USING PARTICIPATORY APPROACH TO IMPROVE AVAILABILITY OF SPATIAL DATA FOR LOCAL GOVERNMENT

Nowadays, the availability of authoritative geospatial features of various data themes is becoming wider on global, regional and national levels. The reason is existence of legislative frameworks for public sector information and related spatial data infrastructure implementations, emergence of support for initiatives as open data, big data ensuring that online geospatial information are made available to digital single market, entrepreneurs and public bodies on both national and local level. However, the availability of authoritative reference spatial data linking the geographic representation of the properties and their owners are still missing in an appropriate quantity and quality level, even though this data represent fundamental input for local governments regarding the register of buildings used for property tax calculations, identification of illegal buildings, etc. We propose a methodology to improve this situation by applying the principles of participatory GIS and VGI used to collect observations, update authoritative datasets and verify the newly developed datasets of areas of buildings used to calculate property tax rates issued to their owners. The case study was performed within the district of the City of Požega in eastern Croatia in the summer 2015 and resulted in a total number of 16072 updated and newly identified objects made available online for quality verification by citizens using open source geospatial technologies.

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Factors influencing integrated information management: Spatial data infrastructure in Pakistan

Information Development ◽

10.1177/02666669211048483 ◽

2021 ◽

pp. 026666692110484

Author(s):

Asmat Ali ◽

Muhammad Imran ◽

Munazza Jabeen ◽

Zahir Ali ◽

Syed Amer Mahmood

Keyword(s):

Information Management ◽

Spatial Data ◽

Structural Equation ◽

Explanatory Power ◽

Primary Data ◽

Equation Modeling ◽

Geospatial Information ◽

Data Infrastructure ◽

Significance Level ◽

Retrieval Processes

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond.

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From Surveying to Geomatics

Landscape & Environment ◽

10.21120/le/10/3-4/8 ◽

2016 ◽

Vol 10 (3-4) ◽

pp. 153-160 ◽

Cited By ~ 1

Author(s):

Besim Ajvazi ◽

Fisnik Loshi ◽

Béla Márkus

Keyword(s):

Information And Communication Technologies ◽

Spatial Data ◽

Professional Education ◽

Spatial Databases ◽

Unmanned Aerial Systems ◽

Geospatial Information ◽

Automatic Data ◽

Data Infrastructure ◽

Building Information ◽

Concept Building

In the land surveying profession fast changes have been taking place in the last fifty years. Technological changes are generated by the Information and Communication Technologies; the analogue – digital trends; the automatic data acquisition methods replace manual ones; instead of two-dimensional base maps we use dynamic spatial databases more and more integrated into a global data infrastructure. However, these changes cause impacts also on scientific level. The traditional top-down approach substituted by bottom-up methodologies; in many cases the point-by-point measurement is changed by 3D laserscanning or Unmanned Aerial Systems, which produces huge amount of data, but it needs new algorithms for information extraction; instead of a simple data provision land surveyors support complex spatial decisions. The paper is dealing with some aspects of these changes. In the first chapter the authors would like to highlight the “data-information-knowledge” relations and the importance of changes in professional education. The second chapter gives an example of the benefits of a Global Spatial Data Infrastructure in spatial decision support. Finally we introduce a new concept (Building Information Modelling) in modelling the real world. However, until now BIM is used in building construction industry, it can can be a paradigm shift in geospatial information management in general.

