福建省海岛和海岸带遥感影像数据库构建与实现

在参考ISO19115-2003遥感影像元数据标准的基础上,利用覆盖福建全境的海岛、海岸带的Landsat7和SPOT5的原始影像、校正影像以及融合影像,构建基于SQL Server2005的福建省海岛、海岸带遥感影像数据库系统,实现了遥感影像元数据与影像数据的一体化存储与管理．同时,使用VB语言的可视化特性,实现了基于用户的可视化查询与下载．本系统的研发,将为福建省海岛、海岸带研究提供一个可以共享的基础数据平台．     

The use of 3-D mapping in geological research and risks analysis: evaluation of a water supply project in the Kathmandu-Melamchi Area

Using 2-D and 3-D multi satellite data (SPOT and LANDSAT TM) in a GIS allows us to produce 3-D digital elevation maps (DEM) through the techniques of remote sensing (RS) analysis and computer aided mapping. In the field of geotechnical research, since 1992, some works have been made in cooperation with ICIMOD-MENRIS, the department of Mines and Geology in Nepal, and the bilateral cooperation from both France and Germany. The use of 2-D and 3-D digital maps to geological and geotechnical research and risks analysis, concerns here the evaluation of the new water supply project Kathmandu-Melamchi proposed by WHO-UNDP and the World Bank. This revised version was published online in July 2006 with corrections to the Cover Date.     

SPOT卫星影像在德尔尼铜矿区域地质研究中的应用

利用卫星遥感影像对青海省德尔尼铜矿区的区域地质做了判释性研究 :( 1)判释出 3条左旋平移断层及一组羽式构造 ,并测得其中一条断层的左旋平移距离为 12 50m ,而在以往 1∶2 0万和 1∶5万的地质填图中均未发现这 3条断层的平移性质 ;( 2 )判释出作为蛇绿岩组成部分的地幔橄榄岩呈现与一般岩浆岩不同的影像特征。     

A comparative analysis of a fixed thresholding vs. a classification tree approach for operational burn scar detection and mapping

The scope of this paper is to demonstrate, evaluate and compare two burn scar mapping (BSM) approaches developed and applied operationally in the framework of the RISK-EOS service element project within the Global Monitoring for Environment and Security (GMES) program funded by ESA (http://www.risk-eos.com). The first method is the BSM_NOA, a fixed thresholding method using a set of specifically designed and combined image enhancements, whilst the second one is the BSM_ITF, a decision tree classification approach based on a wide range of biophysical parameters. The two methods were deployed and compared in the framework of operational mapping conditions set by RISK-EOS standards, based either on sets of uni- or multi-temporal satellite images acquired by Landsat 5 TM and SPOT 4 HRV. The evaluation of the performance of the two methods showed that either in uni- or multi-temporal acquisition mode, the two methods reach high detection capability rates ranging from 80% to 91%. At the same time, the minimum burnt area detected was of 0.9–1.0 ha, despite the coarser spatial resolution of Landsat 5 TM sensor. Among the advantages of the satellite-based approaches compared to conventional burn scar mapping, are cost-efficiency, repeatability, flexibility, and high spatial and thematic accuracy from local to country level. Following the catastrophic fire season of 2007, burn scar maps were generated using BSM_NOA for the entirety of Greece and BSM_ITF for south France in the framework of the RISK-EOS/GMES Services Element project.     

