Multilevel Modeling of Geographic Information Systems Based on International Standards

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Even though different applications based on Geographic Information Systems (GIS) provide different features and functions, they all share a set of common concepts (e.g., spatial data types, operations, services), a common architecture, and a common set of technologies. Furthermore, common structures appear repeatedly in different GIS, although they have to be specialized in specific application domains. Multilevel modeling is an approach to model-driven engineering (MDE) in which the number of metamodel levels is not fixed. This approach aims at solving the limitations of a two-level metamodeling approach, which forces the designer to include all the metamodel elements at the same level. In this paper, we address the application of multilevel modeling to the domain of GIS, and we evaluate its potential benefits. Although we do not present a complete set of models, we present four representative scenarios supported by example models. One of them is based on the standards defined by ISO TC/211 and the Open Geospatial Consortium. The other three are based on the EU INSPIRE Directive (territory administration, spatial networks, and facility management). These scenarios show that multilevel modeling can provide more benefits to GIS modeling than a two-level metamodeling approach.Xunta de Galicia; IN852A 2018/14Xunta de Galicia; ED431G 2019/01This work has been partially funded by grants: MICIU/FEDER-UE, MAGIST: PID2019-105221RB-C41; MICIU/FEDER-UEBIZDEVOPSGLOBAL: RTI-2018-098309-B-C32, Xunta de Galicia/FEDER-UE, ConectaPeme, GEMA: IN852A 2018/14; MINECOAEI/FEDER-UE Datos 4.0: TIN2016-78011-C4-1-R; MINECOAEI/FEDER-UE Velocity: TIN2016-77158-C4-3-R; CITIC research center funded by XUNTA and EU through the European Regional Development Fund- Galicia 2014-2020 Program, grant ED431G 2019/01. Funding for open access charge: Universidade da Coruña/CISUG

PEMODELAN SISTEM INFORMASI GEOGRAFIS (SIG) PADA DISTRIBUSI PENYAKIT DEMAM BERDARAH DENGUE (DBD) DI KECAMATAN KARANGMALANG KABUPATEN SRAGEN

Abstract: Modeling Of Geographic Information System (GIS) In Distribution of Dengue Haemorrhagic Fever (DHF) In The District Karangmalang Sragen. This study aims to provide an overview of the spatial distribution of Dengue Hemorrhagic Fever (DHF), aware of any clustering of dengue cases and analyze the risk factors associated with the incidence of dengue disease in the district Karangmalang Sragen with modeling of Geographic Information Systems (GIS) with SpatialAnalysis. The results of this study indicate that the pattern of distribution of cases of Dengue Hemorrhagic Fever (DHF) in the district Karangmalang Sragen toward clustered (Clustering) and There is a relationship between the distribution of cases of Dengue Hemorrhagic Fever (DHF) with Population Density, Figures Status Free Larva (ABJ) and the percentage of large settlements in districts Karangmalang Sragen.Keywords : Geographic Information Systems (GIS), Dengue Hemorrhagic FeverAbstrak: Pemodelan Sistem Informasi Geografis (SIG) pada Distribusi Penyakit Demam Berdarah Dengue (DBD) di Kecamatan Karangmalang Kabupaten Sragen. Penelitian ini bertujuan untuk memberikan gambaran distribusi spasial penyakit Demam Berdarah Dengue (DBD), mengetahui adanya clustering pada kasus DBD dan menganalisis faktor-faktor resiko yang berhubungan dengan kejadian penyakit DBD di kecamatan Karangmalang kabupaten Sragen dengan pemodelan Sistem Informasi Geografis (SIG). Hasil penelitian ini menunjukkan bahwa Pola distribusi kasus Demam Berdarah Dengue (DBD) di kecamatan Karangmalang ke arah mengelompok (Clustering) dan Terdapat hubungan antara Distribusi kasus Demam Berdarah Dengue (DBD) dengan Kepadatan Penduduk, Status Angka Bebas Jentik (ABJ) dan prosentase luas permukiman di kecamatan Karangmalangjiwa.Kata kunci: Sistem Informasi Geografis (SIG), Demam Berdarah Dengue

