Spatial Decision Support Systems

Planning of shale gas infrastructure and drilling sites for hydraulic fracturing has important spatial implications. The evaluation of conflicting and competing objectives requires an explicit consideration of multiple criteria as they have important environmental and economic implications. This study presents a web-based multi-criteria spatial decision support system (SDSS) prototype with a flexible and user-friendly interface that could provide educational or decision-making capabilities with respect to hydraulic fracturing site-selection in eastern Ohio. One of the main features of this spatial decision support system is to emphasize potential trade-offs between important factors of environmental and economic implications from hydraulic fracturing activities using a weighted linear combination (WLC) method. WLC is a simple approach that integrates users’ preferences into an overall assessment and offers a rationale for trade-offs between decision criteria and objectives. In the prototype, the GIS-enabled analytical components allow spontaneous visualization of available alternatives on maps which provide value-added features for decision support processes and derivation of final decision maps. The SDSS prototype exhibits a straightforward decision-making procedure with easy-to-use web interface and facilitates non-expert participation capabilities. It comprises of a mapping module, decision-making tool, group decision data statistics, and social media sharing tools. The system architecture combines a variety of closely related components using Silverlight, ArcGIS API for Silverlight, ArcGIS Server, and ArcSDE for SQL Server software. During the decision-making process, users are
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guided through a logical flow of successively presented forms and standardized criteria maps to generate visualization of trade-off scenarios and alternative solutions tailored to their personal preferences. Finally, the results and the preferences from all users are graphed for visualization and subsequent decision-making making.

The paper proposes the results of a research industry project concerning predictive maintenance process optimization, applied to a machine cutting polyurethane. A company producing cutting machines, has been provided with an online control system able to detect blade status of a machine supplied to a customer producing polyurethane components. A software platform has been developed for the real time monitoring of the blade status and for the prediction of the break up conditions adopting a multi-parametric data analysis approach, based on the simultaneous use of unsupervised and supervised machine learning algorithms. Specifically, the proposed method adopts a k-Means algorithm to classify bi dimensional risk maps, and a Long Short Term Memory (LSTM) one to predict the alerting levels based on the analysis of the last values for some process variables. The analysed algorithms are applied to an experimental dataset.

This paper is reporting on a research project undertaken jointly between the University of New South Wales (UNSW) and the NSW Department of Housing (DoH) to develop a Spatial Decision Support System (SDSS) to assist planning, management and evaluation in areas of high public housing concentration. In the paper we will describe the development of the SDSS, the specific spatial problems challenging the DoH and the potential for the system to incorporate a range of social, financial and physical data, both internal and from other sources, for interaction and presentation in a three dimensional environment. The prototype SDSS attempts to address the specific challenges of providing better service for clients of the DoH. An information audit and survey has been conducted of the department’s resources and needs. Issues identified include the management of high-rise and superlot areas, crime mapping, community interactivity, internal and intergovernmental information sharing, interoperability and maintaining confidentiality and security of data. Interactive 3D visualisation of the model is facilitated by use of the 3map free geospace platform. Use of open source code and open standards such as X3D for 3D graphics interchange allow the project to explore advanced visualisation techniques while ensuring interoperability and data longevity.

The paper reports on both methodological and substantive findings. It presents a method for generating simplified representations for regional urban populations, their geographical sub-populations and communities. the method generates greatly simplified high-resolution socio-economic profiles of populated geographical areas from complex large census data sets.

