Implementing spatial segregation measures in GIS

Geographic Information Systems (GIS) are an important tool in the environmental management of protected areas, offering advanced technological methods for biodiversity protection and spatial planning.In the Divjakë-Karavasta National Park, the integration of GIS technology has significantly improved the monitoring and management of its rich ecosystems. The use of GIS in this park has enabled a detailed inventory of the health of vegetation, enabling the creation of accurate maps of the distribution of biodiversity.These maps are essential for identifying areas of special ecological importance and for determining appropriate conservation measures. GIS and RS technology provides a solid methodology used to evaluate and analyse different factors that influence a decision with regards to forest health. It helps assess risk to forest health by considering various ecological, climatic and environmental factors(temperatures, humidity, the spread of fires, air pollution etc.) affecting forest health, thus enabling improved management of the forest environment. A set of satellite images from SN32-Satellite Nusat 32 (Albania 1)/SN33-Satellite Nusat 33 (Albania 2), year 2024 are used as main data source to analyze risk factors in forest health of the park. Important indices namely Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Land Cover (LC) and Road infrastructure have been calculated in a GIS environment using ArcGIS Desktop 10.8.2/Pro 3.2. The spatial patterns that study reveal indicate that the majority of forest areas in Divjake-Karavasta National Park resides in an adequate environment under supportive health factors.Moreover, GIS enables real-time monitoring of environmental changes, such as the appearance of invasive species or habitat degradation, providing valuable data for quick and effective interventions. The integration of GIS in the management of the Divjakë-Karavasta. National Park has brought many benefits, but it has also encountered various challenges. One of the main challenges is the need for staff training in the use of advanced GIS technology and the provision of the necessary equipment. However, the benefits of this integration are obvious, including improved efficiency in natural resource management and increased capacity to respond to environmental threats.

Recent advances in wireless communications and networks have integrated relatively new technologies such as Global Positioning System (GPS), to the popular Global System for Mobile Communication (GSM), second generation cellular systems and the Geographic Information Systems (GIS) technologies. Automatic Vehicle Location (AVL) is based on a combination of GPS, GIS and telecommunication technologies. Automatic Vehicle Tracking systems are more and more used for different purposes, especially those related to tracking one vehicle or a fleet of vehicles. In this work, we introduce a new AVL system, which is based and developed under GIS software environment. The centralized software at the control station offers a new technology of transferring the intelligence of tracking system from the car unit, into the control office PC software. Centralized software will reduce the programming efforts in the car unit and will offer better fleet management. Moreover, the core of our system is based on the objects or the controllers of the GIS software, which reduces dramatically the overall system cost. Our system provides an easy access to change the functions of the system, with great possibility to satisfy the local needs. The design of our software will be presented with an explanation of the new supporting technologies that were to create the system. Finally, our software system has been validated using data from local road networks. Copyright © 2005 John Wiley & Sons, Ltd.

A geographic information system (GIS) can contribute significantly to the correct interpretation of the slick signatures visible on synthetic aperture radar (SAR) images. Initially, GIS has proven to be an excellent management tool for resource assessment, oil spill response and planning, and damage assessment. The GIS approach to the problem of oil spill mapping includes integration of the geographical, remote sensing, oil and gas production/infrastructure data and slick signatures, detected by SAR, in GIS. Compiled from data from several sources including nautical maps, geodatabases, ground truth and remote sensing data, GIS allows the retrieval of key information, such as predicting oil spill locations, revealing offshore/onshore sources, and estimating the intensity of oil pollution. SAR and GIS technologies can improve the identification and classification of oil spills, leading to construction of the final product, an oil spill distribution map. This approach has been applied to oil spill mapping in the Sea of Okhotsk, the Caspian Sea, the Black Sea and the Gulf of Thailand. We conclude that the combination of GIS and SAR technologies provides an ideal solution for understanding the spatial/temporal distribution of oil spills in the marine environment and is considered as the core of the oil spill monitoring system.

Throughout the course of human history, significant pressures have been in place to develop the coastline. Whether these pressures are a result of commercial and industrial needs or recreational preference, humans have always tended to settle at or near the waterfront. While obvious benefits can be reaped from this anthropogenic pattern, it also results in significant portions of the world's population subject to flood hazards. With the potential for these hazards to increase due to climate change, coastal zone managers and planners require tools to mitigate the risk to this population. One such tool is Geographic Information Systems (GIS). With GIS technology being at the forefront of Federal Emergency Management Agency's (FEMA) Map Modernization efforts, it has proven to be an effective tool in coastal hazard mitigation. The GIS technology is extensively used to evaluate land use and population change in the coastal areas which ultimately drives the coastal hazard mapping. The identification of risk requires analyzing large GIS data sets including topographic data (e.g. TIN {triangular irregular network} and GRID), orthophotography, land use data, and census population data. The GIS technology can effectively analyze these large data sets using the calculation algorithms built in to the GIS software such ArcGIS and present information that will guide decision makers. The 3D rendering capability of GIS software can be used to visualize various scenarios which aid in effective hazard identification and mitigation. The 3D GIS mapping and animation tools can also be applied to simulate various disaster scenarios that can ultimately aid planners in prevention of human and property loss during coastal disasters. In FEMA Region I, CDM, a FEMA study contractor and its partner OCC have been involved in numerous coastal hazard studies across New England. Together CDM and OCC have scoped total of six counties and have been involved in coastal engineering and mapping activities in more than 10 counties across New England. This paper will present methodologies to analyze various data sources and identify coastal flooding risks.