Spatial Analysis on Tsunami Predictions in Pandeglang Regency

Pandeglang Regency is an area that has the potentiel to be hit by tsunamis. The plate subduction paths of Indo-Australia and Anak Krakatau Volcano make Pandeglang Regency a region with a high tsunami potential. One step that can be taken to overcome and minimize losses is to do spatial planning to protect it against potential tsunami damage. This research aimed to evaluate the spatial area of Pandeglang Regency based on the identification of potential tsunami hazards.  The concept of modelling the tsunami inundation height developed by Berryman and based on Head Regulation No.4 of 2012 of the Indonesian National Board for Disaster Management has been used to identify potential tsunami hazards. The modelling was carried out by calculating the potential distribution of tsunami wave heights in coastal areas.  Three scenarios were used to estimate the distribution. The results showed that the first scenario predicted a maximum tsunami height   of 7.5 meters above sea level with the furthest tsunami inundation reaching 1,700.12 meters. Second scenario predicted maximum height of 15 meters, with the furthest tsunami inundation reaching 3,384.62 meters. Meanwhile, the last scenario was able to predict a height of 20 meters and showed the furthest tsunami inundation reaching 5.155,11 meters. These results proved that in all scenarios, the widest inundation would occur in Panimbang Regency. This is due to the relatively small variations in roughness and slope of the surface. The same condition also occurs in the last two scenarios, in which Sumur District was the area most ffected. Therefore, the spatial plan of Pandeglang Regency needs to be evaluated and the function of residential area changed to reduce and prevent large losses

The Management of Geographic Information Flows in Crisis Situations

This paper studies the management of geographic information and knowledge flows for decision support in crisis situations. The authors compare and contrast a number of concepts that have been forwarded by academics as possible methodologies for the study of this area. The authors believe that they may have found an answer using system models combined with decision-making, information management and geographic information management models. Especially, the authors apply a system model about situation awareness. This model reflects to a state where a comprehensive mutual understanding and sharing of ideas between the decision-makers are provided. It supports the categorizing of geographic information and knowledge according to the user specific value and updating frequency. Currently a prototype of a decision support system based on the model is under development

Põllumassiivide identifitseerimissüsteemi kontseptuaalne mudel: geoinfo huvigruppi kontseptuaalse mudeli loomine