The complexity and uncertainty in decision making causes supply chains to be more adaptive. In its expansion, the supply chain not only discusses distance and time, but has considered the risks and spatial perspectives. Spatial problems are generally solved by Geographic Information Systems (GIS) and Spatial Decision Support Systems (SDSS). Both systems provide various types of spatial analysis and visualization tools arranged in a problem-solving framework. The combination of GIS and Artificial Intelligent (AI) has greatly facilitated decision makers regarding data collection and spatial analysis, data manipulation and storage. The objective of this study was proposed to consider the Internet of Things (IoT) by including intelligent systems in existing sets of tools. The contribution of this study, we proposed intelligent system collaboration in SDSS to overcome the limitations of GIS in providing a knowledge base. We recommend that IoT devices namely remote sensing, RFID, and QR code be added to the SDSS to facilitate spatial data mining interpretation and be able to provide more knowledge base support. We offer the concept of Intelligent Spatial Decision Support Systems (ISDSS) in the agro-industry supply chain. We recommend various troubleshooting features that are not available in standard statistical methods, including using the Multi Objectives Genetic Algorithm (MOGA). For further research, we suggest this concept can be implemented in agro-industrial logistics.

The  Geoinformatics  Engineer  (GE),  who  uses  mathematical  theory  and  precise  measurements  for  the  collection  and
distribution of geospatial data, plays a significant role in the oil and gas industry. The paper reviews the role the GE woul d play in
the recent oil and gas discovery in Ghana. This is because the GE is  required in the planning and execution of nearly every form of
activities  at  the  upstream,  midstream  and  downstream;  for  example  offshore  and  onshore  construction,  exploration  and
engineering for the production and dissemination of oil and gas. Ghana is at the initial stages in the commercial production  of oil
and  gas;  and  thus  needs  research  institutions  with  excellent practical  and  research skills, such  as  the  Department  of Geomat ic
Engineering (DGE), Kwame Nkrumah University of Science and Technology (KNUST), Ghana and School of Earth Sciences and
Engineering  (SESE),  Hohai  University,  China,  in  employing  Geoinformatics  theories,  applications  and  principles  for  geospatial
decision making for sustainable production of oil and gas for Ghana and the Sub-Saharan Africa. SESE expertise in 3S Technology
would greatly assist in the construction and monitoring of oil and gas infrastructures at the upstream, midstream and downstream.
The  paper  recommends  useful  suggestions  for  smooth  management  of  the  oil  and  gas  industry  focusing  on  GEs  and  research
institutions.

One of the major challenges for software, nowadays, is software cost estimation. It refers to estimating the cost of all activities including software development, design, supervision, maintenance and so on. Accurate cost-estimation of software projects optimizes the internal and external processes, staff works, efforts and the overheads to be coordinated with one another. In the management software projects, estimation must be taken into account so that reduces costs, timing and possible risks to avoid project failure. In this paper, a decision- support system using a combination of multi-layer artificial neural network and decision tree is proposed to estimate the cost of software projects. In the model included into the proposed system, normalizing factors, which is vital in evaluating efforts and costs estimation, is carried out using C4.5
decision tree. Moreover, testing and training factors are done by multi-layer artificial neural network and the most optimal values are allocated to them. The experimental results and evaluations on Dataset NASA60 show that the proposed system has less amount of the total average relative error compared with COCOMO model.

Mountain landscapes reflect long-term interactions of human beings with biophysical systems. Thus, the spatial planning process and land policies for mountain areas must be based on a thorough understanding of the spatiotemporal changes of social, economic, cultural and environmental reality as well as the inherent problems due to their particular characteristics and development constraints. In the terminology of decision-making theory, these complex spatial decision problems are called semi-structured and can be solved by decision makers with computer support. Moreover, the multifactoral nature of problems in mountainous areas requires a Multi-Criteria Decision Analysis (MCDA) involving a set of alternatives that are evaluated on the basis of different (possibly conflicting) criteria. Based on the above, Multi-Criteria Spatial Decision Support Systems (MC-SDSS) aim to improve the effectiveness of decision-making by incorporating decision-maker judgments and computer-based programs within the decision-making process. In this paper, we intend to a) present the state-of-the-art of MC-SDSSs and its significance as a planning tool when used in mountainous areas and b) to outline the multiple benefits and the effectiveness of the incorporation of Artificial Intelligence (AI) techniques in the MC-SDSS for Multisite Land Use Allocation (MLUA) procedures in mountainous areas.

