Geographic Information Systems as Decision Tools

Due to their extension and complexity, problems concerned with geographic space are usually classified as ill or unstructured. For these reasons decision-making processes (DMP) that conclude with the selection of optimal or satisfactory solutions require effective and efficient means of support. Spatial Decision Support Systems (SDSS) are computer systems developed to support DMP in which the problems have geographic dimensions and whose structure is complex or impossible to delineate. These systems are functionally composed of data and scientific models managed with the aim of providing maximised support to DMP. The component represented by spatial data is one of the main obstacles that have to be overcome for SDSS to give effective support. Geographic Information Systems (GIS) have been a paradigm in SDSS development strategies, fundamentally due to their capacity to collect, store, and handle spatial data. The scientific modelling component, represented by mathematical models of natural physical processes, usually is implemented in SDSS through specific software subsystems. Especially in the last seven years there has been great scientific interest in SDSS accompanied by a proliferation of adjacent technologies. Some authors have attempted to classify SDSS without, however, reaching a generally accepted proposal. This lack of clarity has made detailed analysis of existing systems and development of new projects more difficult. The aims of this research were: a) identify and analyse the main variables that determine current application software development methodologies in the field of SDSS; b) provide a taxonomy of these methodologies, with the objectives of being generic, general, and practical; c) identify and analyse the strategy that presents the greatest flexibility to develop effective SDSS. The research was based on a bibliographic survey and is part of the doctoral thesis of first author. The paper presents and criticises relevant issues about different development strategies and the respective systems produced. Three main variables were identified and guided the development of the taxonomy of the strategies. The paper proposes five taxonomic classes of coupling GIS technology and scientific modelling subsystems. These classes are defined and the paper argues that they are sufficient to categorise the main current methodologies as well as suggest places to expect new technologies. Each class is also exemplified with a number of SDSS applied to the watershed DMP domain. Within these classes, the research identified and analysed the one most likely to show the greatest flexibility to develop effective SDSS

To develop refined agriculture and improve Agricultural productivity, a new monitoring system has been proposed in this paper. Based on the actual situation of early agriculture and the actual national conditions of China, Geographic Information System (GIS) technology and Global Positioning System (GPS) technology have been combined. Based on the combination of GIS technology and GPS technology, the results show that the position of field vehicles can be displayed in the electronic MAP in real time within 5% error. On this basis, Agricultural production and cultivation can be realized, and the monitoring system can realize the real-time display of vehicle location in the field on electronic MAP to guide production and cultivation. The static test shows that the positioning accuracy of the four GPS receivers is the worst, and the positioning accuracy of MAP330 receiver and GPS25 receiver is better. However, the positioning accuracy of AGl32 receiver is the highest with the 0.37m error when compared with the error of 1.2m of other machines. Using GPS to measure the area, the error of farmland area and farmland side length is less than 5%, and the precision AGl32 receiver for precision Agricultural measurement is also improved with the proposed model.

Wireless technology applied to GIS

This is the second part of a two-part discussion, in which we will provide an overview of the use of GIS and GPS in environmental analysis and enforcement. Geographic Information Systems (GIS) describes a system which manages, analyses and displays geographic information. Environmental applications include analysis of source, extent and transport of contaminants, nonpoint runoff modeling, flood control, and emergency response support. The ability to examine spatial relationships between environmental observations and other mapped and historical information, and to communicate these relationships to others, makes GIS valuable in environmental forensics. The US Environmental Protection Agency currently requires the inclusion of locational information with all other environmental data that is collected. Geographic Information Systems is a complex tool that requires careful planning and design to be successfully implemented. Choices in hardware, software and data development must be based on evaluation of project objectives, analytical requirements, data availability and data development considerations. Data sets must be evaluated and documented with metadata. The Global Positioning System (GPS) is a satellite-based system which provides highly accurate, three-dimensional position information anywhere on the earth's surface. Using portable radio receivers, field analysts can easily record the positions of spill sites, sampling locations and other environmental features. Spatial accuracy of GPS ranges from 20-30 m (single receiver) to 1-5 m (differential GPS) for navigation-grade instruments, and down to millimeter level accuracy for geodetic units. Global Position Systems can be used not only to capture spatial information into a GIS system, but also to evaluate and quantify the spatial accuracy of existing digital map data, and to provide control points for existing aerial photographs and other remotely-sensed data.