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Käesolevas doktoritöös käsitletakse Põllumassiivide identifitseerimissüsteemi (Land Parcel Identification System, LPIS) Kontseptuaalse Mudeli (LPIS Conceptual Model, LCM) loomist ja selle kasutamist ruumiandmete standardiseerimisel, kvaliteedi hindamisel ja koostoimimisel teiste valdkondade ruumiandmetega. Mudelis käsitletud ruumiandmeid kasutatakse põllumajandustoetuste haldamise ja kontrolli eesmärgil ELi Ühise Põllumajanduspoliitika (ÜPP) raames. ÜPP raames makstavate toetuste haldamiseks on igas EL liikmesriigis asutatud Ühtne haldus-ja kontrollisüsteem (Eestis Põllumajandusregistrite amet, PRIA), mille ruumiandmeid haldav komponent on põllumassiivide register ehk identifitseerimissüsteem. Nõue kaardistada ja registreerida toetuskõlbulik maa on viinud olukorrani, kus põllumajandussektoris on tekkinud suur hulk ruumiandmeid. Viimase aastakümne jooksul on kasvanud ÜPP-ga seotud geoinformaatika sektor Euroopas. ÜPP-ga seotud geoinfo huvigrupp (Spatial Data Interest Community) hõlmab nii andmete tootjaid, haldajaid ja kasutajaid, kui ka IT rakenduste arendajaid ning kaugseire andmete tarnijaid. Vajadus hinnata registrite kvaliteeti ja selle vastavust EL määrustele ning tagada koostalitlusvõime keskkonnaalaseid nõudeid toetavate ruumiandmete ja süsteemidega, kutsus esile LCM-i loomise. Töö eesmärgiks oli edendada kontseptuaalmodelleerimist põlluregistrite ruumiandmete kvaliteedi hindamisel ja teiste geoinfo (eelkõige keskkonnakaitse) valdkondadega koostalitlusvõime arendamisel. LCM väljatöötamise metodoloogia aluseks oli ISO19100 seeria rahvusvaheliste standardite metoodika, mida samuti rakendavad ja laiendavad INSPIRE direktiivi printsiibid ja millele keskendutakse uurimistöö teoreetilises osas. Mudeli peamiseks sisendiks said ÜPP-d reguleeritavates määrustes sätestatud kontseptsioonide põhjalik käsitlus ja olemasolevate töötavate süsteemide analüüs, mis põhineb LPIS küsitluste tulemustel (Milenov ja Kay, 2006; Zieliński ja Sagris, 2008 ja 2009) ja hõlmab erinevate liikmesriikide põlluregistreid. Väitekirjas on keskendutud ÜPP otsetoetuste ärimudeli analüüsile ehk ÜPP toetustesüsteemi põhikontseptsioonidele, tehtud kokkuvõtted ja järeldused 2006. ja 2008. aasta küsimustikust. Küsimustikust saadut info laiendati EL põlluregistrite kvaliteedi hindamise programmi raames. LCM esimese versiooni keskmes on kaks klassi: ReferenceParcel ehk põllumassiiv ja AgriculturalParcel ehk toetustaotluses deklareeritud põld. ReferenceParcel-i klassi ülesandeks on toetuskõlbliku põllumaa identifitseerimine, lokaliseerimine ja pindala määramine. ReferenceParcel täidab „konteineri“ rolli deklareeritavate maatükkide suhtes. Kuid käsitletud põllumassiiviklassi alamtüüpe ning analüüsitud erinevaid põllumajanduslikke maakatte klassifitseerimise ja kaardistamise lähenemisviise EL liikmesriikides. Töö teisel etapil on otsitud võimalusi kahe mudeli – LCM ja Maakatastri infosüsteemi mudeli (Land Administration Domain Model, LADM, ISO 19152) – lõimiseks. Kaks mudelit on omavahel integreeritud uue ruumilise klassi SubCadParsel abil – katastriüksuse sees eristuvad maakatte tüübi alamüksused. Käsitletakse ka mõlema mudeli semantiliselt sarnaseid haldusklasse ja tehakse kindlaks uued seosed kahe mudeliklassi vahel. Ära on toodud põhjalik analüüs, millistes reaalse elu tingimustes võiks toimida kahe mudeli integreerimine. LCM viimane versioon keskendub kahele aspektile: (i) nende klasside modelleerimisele, mis toetavad vastavust keskkonna, tervise ja loomade heaolu majandamisnõuetele ning mis toetavad maa heade põllumajandus- ja keskkonnatingimuste kontrolli; (ii) mudeli kasutamisele põlluregistrite loogilise õigsuse (ehk EL määruste nõuetele vastavuse) testimiseks. Selleks on välja töötatud ISO19105 standardil põhinev testide kogum (Abstract Tests Suite, ATS), mis võimaldab kaardistada olemasolevaid LPIS registreid vastavalt LCM skeemile. ATS töötati välja ja testiti koostöös mitmete EL liikmesriikidega ja selle metodoloogia on osa Euroopa komisjoni poolt kehtestatud LPIS kvaliteedi tagamise raamprogrammist alates 2010. aastast. LCM-i kasutati ka LPIS testimise portaali prototüübi loomisel, mis koondas enda alla OGC ühilduvaid veebiteenuseid. Nende eesmärgiks on võimaldada andmevahetust rahvuslike põlluregistrite ja auditeerijatega Euroopa komisjonist. Eelvalitud põllumassiivide geograafiliste kihtide temaatilist ja positsioonilist õigsust kontrolliti liikmesriikide ekspertide poolt kõrge resolutsiooniga kaugseire andmete taustal. Selleks et võimaldata auditeerijate juurdepääsu kvaliteedikontrolli tulemustele, loodi kolm prototüüp-veebiteenust, kus kasutati LCM-i originaalandmete transformeerimiseks. Edasised uuringud kontsentreeruvad erinevate Euroopa põllumajandussüsteemide kajastamisele põlluregistite andmetes ja nende andmete kasutamise võimalustele põllumajanduspoliitika keskkonnamõju hindamisel. LPIS/IACS põhikontseptsioonid vaadatakse uuesti läbi, nüüd juba