共查询到19条相似文献,搜索用时 171 毫秒
1.
2.
3.
国土资源数据库建设成果主要以MapGIS和Geodatabase(GDB)格式进行存储,两者之间的数据转换十分频繁。经测试表明,MapGIS通过中间格式向GDB转换存在问题,因此本文提出直接读取MapGIS加密二进制文件,通过MapGIS SDK和ArcGIS Engine相结合开发转换程序的技术路线,实现MapGIS数据批量自动转换到GDB。在分析MapGIS数据组织、GDB数据组织、实体几何类型对照、几何对象转换对照、属性字段对照等关键技术的基础上,采用多源空间数据无缝集成技术(SIMS)进行程序设计,对转换流程进行优化,开发出了MapGIS到GDB的数据转换软件MapGIS2GDB,该成果能够满足省市级国土资源数据库建设对MapGIS数据转换的需求。 相似文献
4.
利用FME Suite实现MapGIS地图数据和Geodatabase间的语义转换 总被引:1,自引:0,他引:1
通过对Geodatabase和MapGIS数据模型的分析以及传统数据转换方式的探讨,提出了运用FME Su ite对Geodatabase和MapGIS地图数据进行语义转换的技术路线及技术优势,并以云南省国土资源数据交换中心为例详细论证了利用FME对Geodatabase和MapGIS间语义转换的实现方法和过程。 相似文献
5.
6.
本文以清江流域为研究区域,基于GIS技术,对清江流域的资源环境空间要素进行分析。研究选择ArcView3.3作为软件平台,探讨了数字高程模型(DEM)的建立,在此基础上进行水文模拟分析以及地貌形态分析,提取了流域的河网,进行了流域剖面图、坡度、坡向和粗糙度图的绘制,揭示了流域内资源环境的隐含信息。总结分析结果,对区域的资源开发和环境保护的可持续性提出建议。 相似文献
7.
8.
9.
泾河流域和北洛河流域是黄河中游多沙粗沙的主要来源区域,两大流域地貌形态、气象水文都比较接近。本文选取两大流域作为研究对象,为方便研究按照流域自然形态划分区段,利用ArcGIS10.0为技术平台,提取不同区段地貌微观因子、宏观因子和水系网络等,对两流域不同区段进行横向对比,分析其中的异同,根据两流域特性结合当地实际情况提出合理的水土保持建议。 相似文献
10.
Geodatabase是ArcGIS引入的新一代空间数据模型,是建立在DBMS之上的统一的、智能化的空间数据库。本文从基本内涵、提出的技术背景、体系结构三方面对Geodatabase进行了全面阐述,同时介绍了建立Geodatabase数据库的基本方法。 相似文献
11.
数字校园中空间数据在数据库中的组织形式,直接关系到整个空间地理数据库系统的管理和查询性能,而基于Geodatabase的空间数据库对各种系统有着不可替代的优势。文章首先介绍了Geodatabase地理数据库的概念与类别并分析其特点,以南林大校园为例,分析并运用Geodatabase数据模型成功设计了3维校园地理信息系统... 相似文献
12.
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM and LANDSAT images of spatial resolution 30?m were used to construct groundwater potential zones (GPZ) map by integrating geological fractures, drainage network, slope and relief, and convergence index maps of the study area. Weight and score of each map were developed according to their level of contribution toward groundwater accumulation and spatial distribution of groundwater wells. The area that has very high potential for groundwater is located at the foot of Oman Mountains and Al Dhaid Depression covering an area of about 59.33?km², which is 4.40% of the study area. Further hydrological map and data on hydraulic properties of shallow aquifer, as recorded from observation wells in the regions, have been used to validate the produced GPZ map. The validation result showed sufficient agreement between the produced GPZ map. 相似文献
13.
基于事件的疫情应急时空数据模型 总被引:1,自引:0,他引:1
针对疫情应急系统在时空数据逻辑性方面的高要求及已有时空数据模型在该方面的不足,本文以事件产生为触发、事件发展为驱动,进行面向对象的时空数据建模研究:建立了城市疫情应急相关时空数据的概念模型、静态结构模型和时态行为模型;并设计Geodatabase实例和组件模型,实现对时空数据模型的面向对象的组织、管理和操作。通过在眉山市疫情监测应急系统中的成功应用表明,基于事件对多关联复杂空间对象群进行的联动操作,实现了时空数据的逻辑耦合。 相似文献
14.
基于Geodatabase的面向对象空间数据库设计 总被引:18,自引:4,他引:14
在Arc/Info中,支持空间数据库的数据模型经历了C AD模型、C overage模型和G eodatabase模型。文章通过讨论新一代的数据模型———G eodatabase及其G eodatabase数据库的结构体系和数据组织方式,实现了面向对象的空间数据库的设计。 相似文献
15.
16.
Groundwater exploration and modelling requires hydrological parameters and a large volume of hydrologic database. This study integrates remote sensing and geographic information system (GIS) to map and classify hydrological parameters indicates areas of groundwater recharge and discharge. Bivariate quadratic surfaces with moving window size of 5 × 5 were fitted to the digital elevation model and drainage basins, drainage network, topographic wetness index (TWI) and hydroforms were derived. The eight-direction algorithm (D8) that determines in which neighbouring pixel any water in a central pixel will flow naturally was used to delineate drainage basin and drainage network in the study area. The TWI was used to quantify the effect of local topography on hydrological processes and for modelling soil moisture. The results indicate the presence of intensive of stream network (1336 km2), wettest zones and accumulation zones (63.99 km2) within Wadi Bih, the UAE and Wadi Khasb, Oman, suggesting regional recharge. 相似文献
17.
18.
Huafei Yu Tinghua Ai Min Yang Jingzhong Li Lu Wang Aji Gao Tianyuan Xiao Zhe Zhou 《Transactions in GIS》2023,27(7):1898-1927
Deep learning is increasingly being used to improve the intelligence of map generalization. Vector-based map generalization, utilizing deep learning, is an important avenue for research. However, there are three questions: (1) transforming vector data into a deep learning data paradigm; (2) overcoming the limitation of the number of samples; and (3) determining whether existing knowledge can accelerate deep learning. To address these questions, taking river network selection as an example, this study presents a framework integrating hydrological knowledge into graph convolutional neural networks (GCNNs). This framework consists of the following steps: constructing a dual graph of river networks (DG_RN), extracting domain knowledge as node attributes of DG_RN, developing an architecture of GCNNs for the selection, and designing a fine-tuning rule to refine the GCNN results. Experiments show that our framework outperforms existing machine learning and traditional feature sorting methods using different datasets and achieves good morphological consistency after the selection. Furthermore, these results indicate that DG_RN meets the data paradigm of graph deep learning, and the framework integrating existing characteristics (i.e., Strahler coding, the number of tributaries, the distance between proximity rivers, and upstream drainage area) mitigates the dependence of GCNNs on plenty of samples and enhance its performance. 相似文献