Effects of geographic information system vector–raster–vector data conversion on landscape indices

1996 ◽  
Vol 26 (8) ◽  
pp. 1416-1425 ◽  
Author(s):  
Pete Bettinger ◽  
Gay A. Bradshaw ◽  
George W. Weaver
Keyword(s):  
Information System ◽  
Fractal Dimension ◽  
Geographic Information System ◽  
Cell Size ◽  
Grid Cell ◽  
Conversion Process ◽  
Data Conversion ◽  
Edge Density ◽  
Gis Data ◽  
Landscape Level

The effects of geographic information system (GIS) data conversion on several polygon-and landscape-level indices were evaluated by using a GIS vegetation coverage from eastern Oregon, U.S.A. A vector–raster–vector conversion process was used to examine changes in GIS data. This process is widely used for data input (digital scanning of vector maps) and somewhat less widely used for data conversion (output of GIS data to specific formats). Most measures were sensitive to the grid cell size used in the conversion process. At the polygon level, using the conversion process with grid cell sizes of 3.05, 6.10, and 10 m produced relatively small changes to the original polygons in terms of ln(polygon area), ln(polygon perimeter), and 1/(fractal dimension). When grid cell size increased to 20 and 30 m, however, polygons were significantly different (p < 0.05) according to these polygon-level indices. At the landscape level, the number of polygons, polygon size coefficient of variation (CV), and edge density increased, while mean polygon size and an interspersion and juxtaposition index (IJI) decreased. The youngest and oldest age-class polygons followed the trends of overall landscape only in terms of number of polygons, mean polygon size, CV, and IJI. One major side effect of the conversion process was that many small polygons were produced in and around narrow areas of the original polygons. An alleviation process (referred to as the dissolving process) was used to dissolve the boundaries between similarly attributed polygons. When we used the dissolving process, the rate of change for landscape-level indices slowed; although the number of polygons and CV still increased with larger grid cell sizes, the increase was less than when the dissolving process was not used. Mean polygon size, edge density, and fractal dimension decreased after use of the dissolving process. Trends for the youngest and oldest age-class polygons were similar to those for the total landscape, except that IJI was greater for these age-classes than for the total landscape.

scholarly journals An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS

2019 ◽  
Vol 8 (9) ◽  
pp. 392
Author(s):  
Junqiang Zhang ◽  
Lirui Xu ◽  
Yi Zhang ◽  
Gang Liu ◽  
Lingjun Zhao ◽  
...  
Keyword(s):  
Information System ◽  
Information Processing ◽  
Geographic Information System ◽  
Data Processing ◽  
Business Processes ◽  
Geographic Information ◽  
Processing Method ◽  
On Demand ◽  
Business System ◽  
Gis Data

With the rapid development of information processing technology and continuously evolving technological hardware and software, the scale of spatial data has grown exponentially. This has necessitated that stricter requirements be placed on the way data is processed. The traditional single-machine centralized data processing method is gradually being replaced by the network-based cloud geographic information system (GIS) mode. However, the information processing method of the business system in the existing spatial information network environment is difficult to expand, which limits the application of the business system. This paper proposes an on-demand and extended model for the GIS data processing procedure that considers the three-way separation of algorithm development, business processes, and the operational interface, and can implement an on-demand expansion of business processes by process modeling the business and task scheduling the workflow engine. This can expand the scope of business systems and improve the efficiency of business system construction.

Fractal Dimension and Patchiness in Hinabian-Lawigan Watershed Southern Leyte, Philippines

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Jay-Ar O. Ragub ◽  
Ricardo T. Bagarinao
Keyword(s):  
Information System ◽  
Fractal Dimension ◽  
Geographic Information System ◽  
Landscape Ecology ◽  
Landscape Metrics ◽  
Agricultural Production ◽  
Geographic Information ◽  
Forest Patches ◽  
Barren Land ◽  
Critically Endangered Species

Landscape metrics for analyzing landscape structures is fast developing topics in landscape ecology. This study examines fractal dimension and patchiness of the Hinabian-Lawigan watershed (Southern Leyte, Philippines), which is a habitat to different critically endangered species in the province. Three indices were used (i.e. total patch number, TPN; mean patch size, MPS; and mean patch fractal dimension, MPFD). The analysis was facilitated through the use of Geographic Information System (GIS) and patch analyst extension of ArcGIS. Land use-land cover classification system was used to identify the different patches. Results indicate that the watershed consists of patches of annual cropland, barren land, built-up areas, closed forests, pastureland, and shrubland. Closed forest patches have the largest total area (3,727.98 has) but have the highest TPN (i.e.1,700) and MPS (2.19 has). Their computed MPFD is greater than 1, which means that they are highly fragmented, and needed to be connected. Built-up areas are not prevalent in the watershed but may become a future concern if unmanaged. Of greatest concern is the presence of agricultural production areas (TPN value of 828 and MPFD of 1.52). Encroachment of agricultural production activities to forest areas may lead to further forest fragmentation. Its regular disturbance should be managed.   Keywords - landscape ecology, patch, fractal dimension, fragmentation, landscape,landscape metrics, Geographic Information System, Hinabian-Lawigan Watershed, Southern Leyte, Philippines

scholarly journals BUILDING INFORMATION MODELING (BIM) AND GEOGRAPHIC INFORMATION SYSTEM (GIS) DATA COMPATIBILITY FOR CONSTRUCTION PROJECT