mõjuhindamise ja indikaatorite väljatöötamise kontekstis. Teoreetilist arutlust illustreerib kõrge loodusväärtusega põllumajandusmaa (KLV) indikaatorite väljatöötamise näide Jõgevamaal – põlluregistrist saadud detailiderohked andmed lubavad arvutada nii maastiku meetrika kui ka põllumajandusintensiivsuse indikaatoreid, seejuures tüpiseerides põllumajandussüsteemide erinevaid aspekte. Seega, LCM toetab geograafiliste andmete harmoniseerimist ja koostalitusvõimet mitmel moel: (i) pakkudes valdkonna siseselt andmete ühiselt mõistetavat tehnilist lugemist, nii mudeli vastavusetesti (ATS) kui ka veebiteenuste kaudu transformeerimisel; (ii) võimaldades semantilise vastavuse leidmist ja andmete/süsteemide integreerimist erinevate geoinfo valdkondade vahel. Loodud ja arendatud esialgselt Euroopa komisjoni LPIS kvaliteedisüsteemi vajadusi silmas pidades, võimaldab LCM erinevate liikmesriikide põllumajandusregistrite andmete ühiselt mõistetavat lugemist ka teistes valdkondades. LCM on lisatud kasutusjuhtumina rahvusvahelise standardi ISO 19152 ’Land Administration Domain Model’ lisasse H ja INSPIRE DS2.8 Land Cover rakenduseeskirja lisasse B2.This dissertation presents the development of the Land Parcel Identification System (LPIS) Conceptual Model (LCM) for the administration and control of agricultural subsidies of the European Common Agricultural Policy (CAP). The subsidies which European farmers receive in the frame of the CAP are administered through the Integrated Administration and Control System (IACS) that are established and run by the EU member states. IACS includes a Land Parcel Identification System (LPIS) as its spatial component. The requirement to map and record land eligible for payments has led to the situation where the agricultural sector has acquired a large amount of geographic data; the geospatial community of data producers, custodians and users has grown during the last decades. The need to assess the quality and consistency of the LPIS towards the EU regulators as well as to ensure systems’ interoperability as it is required for compliance with environmental legislation, call for harmonisation efforts. In the view of this, an LPIS Conceptual Model (LCM) was developed. The objective of the study was to introduce the modeling framework of ISO 19100 series for advance of quality of geospatial data in the LPIS domain and of interoperability with other geospatial domains. The LCM was generated by means of both (i) methodological approaches of International Standards of ISO 19100 series, further extended by the INSPIRE principles, and (ii) reverse engineering of existing operational LPIS systems. The latter is based on the results of two LPIS surveys covering different national implementations. Business analysis of the relevant EU regulations and the LPIS surveys led to the first-cut LCM. Model’s core classes – reference and agricultural parcels – cover process of land registration for administration of agricultural subsidies, agri-environmental measures of rural development and environmental restriction. Agricultural and reference parcels of the model build the framework for recording land cover and land use. Further model refinement addressed the quality aspects of the geographical databases: the LCM became naturally a part of the LPIS Quality Assurance programme between the European Commission and EU countries. The LCM was used (i) for conformance assessment of national systems and (ii) for implementation of the LPIS Test Bed portal: set of OGC compliant Web services allowing for agricultural data transformation from national data schemas to the common model as well as transferring, checking and storing spatial and non-spatial observations from the quality inspection. The study case for interoperability with cadastral domain looked for possibilities of the collaboration of two models – the LCM and the Land Administration Domain Model (became ISO19152 LADM). Owner’s rights, restrictions and responsibilities arising from land ownership in the cadastral domain have many similarities, but also differences with agricultural practice. The collaboration model established via newly introduced spatial class, also the semantic similarity of administrative classes of both models were analysed in details. Further studies include a representation of different European agricultural systems in LPIS and potentials of using LPIS data in the environmental impact assessment of the agricultural policy. Different types of land parcel proposed by the thesis and ways of integration with data from environmental domain viewed in context of the development of agri-environmental indicators. Developed firstly for the needs of LPIS Quality Assurance Framework of the European Commission, the LCM also became a part of the International Standard ISO19152 – Land Administration Domain Model (Annex H: use case in agriculture) and INSPIRE DS2.8 Land Cover specification (Annex B2: use case in agriculture)