Abstract— Vehicle tracking system using GPS and GPRS integration googlemap provide information that is maximized with the technology of GPS (Global Positioning System) receiver which can indicate the position of the vehicle with the map and the ability of the appointment of direction and position coordinates (x, y or latitude, longitude) textually and visual at any location. Vehicle tracking system is built using equipment GIS (Geographic Information System) and dedicated to smartphones which support Global Positioning System (GPS), as well as portable computers, using General Packet Radio Service (GPRS) as a connection to the internet. The hardware used is a smartphone that supports GPS with supporting tools used are GoogleMaps, Notepad + +, NetBeans IDE 6.5.1, Mysql, Java (J2ME), PHP, JavaScript. The results of this system in the form of tracking system capable of monitoring the movement of vehicles on an ongoing position by utilizing GPS and GPRS as the sender of the wireless data and Internet connections. Keywords— GIS, GPS, GPRS, googlemaps, J2ME,

Global positioning system (GPS) is a satellite navigation system which delivers specially coded satellite signals that can be communicated in a GPS receiver, allowing the receiver to compute position, velocity and time of the object. GPS technology contained the space segment, control segment and the user segment. The most essential part of GPS system, the GPS receiver and user communities are present in user segment. GPS receiver acquires signals and converts the radio signals into position, velocity and time estimates1. Google Earth is not a geographic information system (GIS) with the extensive analytical capacities, but it is much easier than those high performance analytical software packages.

Remote sensing has served as an efficient method of gathering data about glaciers since its emergence. The recent advent of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) has created an effective means by which the acquired data are analysed for the effective monitoring and mapping of temporal dynamics of glaciers. A large number of researchers have taken advantage of remote sensing, GIS and GPS in their studies of glaciers. These applications are comprehensively reviewed in this paper. This review shows that glacial features identifiable from aerial photographs and satellite imagery include spatial extent, transient snowline, equilibrium line elevation, accumulation and ablation zones, and differentiation of ice/snow. Digital image processing (e.g., image enhancement, spectral ratioing and automatic classification) improves the ease and accuracy of mapping these parameters. The traditional visible light/infrared remote sensing of two-dimensional glacier distribution has been extended to three-dimensional volume estimation and dynamic monitoring using radar imagery and GPS. Longitudinal variations in glacial extent have been detected from multi-temporal images in GIS. However, the detected variations have neither been explored nor modelled from environmental and topographic variables. GPS has been utilized independent of remote sensing and GIS to determine glacier ice velocity and to obtain information about glacier surfaces. Therefore, the potential afforded by the integration of nonconventional remote sensing (e.g., SAR interferometry) with GIS and GPS still remains to be realized in glaciology. The emergence of new satellite images will make remote sensing of glaciology more predictive, more global and towards longer terms.

Sowing failure or poor emergence due to limited rainfall is a serious problem for crop production in arid and semiarid regions in north China. The objective of this study was to design a variable rate precision irrigating hill-seeder, which could change the amount of irrigating water automatically according to the soil moisture content of the field. A control system integrating single-chip computer, Global Positioning System (GPS), Geographic Information System (GIS) and variable rate application (VRA) technologies was developed. The system employed a high speed single-chip W78E58 unit as the control center, a high capacity U-disk for GIS data transfer, and a GPS receiver as the locating device. The system could detect a falling seed through a photoelectric sensor installed inside the collector of the seeder and then open an electromagnetic valve to control water delivery so that the seed and water could fall at the same time and place. The amount of water was determined by the minimum soil moisture content required for seed germination. The control system was adapted to a maize hill seeder. A static calibration experiment showed that the controller had very good linearity. The detection rate of the photoelectric sensor for maize seeds reached above 99%, indicating that the control system had high control accuracy.

In order to improve the information management of the modern digital agriculture, combined several modern digital agriculture technologies, namely wireless sensor network (WSN), global positioning system (GPS), geographic information system (GIS) and general packet radio service (GPRS), and applied them to the information collection and intelligent control process of the modern digital agriculture. Combining the advantage of the local multi-channel information collection and the low-power wireless transmission of WSN, the stable and low cost long-distance communication and data transmission ability of GPRS, the high-precision positioning technology of the DGPS positioning and the large-scale field information layer-management technology of GIS, such a hybrid technology combination is applied to the large-scale field information and intelligent management. In this study, wireless sensor network routing nodes are disposed in the sub-area of field. These nodes have GPS receiver modules and the electric control mechanism, and are relative positioned by GPS. They can real-time monitor the field information and control the equipment for the field application. When the GPS position information and other collected field information are measured, the information can be remotely transmitted to PC by GPRS. Then PC can upload the information to the GIS management software. All the field information can be classified into different layers in GIS and shown on the GIS map based on their GPS position. Moreover, we have developed remote control software based on GIS. It can send the control commands through GPRS to the nodes which have control modules; and then we can real-time manage and control the field application. In conclusion, the unattended automatic wireless intelligent technology for the field information collection and control can effectively utilize hardware resources, improve the field information intelligent management and reduce the information and intelligent cost.