Keywords: MC-SDSS, Mountainous Areas, Spatial Planning, Decision Making, Artificial Intelligence

Large-scale infrastructure projects require the acquisition of appropriate land for their construction and maintenance, while they often cause extensive fragmentations of the affected landscape and land plots as well as significant land loss of the immediately affected land owners. A good practice in this field comes from Germany. In Germany, the so-called “land consolidation for large-scale projects” is used to distribute the land loss among a larger group of land owners and to reduce the damages caused by land dissection. In this article, the results of detailed analyses of the land consolidation for large-scale projects’ procedures in Germany are presented. The procedure is coordinated by the land consolidation authority, which has to check several formal and content requirements before implementing a land consolidation procedure. The needed land for the large-scale infrastructure project has to be provided by the owners of the land plots in the land consolidation area by selling it to the developer, by balanced land-loss following the land consolidation plan or relinquishment of re-allocation of particular land owners. The main objective of this article is to introduce and analyse the aims, requirements and procedure of German land consolidation for the purpose of land acquisition by large-scale infrastructure projects associated with remarkable spatial interventions.

One of the major challenges for software, nowadays, is software cost estimation. It refers to estimating the cost of all activities including software development, design, supervision, maintenance and so on. Accurate cost-estimation of software projects optimizes the internal and external processes, staff works, efforts and the overheads to be coordinated with one another. In the management software projects, estimation must be taken into account so that reduces costs, timing and possible risks to avoid project failure. In this paper, a decision- support system using a combination of multi-layer artificial neural network and decision tree is proposed to estimate the cost of software projects. In the model included into the proposed system, normalizing factors, which is vital in evaluating efforts and costs estimation, is carried out using C4.5 decision tree. Moreover, testing and training factors are done by multi-layer artificial neural network and the most optimal values are alloc...

This paper is reporting on a research project undertaken jointly between the University of New South Wales (UNSW) and the NSW Department of Housing (DoH) to develop a Spatial Decision Support System (SDSS) to assist planning, management and evaluation in areas of high public housing concentration. In the paper we will describe the development of the SDSS, the specific spatial problems challenging the DoH and the potential for the system to incorporate a range of social, financial and physical data, both internal and from other sources, for interaction and presentation in a three dimensional environment. The prototype SDSS attempts to address the specific challenges of providing better service for clients of the DoH. An information audit and survey has been conducted of the department’s resources and needs. Issues identified include the management of high-rise and superlot areas, crime mapping, community interactivity, internal and intergovernmental information sharing, interoperabil...

There is always a growing consensus on the necessity of transforming GIS into real decision support tools. In this paper, we recommend the integration of GIS and Multi-criteria analysis methods for Market Policy, Analysis, Research and Development. We present the reasons that have led to this integration and a conceptual framework to facilitate it. It also provides a brief summary of applications and research issues for geo-spatial technologies. The paper summarizes important features, functions, capabilities for geographic technologies and finding out the proper location of new industries on the basis of site suitability analysis and its land and parcel information. It also represents a research and development and management strategy. In addition, business analysis and research topics for GIS have been discussed and analyzed. Opportunities for research are proposed including issues related to GIS management, organizational impacts, utility and facility management, collaborative issues, evaluations of decision-making effectiveness, and societal impacts in both developed and developing countries.