Towards High-Performance Big Data Processing Systems

The amount of generated and stored data has been growing rapidly, It is estimated that 2.5 quintillion bytes of data are generated every day, and 90% of the data in the world today has been created in the last two years. How to solve these big data issues has become a hot topic in both industry and academia. Due to the complex of big data platform, we stratify it into four layers: storage layer, resource management layer, computing layer, and methodology layer. This dissertation proposes brand-new approaches to address the performance of big data platforms like Hadoop and Spark on these four layers. We first present an improved HDFS design called SMARTH, which optimizes the storage layer. It utilizes asynchronous multi-pipeline data transfers instead of a single pipeline stop-and-wait mechanism. SMARTH records the actual transfer speed of data blocks and sends this information to the namenode along with periodic heartbeat messages. The namenode sorts datanodes according to their past performance and tracks this information continuously. When a client initiates an upload request, the namenode will send it a list of \u27\u27high performance\u27\u27 datanodes that it thinks will yield the highest throughput for the client. By choosing higher performance datanodes relative to each client and by taking advantage of the multi-pipeline design, our experiments show that SMARTH significantly improves the performance of data write operations compared to HDFS. Specifically, SMARTH is able to improve the throughput of data transfer by 27-245% in a heterogeneous virtual cluster on Amazon EC2. Secondly, we propose an optimized Hadoop extension called MRapid, which significantly speeds up the execution of short jobs on the resource management layer. It is completely backward compatible to Hadoop, and imposes negligible overhead. Our experiments on Microsoft Azure public cloud show that MRapid can improve performance by up to 88% compared to the original Hadoop. Thirdly, we introduce an efficient 3-level sampling performance model, called Hedgehog, and focus on the relationship between resource and performance. This design is a brand new white-box model for Spark, which is more complex and challenging than Hadoop. In our tool, we employ a Java bytecode manipulation and analysis framework called ASM to reduce the profiling overhead dramatically. Fourthly, on the computing layer, we optimize the current implementation of SGD in Spark\u27s MLlib by reusing data partition for multiple times within a single iteration to find better candidate weights in a more efficient way. Whether using multiple local iterations within each partition is dynamically decided by the 68-95-99.7 rule. We also design a variant of momentum algorithm to optimize step size in every iteration. This method uses a new adaptive rule that decreases the step size whenever neighboring gradients show differing directions of significance. Experiments show that our adaptive algorithm is more efficient and can be 7 times faster compared to the original MLlib\u27s SGD. At last, on the application layer, we present a scalable and distributed geographic information system, called Dart, based on Hadoop and HBase. Dart provides a hybrid table schema to store spatial data in HBase so that the Reduce process can be omitted for operations like calculating the mean center and the median center. It employs reasonable pre-splitting and hash techniques to avoid data imbalance and hot region problems. It also supports massive spatial data analysis like K-Nearest Neighbors (KNN) and Geometric Median Distribution. In our experiments, we evaluate the performance of Dart by processing 160 GB Twitter data on an Amazon EC2 cluster. The experimental results show that Dart is very scalable and efficient

