基于布尔矩阵的空间关联规则提取方法研究

空间关联规则是空间数据挖掘(SDM)中的重要内容之一。由于空间数据的复杂性,传统的空间关联规则挖掘方法主要是将空间数据库变换为非空间数据库,通过挖掘算法挖掘空间关联规则。目前,Apriori算法是关联规则挖掘中使用最为普遍的算法,但是,由于该算法在关联规则提取过程中需要多次扫描数据库,并且产生冗余的候选项集,因此,在执行大型数据库的关联规则挖掘时,具有效率低下的缺陷。本文基于Apriori算法提出了基于布尔矩阵的空间关联规则挖掘算法,并以挖掘福建省厦门市土地覆盖现状与地形特征因子的空间关联关系作为试验案例,对比Apriori算法的提取结果与提取效率,结果表明:该算法不仅减少了扫描数据库的次数,而且减少了冗余候选项集的产生,提高了空间关联规则的提取效率。     

基于bat和vbs的Oracle属性数据和ArcSDE空间数据自动备份技术

数据库自动备份功能的实现大都是制作一个工具在Windows任务里定时执行,而工具的制作则多种多样,可以使用高级语言开发平台编写,也可以使用脚本写成批命令执行。常规的是开发一个自动备份工具,这样做有一定的开发量,且需要依赖某些部署环境。本文介绍在Windows平台下,如何仅通过dos命令和vbs脚本完成Oracle属性数据和ArcSDE空间数据的自动备份功能。     

基于ArcGIS Server的医院网络地理信息服务系统

为解决目前医院地理信息服务系统在信息共享、空间分析等方面的不足,采用ArcGIS Server组件、C#编程语言、SQL Server数据库研发了医院网络地理信息服务系统。该系统以天地图作为基础地理数据,融合医院空间与医疗信息,并部署到互联网环境中。除具有医疗专题信息的网络浏览与查询外,系统还实现了诸多空间分析、地学统计等功能,既可为市民就医提供更全面的信息查询,又可为医疗事故的突发与应急提供技术支撑。     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial interpolation of snow water equivalency using surface observations and remotely sensed images of snow‐covered area

As demand for water continues to escalate in the western Unites States, so does the need for accurate monitoring of the snowpack in mountainous areas. In this study, we describe a simple methodology for generating gridded‐estimates of snow water equivalency (SWE) using both surface observations of SWE and remotely sensed estimates of snow‐covered area (SCA). Multiple regression was used to quantify the relationship between physiographic variables (elevation, slope, aspect, clear‐sky solar radiation, etc.) and SWE as measured at a number of sites in a mountainous basin in south‐central Idaho (Big Wood River Basin). The elevation of the snowline, obtained from the SCA estimates, was used to constrain the predicted SWE values. The results from the analysis are encouraging and compare well to those found in previous studies, which often utilized more sophisticated spatial interpolation techniques. Cross‐validation results indicate that the spatial interpolation method produces accurate SWE estimates [mean R² = 0·82, mean mean absolute error (MAE) = 4·34 cm, mean root mean squared error (RMSE) = 5·29 cm]. The basin examined in this study is typical of many mid‐elevation mountainous basins throughout the western United States, in terms of the distribution of topographic variables, as well as the number and characteristics of sites at which the necessary ground data are available. Thus, there is high potential for this methodology to be successfully applied to other mountainous basins. Copyright © 2010 John Wiley & Sons, Ltd.     

广州市美丽乡村空间分异特征及其影响因素

以广州市已公布的4批美丽乡村建设试点数据为基础，通过最邻近指数、基于Riple’s函数的多距离空间聚类分析、核密度分析和叠置分析等方法，探讨了广州市美丽乡村的发展现状、空间分布格局及其影响因素。结果表明：1）自2013年起，广州市美丽乡村数量逐年递增且增长率呈现上升趋势；2）广州市美丽乡村空间分布呈明显的集聚型分布；3）Ripley’s函数分析表明美丽乡村要素点空间分布格局随距离变化略有不同，在0.14 km处集聚强度达到最大；4）核密度分析显示美丽乡村高密度区域主要分布在广州南部和西北部，包括番禺－南沙1个热点主核心区和从化、花都－白云2个热点副核心区，密度分布呈现多核心不均衡特点；5）乡村的地形水文、人文历史、交通区位和政策规划为美丽乡村空间分布的主要影响因素，其中，政策规划因素对“美丽乡村群”空间格局的形成起决定性影响。空间分布特征总体反映出广州市美丽乡村规划建设初见成效，并逐步形成以热点核心区为基础的“美丽乡村群”。最后，在乡村选点、空间优化、价值提升以及乡村治理等方面提出若干建议。     

On the prediction of the Toce alpine basin floods with distributed hydrologic models

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant. The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km²). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations). The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.     

Gender analysis for better coastal management – Increasing our understanding of social-ecological seascapes

Although highly recognized as needed, studies linking gender and coastal/marine management are scarce. This research illustrates the importance of gender analysis in natural resource management by linking gender and coastal management i.e. Marine Spatial Planning. The research was conducted in various Zanzibar seascapes (Unguja Island, Tanzania). Using a typology comprising gender structure, symbolism and identity; the results show a clear gendered division of labor, highly associated with a gender symbolism in which traditional roles of women as responsible for reproduction activities played a major role. Men used the whole seascape for their activities, while women remained in coastal forests and shallow areas collecting wood, invertebrates and farming seaweed. These activities allowed women to combine productive and reproductive work. Ecosystem importance for subsistence decreased with distance from land for both genders, while the importance for income increased with distance for men. Both genders acknowledged seagrasses as very important for income. Income closely followed the universal pattern of men earning more. Identities were defined by traditional ideas like “women are housewives”, while men identities were strongly associated with fisheries with reinforced masculinity. Livelihood diversity was higher for women also showing a tendency of slow change into other roles. Management was found to be strongly androcentric, revealing a deep gender inequality. The research exemplifies how a gender analysis can be conducted for management enhancement. It also invites replication around the world. If management is found to be androcentric in coastal locations elsewhere, a serious gender inequality can be at hand at global level.     

Input data resolution‐induced uncertainty in watershed modelling

The temporal‐spatial resolution of input data‐induced uncertainty in a watershed‐based water quality model, Hydrologic Simulation Program‐FORTRAN (HSPF), is investigated in this study. The temporal resolution‐induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log‐normal relation with time interval for temperature data while it exhibits a power‐law relation for rainfall data. The temporal‐scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash‐Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate‐nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log‐normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal‐scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non‐symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.     

The method of a two-point conditional column density for estimating the fractal dimension of the distribution of galaxies

We suggest a new method for estimating the fractal dimension of the spatial distribution of galaxies: the method of selected cylinders. We show the capabilities of this method by constructing a two-point conditional column density for galaxies with known redshifts from the LEDA database. The fractal dimension of a sample of LEDA and EDR SDSS galaxies has been estimated to be 2.1±0.1 for cylinder lengths of 200 Mpc. A major advantage of the suggested method is that it allows scales comparable to the catalog depth to be analyzed for galaxy surveys in the form of conical sectors and small fields in the sky.