Quality Assessment Of Digital Surface Models Generated From IKONOS Imagery

The growing applications of digital surface models (DSMs) for object detection, segmentation and representation of terrestrial landscapes have provided impetus for further automation of 3D spatial information extraction processes. While new technologies such as lidar are available for almost instant DSM generation, the use of stereoscopic high-resolution satellite imagery (HRSI), coupled with image matching, affords cost-effective measurement of surface topography over large coverage areas. This investigation explores the potential of IKONOS Geo stereo imagery for producing DSMs using an alternative sensor orientation model, namely bias-corrected rational polynomial coefficients (RPCs), and a hybrid image-matching algorithm. To serve both as a reference surface and a basis for comparison, a lidar DSM was employed in the Hobart testfield, a region of differing terrain types and slope. In order to take topographic variation within the modelled surface into account, the lidar strip was divided into separate sub-areas representing differing land cover types. It is shown that over topographically diverse areas, heighting accuracy to better than 3 pixels can be readily achieved. Results improve markedly in feature-rich open and relatively flat terrain, with sub-pixel accuracy being achieved at check points surveyed using the global positioning system (GPS). This assessment demonstrates that the outlook for DSM generation from HRSI is very promising.     

A multidisciplinary multi-scale framework for assessing vulnerabilities to global change

Terrestrial ecosystems provide a number of vital services for people and society, such as food, fibre, water resources, carbon sequestration, and recreation. The future capability of ecosystems to provide these services is determined by changes in socio-economic factors, land use, atmospheric composition, and climate. Most impact assessments do not quantify the vulnerability of ecosystems and ecosystem services under such environmental change. They cannot answer important policy-relevant questions such as 'Which are the main regions or sectors that are most vulnerable to global change?’ 'How do the vulnerabilities of two regions compare?’ 'Which scenario is the least harmful for a sector?’This paper describes a new approach to vulnerability assessment developed by the Advanced Terrestrial Ecosystem Analysis and Modelling (ATEAM) project. Different ecosystem models, covering biodiversity, agriculture, forestry, hydrology, and carbon sequestration are fed with the same Intergovernmental Panel on Climate Change (IPCC) scenarios based on the Special Report on Emissions Scenarios (SRES). Each model gives insights into specific ecosystems, as in traditional impact assessments. Moreover, by integrating the results in a vulnerability assessment, the policy-relevant questions listed above can also be addressed. A statistically derived European environmental stratification forms a key element in the vulnerability assessment. By linking it to other quantitative environmental stratifications, comparisons can be made using data from different assessments and spatial scales.     

冲积平原区土壤元素组成特征及其示踪作用

应用土壤元素组成特征研究基础地质问题是覆盖区多目标地球化学调查工作后项重要任务。通过对珠江三角洲，江汉平原，成都盆地3个冲积平原区土壤元素组成特征的研究，探讨了其对土壤成壤母质特性的示踪作用，为今后开展类似的研究工作提供了一种思路。     

高山峡谷区影响土壤测量找矿效果的元素表生活动特性研究

研究发现，高山峡谷区内土壤中元素的表生活动以表生富集作用为主，元素表征富集作用的程度、富集层位和粒级等受矿化作用和自然风化作用双重影响。非矿化地段土壤中元素的表生富集程度较矿化带处土壤中元素表生富集程度更强；矿化带处B层土壤比A层土壤中元素的富集强度稍大，元素明显地富集在粗粒级组分中；近矿（化）带的非矿化地段，A、B两层土壤仍受到矿化组分的影响，A层土壤比B层土壤受到的影响更加明显，粗粒级组分比细粒级组分反映敏感，C层土壤中元素在细粒级组分中轻微富集。根据本次研究结果，调整了高山峡谷区土壤测量工作方法，经试点测量验证，找矿效果良好。     

福建福安下白石特大桥海上岩土勘察方法

下白石特大桥是同江至三亚国道主干线福鼎至宁德高速公路建设中的一项控制性工程 ,是交通部指定的三阶段设计工程 ,桥长 110 5 m,主跨采用 2× 2 6 0 m预应力混凝土连续钢构。桥位位于白马河入海口处 ,工程地质、水文地质条件复杂 ,通过采用地表大面积的综合地质调查、海上地震映像物探以及海上钻探、原位测试、岩土测试等一系列行之有效的岩土勘察方法 ,确保了岩土工程勘察质量 ,其结果切实可行 ,为后期施工单位提供科学依据。     

可持续发展评估指标、方法及应用研究

可持续发展评估指标及方法研究是可持续发展定量评估研究的基础,是实施可持续发展管理的依据,是生态经济学与可持续发展研究的前沿领域和热点问题之一. 在概括介绍可持续发展评估的工具--指标/指数的概念和功能、国际上代表性可持续发展研究机构指标选取的原则的基础上,全面分析归纳了可持续发展指标(体系)的类型及其框架模式. 详细介绍了联合国可持续发展委员会(UNCSD)、经济合作与发展组织(OECD)、世界保护同盟(IUCN)、世界银行等国际上代表性机构的可持续发展系统性指标体系的最新研究进展,并分析了这些系统性指标体系的优缺点. 深入分析了国际上典型的社会发展类、经济发展类、生态环境类可持续发展指标(指数)的研究、开发与实际评估应用的情况. 最后,总结了当前可持续发展指标(体系)研究的特点与趋势.     

基于栅格空间信息定量化的湖南西部地区生态环境综合评价

以湖南西部地区为研究区域,采用遥感影像作为主要数据源,针对区域主要生态问题,利用栅格数据结构为主的数字环境模型,建立了生态环境质量综合评价模型. 对区域生态环境质量的空间分异格局进行了研究,通过将评价结果与数字高程模型迭加分析,研究了生态环境质量的垂直地带性分布规律,探索适合以山高坡陡为主要地貌特征的山区生态评价方法,结果显示,湖南西部地区生态环境综合指数呈正态分布,大部分地区环境质量属一般. 总体环境状况东南部好于西北部,河谷盆地优于山地. 研究表明,利用遥感和地理信息系统技术进行区域生态环境评价,具有数据采集快速、客观,评价和制图自动化,评价结果空间定位精度高,直观性与实用性强等优点.     

四平地区生态地质环境的研究

通过对四平地区生态地质环境的调查，对该区水、土壤、大气、区域稳定性、生态资源、地层条件、放射性、矿藏、地方病、旅游地质及垃圾等进行环境现状综合评价。利用ISODATA模糊聚类分析法对该区的生态地质环境质量进行了分区。并利用面积加权法计算出该区的生态地质环境质量评价结果为中上等水平。     

地下水水质预警信息系统研究

地下水水质预警是对地下水水质现状及变化趋势适时给出相应给别警戒信息的方法，包括状态预警和趋势预警两部分。以GIS技术为核心，将水质预警模型与GIS技术相结合，建立了地下水水质预警信息系统。并以吉林省西部平原地区地下水水质为例，研究了该区地下水水质恶化地区的分布、趋势、恶化预警等级及其成因。地下水水质预警系统为地下水资源管理，减少地下水水质恶化的风险提供了科学依据。     

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.