Towards BIM/GIS interoperability: A theoretical framework and practical generation of spaces to support infrastructure Asset Management

The past ten years have seen the widespread adoption of Building Information Modelling (BIM) among both the Architectural, Engineering and Construction (AEC) and the Asset Management/ Facilities Management (AM/FM) communities. This has been driven by the use of digital information to support collaborative working and a vision for more efficient reuse of data. Within this context, spatial information is either held in a Geographic Information Systems (GIS) or as Computer-Aided Design (CAD) models in a Common Data Environment (CDE). However, these being heterogeneous systems, there are inevitable interoperability issues that result in poor integration. For this thesis, the interoperability challenges were investigated within a case study to ask: Can a better understanding of the conceptual and technical challenges to the integration of BIM and GIS provide improved support for the management of asset information in the context of a major infrastructure project? Within their respective fields, the terms BIM and GIS have acquired a range of accepted meanings, that do not align well with each other. A seven-level socio-technical framework is developed to harmonise concepts in spatial information systems. This framework is used to explore the interoperability gaps that must be resolved to enable design and construction information to be joined up with operational asset information. The Crossrail GIS and BIM systems were used to investigate some of the interoperability challenges that arise during the design, construction and operation of an infrastructure asset. One particular challenge concerns a missing link between AM-based information and CAD-based geometry which hinders engineering assets from being located within the geometric model and preventing geospatial analysis. A process is developed to link these CAD-based elements with AM-based assets using defined 3D spaces to locate assets. However, other interoperability challenges must first be overcome; firstly, the extraction, transformation and loading of geometry from CAD to GIS; secondly, the creation of an explicit representation of each 3D space from the implicit enclosing geometry. This thesis develops an implementation of the watershed transform algorithm to use real-world Crossrail geometry to generate voxelated interior spaces that can then be converted into a B-Rep mesh for use in 3D GIS. The issues faced at the technical level in this case study provide insight into the differences that must also be addressed at the conceptual level. With this in mind, this thesis develops a Spatial Information System Framework to classify the nature of differences between BIM, GIS and other spatial information systems

Proceedings, MSVSCC 2015

The Virginia Modeling, Analysis and Simulation Center (VMASC) of Old Dominion University hosted the 2015 Modeling, Simulation, & Visualization Student capstone Conference on April 16th. The Capstone Conference features students in Modeling and Simulation, undergraduates and graduate degree programs, and fields from many colleges and/or universities. Students present their research to an audience of fellow students, faculty, judges, and other distinguished guests. For the students, these presentations afford them the opportunity to impart their innovative research to members of the M&S community from academic, industry, and government backgrounds. Also participating in the conference are faculty and judges who have volunteered their time to impart direct support to their students’ research, facilitate the various conference tracks, serve as judges for each of the tracks, and provide overall assistance to this conference. 2015 marks the ninth year of the VMASC Capstone Conference for Modeling, Simulation and Visualization. This year our conference attracted a number of fine student written papers and presentations, resulting in a total of 51 research works that were presented. This year’s conference had record attendance thanks to the support from the various different departments at Old Dominion University, other local Universities, and the United States Military Academy, at West Point. We greatly appreciated all of the work and energy that has gone into this year’s conference, it truly was a highly collaborative effort that has resulted in a very successful symposium for the M&S community and all of those involved. Below you will find a brief summary of the best papers and best presentations with some simple statistics of the overall conference contribution. Followed by that is a table of contents that breaks down by conference track category with a copy of each included body of work. Thank you again for your time and your contribution as this conference is designed to continuously evolve and adapt to better suit the authors and M&S supporters. Dr.Yuzhong Shen Graduate Program Director, MSVE Capstone Conference Chair John ShullGraduate Student, MSVE Capstone Conference Student Chai