This article will discuss how to improve the ability to protect the collection mural with Lidar and Geographic Information System (GIS) technology. Firstly, we gain three dimensional point clouds through the Lidar technology, and make high-precision Digital Orthophoto Map (DOM), which has the same scale as the real collection mural. Secondly, the spatial disease database will be built based on the DOM of collection mural with the GIS technology. Then we can get some useful dataset for protecting collection mural, such as disease map and trend map. Disease map, based on some spatial analysis and spatial statistics, will tell you where the disease is, and how serious the disease is. Lastly, but importantly, we can classify the disease grade based on the collection mural with decision tree. So protector of collection mural knows what’s the most serious disease. It is better than the traditional methods both in accuracy and efficiency. Finally, this article has confirmed the related method efficiency and the precision in the collection mural of Greatly Summons Temple.

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.

The role of environmental management is extremely important in human life because of its contribution to environmental protection and strategies. In modern society, nevertheless, facing the challenges in land, water, and air quality management in reality is unavoidable. Understanding the information on variability and features of environmental issues is necessary to support decision-makers in establishing environmental management planning. Spatial information and data should be considered as basic initial knowledge of environmental management. Among various technologies, Geographic Information Systems (GIS) is known as one of the most popular tools to store, analyze, and visualize data relating to geographically referenced information which can mitigate these challenges more effectively and accurately. The main purpose of this paper is to emphasize how GIS applications in environmental management, discuss the challenges of GIS technology in environmental management, and provide recommendations for future research directions. Many articles over the last decades were reviewed to highlight the application of GIS in environmental management. These results indicated GIS applications support land, water, air quality, and waste management. Moreover, it is a useful tool to monitor and assess environmental quality and in environmental planning and decision-making. For the limitation of GIS application, it is obvious that accuracy assessment and sensitivity analysis should be noticed and assessed although GIS application may strongly support decision-making in environmental management. Emerging GIS technologies and tendencies could help address these challenges. In future, GIS should be integrated along with new technologies and different decision-making algorithms in further steps for developing and supporting spatial decision-support systems more efficiently.

Rational use and protection of soils in market conditions requires adequate application of new scientific and methodological approaches. One of such systems-analytical methods of organizing a soil cadastre is the combination of traditional ground-based methods with geographic information systems (GIS) technologies based on the widespread use of aerospace images of high resolutions. The totality of information necessary for mapping soil cover structures and their quantitative assessment is described in GIS databases. Data integration is implemented through a spatial and attributive component in the form of: the results of topographic and thematic maps. At the same time, the creation of attributive GIS databases involves the digitization of thematic maps linked in a single cartographic projection (which was a topographic map at a scale of 1:50,000). As results of the research, digital soil maps for the Chingirlau district of the West Kazakhstan region were created on the basis of GIS technologies, using the ArcGIS software products. It was established that within the limits of the Chingirlau district of the West Kazakhstan region, dark chestnut soils in combination with various soil combinations pre-dominate in the structure of the soil cover. They are formed on loess-like loams in the conditions of the dry steppe zone with a non-leaching type of water regime under fescue-grass, forb-grass-wormwood, meadowsweet-grass with wormwood plant communities. To improve the quality of generalized maps (district, regional, etc.), it is necessary to create objective automated methods for generalizing maps in a digital environment. A method for compiling a digital soil map using the ArcGIS soft-ware product, accessible to a wide range of GIS users, has been developed. To compile soil maps, it is possible to use any scanned cartographic bases, photoplans, and other raster materials. Based on the developed methodology, a large-scale soil map of the Chingirlau district of the West Kazakhstan region was created on the basis of soil maps of rural districts made using GIS technologies.