2021 ◽  
Vol 6 (24) ◽  
pp. 278-289
Author(s):  
Wan Nor Fa’aizah Wan Abdul Basir ◽  
Uznir Ujang ◽  
Zulkepli Majid
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Data Exchange ◽  
Large Scale ◽  
Building Information Modeling ◽  
Construction Project ◽  
Geographic Information ◽  
Information Modeling ◽  
Gis Data ◽  
Building Information

Building Information Modeling (BIM) is a technology that focusing on the building element properties to the construction components which cover the interior and exterior building, while Geographic Information System (GIS) describe to the technology that can provide the large-scale information which cover inside and outside buildings (spaces and areas). In construction project application, BIM technology already been used as a worldwide tool while GIS rarely been applied. Each technology contains their own advantages that can be utilized in the construction project application. To bring the best effective approach in construction project, the integration between BIM and GIS technology can be considered. This paper presented an attempt in integrating BIM and GIS by using FME as a data integration platform to solve the limitation of BIM in construction project by using advantages of GIS. Through this research, an investigation of the data exchange during integration process between BIM and GIS will be look up. By using this approach, it is possible to store the BIM and GIS data in one environment. The end results for this paper will cover the method of the data exchange between BIM to GIS and GIS to BIM. Besides that, this paper highlight how GIS can solve the limitation in BIM in construction project.

GEOGRAPHIC INFORMATION SYSTEM STANDARDS FOR U.S. ENVIRONMENTAL PROTECTION AGENCY'S OIL SPILL PROGRAM

2001 ◽  
Vol 2001 (2) ◽  
pp. 1125-1127
Author(s):  
Ray Worley ◽  
Mark Keller
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Geographic Information ◽  
Mapping Tool ◽  
Units Of Analysis ◽  
Gis Tools ◽  
Gis Data ◽  
Data Elements

ABSTRACT The Oil Program Center at the U.S. Environmental Protection Agency (EPA) Headquarters is developing geographic information system (GIS) standards to aid EPA's 10 regions in developing and implementing GIS. GIS can support spill response, contingency planning, risk analysis, training and exercises, inspections and enforcement actions, reporting, incident analysis, cost recovery, and outreach. By developing and promoting standards, the Oil Program Center hopes to ensure that GIS development is targeted at the broadest practical user base and considers all aspects of EPA's oil program. In addition, GIS standards will promote consistency between EPA regions, promote data sharing, reduce duplication of effort, and focus attention on using GIS as an analytical tool rather than just as a mapping tool. The standards also may promote greater consistency between the Oil Program Center and other offices within EPA; for example, standards promote watershed-based analysis, which is consistent with other offices' use of watersheds as units of analysis. The standards address the following issues: Minimum essential data elements Data verification and accuracy standards Standard symbols and icons System design and data structure Because the specific needs of regions differ, the GIS tools that they develop will reflect these differences. GIS data standards, however, will promote compatibility across the regions to facilitate collaboration and expand prevention, preparedness, response, and outreach capabilities.

Techniques for Building Multijurisdictional Geographic Information System Platforms for Transportation Analysis

2002 ◽  
Vol 1804 (1) ◽  
pp. 187-195
Author(s):  
Kai Han ◽  
Jeannette Montufar ◽  
Scott Minty ◽  
Alan Clayton
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Data Sharing ◽  
Spatial Data ◽  
Geographic Information ◽  
Data Sources ◽  
Data Sets ◽  
Data Interoperability ◽  
Gis Data ◽  
Transportation Applications

Transportation analysis involving multiple jurisdictions requires data sharing and spatial data interoperability among geographic information system (GIS) data sets. Data sharing and spatial data interoperability issues related to multijurisdictional transportation analysis are discussed. Specific techniques based on practical data-sharing, problem-solving experience are developed. To further enhance the data-sharing process, a conceptual framework is established to guide technique implementations. Regional GIS transportation (GIS-T) platforms integrated from various data sources by applying the framework and the associated techniques are also presented. To better support different transportation applications, an open GIS-T platform is proposed, consisting of a series of customized base maps, each tailored to suit individual applications and, as a whole, linked together by inherently established interoperability.

scholarly journals Design of Private Geographycal Information System (GIS) Server for Battlefield Management System

2017 ◽  
Vol 1 (1) ◽  
pp. 23
Author(s):  
Alde Alanda ◽  
Erwadi Bakar
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Simulation System ◽  
Earth Surface ◽  
Design And Implementation ◽  
Simulation Process ◽  
Data Application ◽  
Simulation Based ◽  
Gis Data ◽  
Existing Data

Geographic Information System (GIS) data is needed for model earth surface in 3D simulation for SAR operation to make simulation process as real as possible. Adding integrated GIS data server to simulation system make simulation application user does not need to input and prepare the GIS data manually, by reducing simulation application user task, user can more concentrate on simulation process.In this research the design and implementation of GIS data application that can provide the data needed by a simulation application using existing data on the online map provider. Application designed to display data necessary to carry out the conversion of GIS data to the format used in the simulation . Based on the test resuls of the conversion of GIS data to map format generated simulation has the same texture to the original map. Simulations can be run by using the map conversion and  the simulation can run using real map but the level of height accuracy  is not optimal.

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