BackgroundGeographical Reconnaissance (GR) operations using Personal Digital Assistants (PDAs) and Global Positioning Systems (GPS) have been conducted in the elimination provinces of Temotu, Solomon Islands and Tafea, Republic of Vanuatu. These operations aimed to examine modern approaches to GR to define the spatial distribution of target populations to support contemporary malaria elimination interventions.MethodsThree GR surveys were carried out covering the outer islands of Temotu Province (October - November, 2008); Santa Cruz Island, Temotu Province (February 2009) and Tanna Island, Tafea Province (July - September 2009). Integrated PDA/GPS handheld units were used in the field to rapidly map and enumerate households, and collect associated population and household structure data to support priority elimination interventions, including bed net distribution, indoor residual spraying (IRS) and malaria case surveillance. Data were uploaded and analysed in customized Geographic Information System (GIS) databases to produce household distribution maps and generate relevant summary information pertaining to the GR operations. Following completion of field operations, group discussions were also conducted to review GR approaches and technology implemented.Results10,459 households were geo-referenced and mapped. A population of 43,497 and 30,663 household structures were recorded during the three GR surveys. The spatial distribution of the population was concentrated in coastal village clusters. Survey operations were completed over a combined total of 77 field days covering a total land mass area of approximately 1103.2 km2. An average of 45 households, 118 structures and a population of 184 people were recorded per handheld device per day. Geo-spatial household distribution maps were also produced immediately following the completion of GR fieldwork. An overall high acceptability of modern GR techniques and technology was observed by both field operations staff and communities.ConclusionGR implemented using modern techniques has provided an effective and efficient operational tool for rapidly defining the spatial distribution of target populations in designated malaria elimination zones in Solomon Islands and Vanuatu. The data generated are being used for the strategic implementation and scaling-up of priority interventions, and will be essential for establishing future surveillance using spatial decision support systems.

Collection of Municipal Solid Waste (MSW) is important in every waste management program. Communal container collection systems appear most prevalent in many developing countries. However, this collection system is associated with problems such as overflow of waste containers, ground dumping at collection sites, and open/indiscriminate dumping at unauthorized places. The spatial distribution of these activities present potential contamination challenges to water resources. Spatial information on Municipal Solid Waste Collection/Dump Sites (MSWCS) is essential for Municipal Solid Waste Management (MSWM) decision-making, including siting and collection route planning, and dumps cleanup. Integration of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) present a platform to capture, map, and analyze spatial MSWM issues. This study applied GIS and GPS technologies to map MSWCS in Wa town, Ghana. Wa Municipality waste collection system efficiency was analyzed based on spatial availability of communal containers. A GIS model was developed and used to analyze proximity of MSWCS to boreholes drinking water sources. A pollution risk map was also developed to analyze the potential impact of indiscriminate dumps on hand-dug wells and surface water in Wa. The results reveal poor management in a significant number (about 67%) of MSWCS sites. Fifteen percent of mechanized boreholes failed the minimum proximity requirement (≥100 m) of the model. This study findings illustrate that MSWM in developing countries may be improved using GIS and GPS technologies. The approach used for Wa could be replicated in other towns in Ghana and other developing nations with similar MSWM problems to enhance policy and management decision-making.

Advancement of Geographic Information System (GIS) technologies and Artificial Intelligence (AI) supports development of Decision Support System (DSS) and Spatial Decision Support System (SDSS) to solve complex real life problems. Its areas of implementation encompasses diverse fields from defense to civil departments, from meteorology to disaster management, from traffic analysis to network planning etc. Centre for Development of Telematics (CDOT) has developed a software system for analyzing and identifying optimized GIS routes for laying optical fiber who's planning has been done by Bharat Broadband Network Limited (BBNL). BBNL has done planning for connecting Customer Premise Equipment (CPE) to the Central Office (CO). These routes have been planned by doing manual foot survey. This software system analyses whether the planned GIS routes are optimal or not and suggests optimized fiber routes for planning. In this paper we have presented a solution to the problem that we faced during above mentioned project execution. We have suggested an algorithmic solution based on C4.5 Decision Tree Machine Learning Algorithm. This software system first learns based on user input and then creates rules. Using these rules software system provides fiber planning of optical network over GIS. This algorithm, using machine learning, finds best possible route from a set of routes calculated using different GIS data sources.