Abstrak-Madura merupakan salah satu pulau yang terletak di Provinsi Jawa Timur, Indonesia, yang memiliki banyak potensi wisata, namun belum ada sistem yang mewadahi hal tersebut. Akibatnya, wisatawan kesulitan mendapatkan informasi resmi mengenai objek wisata yang terdapat di Madura. Oleh sebab itu, penelitian ini dilakukan dengan tujuan membuat sebuah sistem pendukung keputusan pemilihan objek wisata di Madura agar calon wisatawan lebih mudah untuk memilih objek wisata yang sesuai dengan keinginannya. Berkaitan dengan tujuan tersebut, penelitian ini menerapkan metode logika Fuzzy Tahani sebagai model pendukung keputusan. Model ini digunakan karena peralatan utamanya adalah sebuah hirarki fungsional yang input utamanya adalah kriteria yang telah ditentukan. Hasil penelitian ini diharapkan dapat mempermudah calon wisatawan dalam mengambil keputusan dalam memilih objek wisata di Madura. Dengan menggunakan kriteria pengunjung, jarak dari pusat kota, dan review objek wisata, sistem pendukung keputusan ini mampu memberikan rekomendasi objek wisata pilihan. Berdasarkan pengujian fungsionalitas, diketahui bahwa sistem ini dapat berjalan dengan dengan presentase 100%. Kata Kunci: Fuzzy Tahani, Madura, objek wisata, sistem pendukung keputusan Abstract-Madura is one of the islands located in the Province of East Java, Indonesia, which has a lot of tourism potency but there has been no system to accommodate this. As a result, the tourists have difficulty of getting the official information about tourism objectives within Madura. Therefore, in this study was conducted with the aim of creating a decision support system for tourism object selection in Madura so that the prospective tourists find it easier to choose tourism attractions that that suits their desires. In connection with these objectives, this study applies the Fuzzy Tahani logic method as the decision support model. It is used because its main equipment is a functional hierarchy that its main input is predetermined criteria. The results of this study are expected to facilitate prospective tourists in making decisions in choosing attractions in Madura. By using the visitor criterias, the distance from the city center, and the reviews of the tourists on the attractions, the decision support system is able to provide recommendations for tourist attractions to be selected. The result of the functionality test showed determined that the system can 100% run. PENDAHULUAN Manusia tidak dapat lepas dari kegiatan berwisata, karena kegiatan tersebut dapat menghilangkan penat dan beban pikiran. Pariwisata merupakan industri yang prospektif di masa mendatang dalam kegiatan sosial (Pareira & Santoso, 2013). Tubuh manusia membutuhkan istirahat dan nikmatnya waktu libur. Dengan berwisata kebutuhan jasmani manusia tersebut akan terpenuhi. Dalam hal ini dibutuhkan suatu sistem yang mampu memilihkan tempat wisata secara cepat dan tepat. Sistem seperti ini dapat membantu bidang kepariwisataan. Wisatawan dapat terbantu dalam mendapatkan informasi dan pengambilan keputusan pemilihan objek wisata secara efektif dan efisien (Purnomo, 2013). Studi kasus ini mengambil lokasi di Madura dikarenakan masih banyak dan variatifnya objek wisata di Madura, namun belum dikenal oleh masyarakat luas (Rani, 2014). Menampilkan ranking dari tempat wisata di Madura dapat memajukan objek wisata di Madura. Dengan jumlah sekitar 60 lokasi wisata yang tersebar di 4 kabupaten, pada saat ini di Pulau Madura masih belum memiliki sistem terkomputerisasi yang dapat membantu calon wisatawan dalam memilih objek wisata sesuai dengan kriteria yang diharapkan. Mereka hanya mendapatkan pelayanan informasi dari kantor dinas pariwisata dan budaya. Calon wisatawan yang ingin mengunjungi salah satu objek wisata di Madura dan tidak memiliki pengetahuan dan pandangan terhadap hal tersebut, harus pergi ke kantor dinas pariwisata terlebih dahulu untuk pelayanan informasi. Banyaknya alternatif objek wisata yang ditawarkan masing-masing kantor dinas pariwisata, dapat