Analysis on coral reefs mapping using SPOT5 data at the Dongsha Atoll

Coral reefs are an sensitive-to-environment complex marine ecosystem. The ecosystem of corals is rich in biodiversity. Remote sensing offers a powerful tool for categorizing coral reefs and is the most cost-effective approach for the large-scale reef survey. The Dongsha Atoll, more than 300 km2 with an average depth of 10 m, is located at the northern continental margin of the South China Sea. It has been abused by destructive fishing during recent decades. Three satellite imageries (Quickbird2, ETM and SPOT5) are used to evaluate the capabilities of SPOT5 imagery to provide data that are useful for categorizing the current distribution of coral reefs therein. During the data processing, unsupervised classification functions are adopted for ETM and SPOT5 data, while the supervised classification method is used for Quickbird2. The classes are (or not) merged into coral reef, and then will be operated by vectorization, simplification, and topological analysis. There are 1 331 coral reefs larger than 100 m2 with a detection limit of 3×3 pixels at the multi-band data of Quickbird2, which is taken as the comparison baseline. The results extracted from SPOT5 and ETM images are less in number and area than those from the Quickbird2 image, whereas the results from SPOT5 data are better than those of ETM data at the silty lagoon due to its higher resolution. SPOT5 XS band 2 fails to distinguish the deep substrate inside the atoll compared with ETM data because of its poor penetration capability. Only SPOT XS band 1 cannot be used to differentiate coral reef from sand bottom. Merging the SPOT5 multi-bands data with the spatial resolution of SPOT5 pan-data and referring to ETM imagery are expected to provide an optimal satellite-based approach for mapping of coral reefs.     

基于RS和GIS的城市公共绿地功能模糊评价

城市公共绿地具有重要的生态功能和社会功能,良好的评价体系有利于其科学的规划和管理。目前主要采用人均公共绿地和服务半径两个指标对公共绿地质量进行评价,不能较好地评价其生态和社会功能。本文根据公共绿地的功能特点,按照评价体系可操作性和可比性要求,选择单位公园绿化覆盖率、面积大小、公园服务半径内的居民区和单位面积比例、服务半径内道路面积比例作为评价因子。并以山东省泰安市为研究区,利用遥感影像监督分类结合ArcGIS空间分析方法从SPOT5影像中获取评价因子数据,利用多级模糊评判方法对研究区城市公共绿地进行评判。模糊评价结果为泰安市公共绿地的生态功能和社会功能综合得分为77.449分,等级标准为良好。     

基于SPOT影像的可吸入颗粒物遥感反演

通过用SPOT 5遥感影像近红外与红光波段计算的差值植被指数(DVI)与实测的可吸入颗粒物(PM10)浓度数据建立模型,对2007年北京市城区SPOT 5影像进行PM10浓度反演试验,反演结果与实测数据所反映的PM10空间分布趋势基本一致.2007年北京市城区北部PM10污染较为严重,南部污染相对较弱; 绿地和水体附近...     

Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery

To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively.     

Development of a modified neural network-based land cover classification system using automated data selector and multiresolution remotely sensed data

Integrating multiple images with artificial neural networks (ANN) improves classification accuracy. ANN performance is sensitive to training datasets. Complexity and errors compound when merging multiple data, pointing to needs for new techniques. Kohonen's self-organizing mapping (KSOM) neural network was adapted as an automated data selector (ADS) to replace manual training data processes. The multilayer perceptron (MLP) network was then trained using automatically extracted datasets and used for classification. Two hypotheses were tested: ADS adapted from the KSOM network provides adequate and reliable training datasets, improving MLP classification performance; and fusion of Landsat thematic mapper (TM) and SPOT images using the modified ANN approach increases accuracy. ADS adapted from the KSOM network improved training data quality and increased classification accuracy and efficiency. Fusion of compatible multiple data can improve performance if appropriate training datasets are collected. This proved to be a viable classification scheme particularly where acquiring sufficient and reliable training datasets is difficult.     

变窗口纹理在SPOT5影像土地覆盖分类中的应用研究

纹理作为有效的空间信息,在遥感信息提取中有着广泛的应用,其中纹理窗口的选择对分类精度影响较大,而且遥感影像中不同地物类型具有多尺度特性,利用单一窗口纹理信息进行分类不能使得各地物类型同时达到较高精度.该文采用SPOT5影像对研究区进行长序列窗口纹理分类实验,并提出变窗口纹理分类方法,实验区分类实验及精度对比表明:长序列窗口纹理分类实验中,7×7窗口分类精度最高,但在这一窗口下建设用地、耕地、裸地等地类的精度仍低于总体精度;而采用基于长序列窗口纹理分类后验概率的变窗口纹理分类方法,总精度达到86.17％,Kappa系数达到0.8230,与7×7窗口分类精度相比各地物类型的生产者精度与用户精度都有进一步提高,验证了变窗口纹理分类方法的可行性.