The Baltimore City Fire Department (BCFD) has been installing smoke alarms city wide for more than three decades. Though data on each visit are entered into a database, no system existed for using these data for planning or evaluation. The objective of this study is to use Geographic Information System (GIS) technology and existing databases to 1) determine the number of residences in need of a home visit; 2) determine total visits, visits per household, and number of homes entered for eligible households; and 3) demonstrate integration of various data via GIS for use in prevention planning. The tax assessment database was queried to determine the number of eligible (as determined by BCFD policy) residences in need of a visit. Each attempted BCFD home visit was coded to identify, if the BCFD personnel interacted with residents ("pass door") and installed alarms. Home visits were geocoded and compared to the tax assessment database to determine city wide pass door rates. Frequency of visits was run by individual residences to measure efficiency. A total of 206,850 residences met BCFD eligibility for a home visit. In 2007, the BCFD attempted 181,757 home visits and 177,213 were successfully geocoded to 122,118 addresses. A total of 122,118 eligible residences (59%) received a home visit. A total of 35,317 residences (29%) received a repeat visit attempt. The pass door rate was 22% (46,429) of all residences. GIS technology offers a promising means for fire departments to plan and evaluate the fire prevention services they provide.

Use of GIS technology to analyse the health effect of exposure to heavy traffic pollution in an Italian general population sample

The management system which is based on handling GIS database files and remotely sensed imageries on Geographical Information System (GIS) environment is an essential tool to guide and regulate the production systems and marketing activities of product chains. In the case of guava, the management system has to be fed with a specific and structured field database and its metadata to verify the phenotypic status of guava trees and to characterize the production system applied by the producer in agronomic terms (coordinate data, planting frame, vigor, health etc). This data is useful to determine agronomic conditions to be incorporated as a field test in a supervised classification process on SPOT satellite images (PAN and MS) which is used as a mean to scale the punctual field observation data. As a numerical value, the raster structure of satellite images and the numeric value for each cell represents guava photosynthetic activity rate. Along with this, the isolation of guava's phenotypic signature in DN units will feed the supervised classification procedure allowing the user to generate thematic maps per class. On GIS environment, a multi-assessment analysis is applied in order to assign a weight to each component on the project. The analysis is based on spatial analysis vicinity functions applied to guava orchard locations, proximity to collecting centers, roads, and highways. The visual immediacy on thematic maps will allow the decision makers to implement their own criteria analysis to plan the market destination of guava production volume weeks after harvest (fresh market or industry) in Calvillo County.

Even just a decade ago having a chapter dedicated to Geographical Information Systems (GIS) in a book on methods in history would have been seen as unusual, but such is the development of digital mapping and spatial technologies over recent years that historians cannot now afford to be without them. This chapter provides an introduction to GIS and its applica- tion and potential for historical study. Given the scope of the chapter it can only be reasonably cursory and aims to show what can be done with GIS in historical research (and teaching), with some pointers for historians on how they might employ GIS and spatial technologies in their own work. It should become clear that GIS is no longer a highly specialised and technical approach to handling spatial and temporal information but an increasingly user-friendly and accessible basis for integrating, analysing and visualising historical and geographical data of a wide variety, both qualitative and quantitative in nature. With this in mind, the chapter sets out: first, what GIS is and how it works; second, why historians might wish to use GIS; thirdly, how GIS is useful for providing insights into the past; and lastly, what the future might be in using GIS for historical research, particularly its problems and challenges. The chapter also provides some directions for further study, including the locations of a growing number of digital online resources that use GIS to disseminate historical material.

This paper mainly introduces the methods of extracting landslide information using ALOS(Advanced Land Observing Satellite) images and GIS(Geographical Information System) technology. In this study, we classified images using three different methods which are the unsupervised、the supervised and the PCA(Principal Components Analysis) for extracting landslide information based on characteristics of ALOS image. From the image classification results, we found out that the quality of classified image extracted with PCA supervised method was superior than the other images extracted with the other methods. But the accuracy of landslide information extracted from this image classification was still very low as the pixels were very similar between the landslide and safety regions. It means that it is really difficult to distinguish those areas with an image classification method alone because the values of pixels between the landslide and other areas were similar, particularly in a region where the landslide and other areas coexist. To solve this problem, we used the LSM(Landslide Susceptibility Map) created with ArcView software through weighted overlay GIS method in the areas. Finally, the developed LSM was applied to the image classification process using the ALOS images. The accuracy of the extracted landslide information was improved after adopting the PCA and LSM methods. Finally, we found that the landslide region in the study area can be calculated and the accuracy can also be improved with the LSM and PCA image classification methods using GIS tools.

Geographic Information System (GIS) technology has many applications and plays a vital role in the majority of the daily operations by government and public administration. However, due to its technical complexity and cost, communities lacking the expertise and resources cannot benefit from this technology. The OpenCIS project, a user‐friendly free Open Source GIS‐based Web Community Information System, seeks to address this issue by bridging the gap between a simple map viewer and full GIS, representing one of the first steps towards the goal of grassroots empowerment through GIS technology.

Urban green fields planning is an important part of urban resources and the environment building, with the rapid development of remote sensing (RS) and geographic information systems (GIS) technology, urban parks and green building research are going with new ideas and methods. This paper discusses the application of RS and GIS technology direction and mode of its application process in green field planning.