Penentuan lokasi outlet dimulai dari pencarian lahan kandidat lokasi sampai pada akuisisi lahan seringkali memerlukan waktu yang melebihi target. Hal ini disebabkan oleh prioritas yang beragam dan persepsi yang berbedabeda dari pihak-pihak yang berwenang menentukan kebijakan dalam menentukan lokasi outlet. Untuk mengatasi masalah ini diperlukan sebuah sistem pendukung keputusan yang dapat digunakan untuk melakukan perhitungan dengan cepat serta mensimulasikan berbagai prioritas dan persepsi yang beragam dari pihak-pihak penentu kebijakan di perusahaan. Dalam tulisan ini penulis menawarkan solusi menggunakan Sistem Informasi Geografis dan metode Simple Additive Weighting sebagai suatu sistem pendukung keputusan pada perusahaan Kalla Automotive. Dari hasil simulasi sistem diperoleh alternatif solusi untuk lokasi outlet di kota Bau Bau adalah di kecamatan Wolio dengan nilai alternatif 0,961923.

Scope & Topics 9 th International Conference on Computer Science and Information Technology (CoSIT 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:

the age of the ubiquity of the Internet has arrived. Globalization of the Planet is going to continue to develop the Information Society, the Internet is expanding, Internet Protocol version 6 is being developed, there was a strong influence on the Internet of things, smart appliances are already going mass market and a rapidly changing global IT trends. They serve to globalization process, but teleoperation and telepresence, monitor and control distance objects; ubiquitous positioning, Internet Governance, key trends and we think that is the right time to be prepared for future. We present a new concept and a new instrument – InternetScopy that allows observing remote objects by collecting big data and visualize the situation in multipurpose and multileveled government applications. Although practically useful and simple to implement, the proposed new concept enables to government heads to monitor a government situation national and international wide scales and multipurpose sectors, as customs, foreign diplomatic relations, healthcare, economy, ecology, education and other areas.

Forests are part of a complex landscape mosaic and play a crucial role for people living both in rural and urbanized spaces. Recent progresses in modelling and Decision Support System (DSS) applied to the forestry sector promise to improve public participative forest management and decision-making in planning and conservation issues. However, most DSS are not open-source systems, being in many cases software designed for site-specific applications in forest ecosystems. Furthermore, some of these systems often miss challenging the integration of other land uses within the landscape matrix, which is a key issue in modern forestry planning aiming at linking recent developments in open-source Spatial-DSS systems to sectorial forest knowledge. This paper aims at demonstrating that a new type of S-DSS, developed within the Life+ project SOILCONSWEB over an open-source Geospatial Cyber-Infrastructure (GCI) platform, can provide a strategic web-based operational tool for forest resources ma...

Good acquaintance with an organization’s business rules is an undeniable success factor in a decision-making process. In environmental studies, decisions are multidisciplinary, rule oriented and are very much related to spatiality. SPeCS (Spatial Decision Support Collaborative System) is a framework which intends to support the aspects of multi-criteria spatial analysis within a distributed GIS architecture. This work has the following objectives: i) to define spatial business rules, so common in environmental studies; ii) to emphasize the importance of having the appropriate resources and techniques for managing this spatial knowledge; iii) to present a proposal complementing knowledge management in SPeCS with the appropriate support for spatial business rules; iv) and to validate some of the ideas presented through an implemented prototype.

Current trends in Alberta require the involvement of multiple stakeholders and decision support tools in planning the placement of wind farms. While the use of decision support tools can assist stakeholders in making decisions, developing useful tools for a domain as complex as wind farm placement planning is challenging. In addition, few design requirements exist to ensure that decision support tools are specific to local needs, and that they have capabilities to support stakeholders in making informed decisions about placement locations. To this end, we conducted a study, using questionnaires and interviews, to: (1) identify the main issues that influence wind farm placement and land use decisions in Alberta; (2) identify stakeholders’ decision support needs for evaluating wind farm placement decisions, and how these needs can be incorporated in a decision support tool; (3) gain a deeper understanding of how stakeholders in Alberta currently interact with existing tools, and identify areas where design can improve usability; and (4) derive usability attributes that can inform the development of a decision support tool for wind farm placement planning in Alberta. Based on the study findings, we propose some design recommendations which highlight the relevance of a place-based decision support tool with visual and analytical attributes.