复合混沌系统的矢量数据加密研究

根据矢量数据的特点和混沌映射系统的加密方法,本文提出了一种基于Logistic映射和Chebyshev映射的复合混沌系统。它通过使用迭代状态的周期替换,并输出整数化的混沌映射序列,有效地避免计算机有限精度产生的累计误差。该算法有较强的随机性、抗穷举攻击能力、抵御已知明文攻击能力和较好的时间代价。经过安全性分析,本算法可以较好地用于矢量数据的加密。     

现代城市数字测图方法浅析

本文分析比较了目前城市大比例尺数字化测图中主要方法的优缺点，并为实现数字化地形图中不连续线、面状符号及复杂线状符号向GIS的自动化导入，针对电子平板法提出了基础线的概念。对全站仪草图法，提出在全站仪上加挂微型计算机，并用常规摄像方法代替草图。     

PSP和TSP在数字制图系统开发中的运用

简要介绍了数字地图制图系统，结合在开发一个应用软件系统时所要面临的一些实际问题和困难，引入了软件工程思想中改进软件开发方式的个体软件过程(PSP)和群组软件过程(TSP)。     

北京山区植被覆被率遥感制图与景观格局分析——以门头沟区为例

准确、快速地获取植被覆盖状况信息是北山区生态恢复和建设的关键与重点.本文在FCD Mapping model的原理和方法基础上,利用TM图像对北京门头沟区植被覆被率展开调查和制图应用研究,并利用FRAGSTATS软件对所得的植被覆盖等级图从斑块大小、斑块数、斑块密度、斑块平均面积、分形维数和聚集度等角度进行了空间格局的剖析.     

Downscaling in remote sensing

Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise.     

Analyzing fine-scale wetland composition using high resolution imagery and texture features

In order to monitor natural and anthropogenic disturbance effects to wetland ecosystems, it is necessary to employ both accurate and rapid mapping of wet graminoid/sedge communities. Thus, it is desirable to utilize automated classification algorithms so that the monitoring can be done regularly and in an efficient manner. This study developed a classification and accuracy assessment method for wetland mapping of at-risk plant communities in marl prairie and marsh areas of the Everglades National Park. Maximum likelihood (ML) and Support Vector Machine (SVM) classifiers were tested using 30.5 cm aerial imagery, the normalized difference vegetation index (NDVI), first and second order texture features and ancillary data. Additionally, appropriate window sizes for different texture features were estimated using semivariogram analysis. Findings show that the addition of NDVI and texture features increased classification accuracy from 66.2% using the ML classifier (spectral bands only) to 83.71% using the SVM classifier (spectral bands, NDVI and first order texture features).     

Stochastic gradient boosting classification trees for forest fuel types mapping through airborne laser scanning and IRS LISS-III imagery

This paper presents an application of Airborne Laser Scanning (ALS) data in conjunction with an IRS LISS-III image for mapping forest fuel types. For two study areas of 165 km² and 487 km² in Sicily (Italy), 16,761 plots of size 30-m × 30-m were distributed using a tessellation-based stratified sampling scheme. ALS metrics and spectral signatures from IRS extracted for each plot were used as predictors to classify forest fuel types observed and identified by photointerpretation and fieldwork. Following use of traditional parametric methods that produced unsatisfactory results, three non-parametric classification approaches were tested: (i) classification and regression tree (CART), (ii) the CART bagging method called Random Forests, and (iii) the CART bagging/boosting stochastic gradient boosting (SGB) approach. This contribution summarizes previous experiences using ALS data for estimating forest variables useful for fire management in general and for fuel type mapping, in particular. It summarizes characteristics of classification and regression trees, presents the pre-processing operation, the classification algorithms, and the achieved results. The results demonstrated superiority of the SGB method with overall accuracy of 84%. The most relevant ALS metric was canopy cover, defined as the percent of non-ground returns. Other relevant metrics included the spectral information from IRS and several other ALS metrics such as percentiles of the height distribution, the mean height of all returns, and the number of returns.     

Spectral material mapping using hyperspectral imagery: a review of spectral matching and library search methods

Imaging spectroscopy is an emerging and versatile technique that finds applications in diverse fields concerned with remote identification, discrimination and mapping of materials. The large amount of spectral data produced by hyperspectral imaging necessitates the development of automated techniques that convert imagery directly into thematic maps. Spectral library search method, a method of choice for organic compound identification by the mass spectroscopy, has caught the attention of researchers as one of the appropriate methods for an efficient exploitation of high quality spectral data available from the hyperspectral imaging systems. Given the apparent increase in the number of papers appearing on the subject as well as the variety of methods proposed, it is reasonable to say that the field of automated interpretation of reflectance spectral data has passed its infancy now gaining important space in the scientific community. We present an overall view of the literature relevant to the development of library search method, the various search algorithms and systems available in the purview for developing an automated hyperspectral data analysis system for material identification.     

基于六角格的陆地边界环境模型构建方法研究

陆地边界环境是边界划界与边界区域分析的基础,是关系到国家利益的重要内容。然而,国内外对相关技术的研究却不多,研究成果更少。针对这一问题,本文分析了陆地边界环境的具体内容,提出了基于六角格的陆地边界环境模型,探讨了模型的构建流程,研究了建模过程中的几项关键技术,包括数学基础的确定、区域剖分技术、区域细分技术及信息映射方法等。最后对模型技术进行了总结,展望了其实际应用前景。     

一等水准点之记标准化与规范化研究

为保证一等水准点之记精度与质量,提高测绘人员野外工作效率,对目前的一等水准点之记进行了探讨与分析,指出了其详细位置图与点位,详细说明表达、标石断面图绘制和经纬度书写及交通路线描述中存在的缺点,并基于此提出了若干改进意见,这在一定程度上促进了一等水准点之记信息的标准化与规范化。