A Geographic Information System (GIS) can be described as a sophisticated, spatial software that allows for combining different types of data including, but not limited to, demographics, health data, and community resources, all connected by an underlying map. The GIS can then be used to investigate various relationships, trends, and patterns between the different layers of data. In addition to analyzing various secondary data, such as census information or summarized electronic health records, utilizing geospatial technologies, for example, field mapping devices or global positioning system (GPS) units, means that a detailed insight can be gained into the health consequences of any environment. Examples of what one can determine using GIS include which health outcomes cluster around a water course; what is the most effective route for a rural patient to travel to care; or which neighborhoods, and even intersections, generate spikes in pediatric injuries.There are many GIS applications in both public health and clinical health research. In addition, several other aligned disciplines, such as sociology, social work, urban planning, and geography, use GIS to visualize and analyze geographic data that have a relevance to health phenomena. For example, GIS has been utilized to study heart disease mortality and access to hospitals (Yamashita & Kunkel. 20101: breast cancer and historical exposure to pesticides (Brody et al.. 2004): clusters of opioid prescription abuse in New Mexico (Brownstein. Green. Cassidv. & Butler. 20101: obesity and neighbor fast-food outlets (Li, Harmer, Cardinal. Bosworth, & Johnson-Shelton, 20091: and sexually transmitted diseases epidemiologic patterns in Fort Bragg, North Carolina (Zenilman et al.. 2002). The appreciation of how space and place intersect with health, and a suite of important, new geospatial technologies have opened new avenues of research and given rise to several multidisciplinary fields including medical geography, geomedicine, health geography, and geographic gerontology. In spite of having different names and sometimes different disciplinary perspectives, these fields all focus on the interrelationships between geographic/environmental attributes and health outcomes.However, the manner in which our environment affects health and wellbeing is still in its infancy in the nursing literature. This column will provide a basic introduction as to how GIS can be used as a research tool to study various nursing phenomena. We will begin by reviewing selected examples of the relatively few nursing studies that have utilized a GIS.Examples of GIS Use in the Nursing LiteratureBloch (2011! examined the correlation between the exposure to stressful environments (as indicated by crime rate and poverty) and preterm birth rate in foreign-born and United States (U.S.)-born African American mothers. Bloch studied 2000 U.S. Census data and Philadelphia crime data, using a GIS, to show how stressful neighborhoods are significantly associated with a higher prevalence of preterm birth for foreign-born and U.S.-born black mothers. Bloch established these relationships by geographically manipulating and overlaying data on births, crime, poverty, race, and nativity into common areas (census tracts).In another example, Madigan, Wiencek, and Vander Schrier (2009) used GIS to examine the availability of community-based, end-of-life care providers to the elderly in rural areas. The researchers created maps for eight states showing the distribution of community-based, end-of-life providers per 1,000 elders at the county level by degree of rurallty. The analysis showed that more than 85% of rural counties in Arkansas and Louisiana did not have end-of-life hospice providers. Madigan et al. noted that studies such as theirs provide crucial information for making social-policy decisions.It is important to recognize that Madigan et al.'s research was conducted at a different geographic scale than that of Bloch's (2011). …

This survey was created by The University of Tennessee (UT) Libraries to assess the need for providing geographic information system (GIS) and global positioning system (GPS) services to the UT Knoxville, community. In the past few years, the UT Libraries have seen an increase in the number of students and faculty who need help with GIS-related technologies (GIS and GPS). To meet these needs, the library has expanded virtual training and begun to collaborate with other departments on campus to assist users with GIS needs. This survey attempts to answer the question: Where does the library fit into campus GIS-related services? Graduate students and faculty who participated in the survey agreed that the library should play a central role in offering GIS-related services. However, the survey results show that there is not enough training available with GIS-related technologies on campus. If the library is to play a central role, then additional resources should be considered to support GIS-related services in the library and across campus.

Enhanced validity and reliability of spatial decision support systems (SDSS) for sustainable transportation decision-making