基于GSM Modem及GIS技术的地质灾害预警系统研究

全球移动通讯系统GSM是目前较为广泛使用的一种数字移动通信网络。基于GSM及GIS技术,探讨了GSM Modem技术在地质灾害预警系统中的应用模式,研究了应用过程中涉及的部分关键技术和规范,并结合AT指令、ASP.NET和C#编程技术,设计、开发了基于Web技术的地质灾害数据采集与预警信息发布功能模块。最后,对该功能模块进行了应用试验,结果令人满意。     

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。     

区域规划空间信息系统建设与应用研究——以江苏省城乡规划信息系统为例

区域性城乡规划信息系统建设开展较晚,与城市级规划信息系统不同,其应用需求、数据构成、技术架构具有其独特性。结合新一轮江苏省城镇体系规划修编工作,开展全省城乡规划信息数据建库和应用平台的开发工作,系统根据区域规划的编制和研究应用需求,制定了面向未来区域规划工作需求的数据标准,集成了全省多源、多尺度、多时态的空间数据,实现了跨专业、跨平台空间信息的整合与共享。为江苏省城镇体系规划以及其他相关编制提供数据分析、规划决策支撑等服务,并预留未来与其他各类地理信息系统的应用接口。     

Optimization of land use structure based on ecological GREEN equivalent

Optimization of land use structure consists of economic and social and ecological optimization. Applying the minds of system engineering and principles of ecology, this paper presents such thoughts: the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district; through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland) and based on the rule, GREEN equivalent, this paper introduces the area conversion between woodland and cultivated land, also between woodland and grassland; this paper establishes a multi-dimension controlling model of optimization of land use structure. In addition, a multi-objective linear programming model for optimization of land use structure is designed. In the end, this paper tests and verifies this theory of ecological optimization, taking Qionghai city in Hainan Province as an example.     

Development of a data mining method for land control

Land resources are facing crises of being misused, especially for an intersection area between town and country, and land control has to be enforced. This paper presents a development of data mining method for land control. A vector-match method for the prerequisite of data mining i. e., data cleaning is proposed, which deals with both character and numeric data via vectorizing character-string and matching number. A minimal decision algorithm of rough set is used to discover the knowledge hidden in the data warehouse. In order to monitor land use dynamically and accurately, it is suggested to set up a real-time land control system based on GPS, digital photogrammetry and online data mining. Finally, the means is applied in the intersection area between town and country of Wuhan city, and a set of knowledge about land control is discovered.     

Towards an integral strategy for modelling uncertain geospatial data

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzzines significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN (triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.     

Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping

Abstract

The aim of this study was to determine how well the landslide susceptibility parameters, obtained by data-dependent statistical models, matched with the parameters used in the literature. In order to achieve this goal, 20 different environmental parameters were mapped in a well-studied landslide-prone area, the Asarsuyu catchment in northwest Turkey. A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database. In order to run a series of logistic regression models, different random landslide-free sample sets were produced and combined with seed cells. Different susceptibility maps were created with an average success rate of nearly 80%. The coherence among the models showed spatial correlations greater than 90%. Models converged in the parameter selection peculiarly, in that the same nine of 20 were chosen by different logistic regression models. Among these nine parameters, lithology, geological structure (distance/density), landcover-landuse, and slope angle were common parameters selected by both the regression models and literature. Accuracy assessment of the logistic models was assessed by absolute methods. All models were field checked with the landslides resulting from the 12 November 1999, Kayna?li Earthquake (Ms = 7.2).     

Three-dimensional trees for virtual globes

One of the problems in virtual globes technologies is the real-time representation of vegetal species. In forest or garden representations, the low detailed plants produce a lack of realism. Efficient techniques are required to achieve accurate interactive visualisation due to the great number of polygons the vegetal species have. This article presents a multi-resolution model based on a geometric representation of vegetal species that allows the application to perform the progressive transmission of the model, that is, the transmission of a simple representation followed by successive refinements of it. It has a hardware-oriented design in order to obtain interactive frame rates. The geometric data of the objects are stored in the graphics processing unit and, moreover, the change from one approximation to another is obtained by performing mathematical calculations in this graphics hardware. The multi-resolution model presented here enables instancing: as many vegetal species as desired can be rendered with different levels of detail, while all of them are accessing the same geometric data. This model has been used to build a real-time representation of a not imaginary scenario.     

A hierarchical spatiotemporal adaptive fusion model using one image pair

ABSTRACT

Image fusion techniques that blend multi-sensor characteristics to generate synthetic data with fine resolutions have generated great interest within the remote sensing community. Over the past decade, although many advances have been made in the spatiotemporal fusion models, there still remain several shortcomings in existing methods. In this article, a hierarchical spatiotemporal adaptive fusion model (HSTAFM) is proposed for producing daily synthetic fine-resolution fusions. The suggested model uses only one prior or posterior image pair, especially with the aim being to predict arbitrary temporal changes. The proposed model is implemented in two stages. First, the coarse-resolution image is enhanced through super-resolution based on sparse representation; second, a pre-selection of temporal change is performed. It then adopts a two-level strategy to select similar pixels, and blends multi-sensor features adaptively to generate the final synthetic data. The results of tests using both simulated and actual observed data show that the model can accurately capture both seasonal phenology change and land-cover-type change. Comparisons between HSTAFM and other developed models also demonstrate our proposed model produces consistently lower biases.