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CloudGanga

Geospatial Intelligence ◽

10.4018/978-1-5225-8054-6.ch013 ◽

2019 ◽

pp. 278-297 ◽

Cited By ~ 2

Author(s):

Rabindra K. Barik

Keyword(s):

Cloud Computing ◽

Spatial Data ◽

Learning Approaches ◽

Geospatial Information ◽

Ganga Basin ◽

Hydro Power ◽

Data Infrastructure ◽

Irrigation Project ◽

Well Location ◽

River Ganga

The present research paper proposes and develops a Cloud computing based Spatial Data Infrastructure (SDI) Model named as CloudGanga for sharing, analysis and processing of geospatial data particularly in River Ganga Basin management in India. The main purpose of the CloudGanga is to integrate all the geospatial information such as dam location, well location, irrigation project, hydro power project, canal network and central Water Commission gauge stations locations related to River Ganga. CloudGanga can help the decision maker/ planner or common users to get enough information for their further research and studies. The open source software (Quantum GIS) has been used for the development of geospatial database. QGIS Plugin has been linked with Quantum GIS for invoking cloud computing environment. It has also discussed about the various overlay analysis in CloudGanga environment. In the present research, machine learning approaches are also used in a R tool for well locations which are associated with the basin of River Ganga.

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Geospatial IoT—The Need for Event-Driven Architectures in Contemporary Spatial Data Infrastructures

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7100385 ◽

2018 ◽

Vol 7 (10) ◽

pp. 385 ◽

Cited By ~ 4

Author(s):

Matthes Rieke ◽

Lorenzo Bigagli ◽

Stefan Herle ◽

Simon Jirka ◽

Alexander Kotsev ◽

...

Keyword(s):

Real Time ◽

Spatial Data ◽

Geospatial Information ◽

Data Infrastructure ◽

Event Driven ◽

Data Infrastructures ◽

Spatial Data Infrastructures ◽

Time Critical ◽

Real Time Information ◽

Time Information

The nature of contemporary spatial data infrastructures lies in the provision of geospatial information in an on-demand fashion. Although recent applications identified the need to react to real-time information in a time-critical way, research efforts in the field of geospatial Internet of Things in particular have identified substantial gaps in this context, ranging from a lack of standardisation for event-based architectures to the meaningful handling of real-time information as “events”. This manuscript presents work in the field of event-driven architectures as part of spatial data infrastructures with a particular focus on sensor networks and the devices capturing in-situ measurements. The current landscape of spatial data infrastructures is outlined and used as the basis for identifying existing gaps that retain certain geospatial applications from using real-time information. We present a selection of approaches—developed in different research projects—to overcome these gaps. Being designed for specific application domains, these approaches share commonalities as well as orthogonal solutions and can build the foundation of an overall event-driven spatial data infrastructure.

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Identifying Users’ Requirements for Emergency Mapping Team Operations in the Dominican Republic

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9030165 ◽

2020 ◽

Vol 9 (3) ◽

pp. 165

Author(s):

Gregorio Rosario Michel ◽

Santiago Muñoz Tapia ◽

Fernando Manzano Aybar ◽

Vladimir Guzmán Javier ◽

Joep Crompvoets

Keyword(s):

Dominican Republic ◽

Spatial Data ◽

Online Survey ◽

Caribbean Region ◽

Geospatial Information ◽

Data Infrastructure ◽

Future Studies ◽

Wide Range ◽

The Caribbean ◽

The Impact

In recent years, a growing number of stakeholders have been taking part in the generation and delivery of geospatial information and services to reduce the impact of severe natural disasters on the communities. This is mainly due to a huge demand for accurate, current and relevant knowledge about the impacted areas for a wide range of applications in risk-informed decision makings. The aim of this paper is to identify users’ requirements for emergency mapping team (EMT) operations in the Dominican Republic (DR). An online survey was applied to collect data from key users involved in the Inter-Institutional Geospatial Information Team in DR. Our findings suggest a set of users’ requirements for EMT operations: (1) standardization; (2) establishing and maintaining a spatial data infrastructure; (3) partnership; (4) effective communication among stakeholders; and (5) capacity building. A better understanding of the users’ requirements and the associated information workflows will lead to a superior level of readiness for EMT operations in DR. This knowledge will support future studies/practices at the local and national levels in the Caribbean region, which share similar challenges in terms of natural hazards and development issues.

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Evaluasi Kesiapan Implementasi Infrastruktur Data Spasial untuk Manajemen Penanggulangan Bencana

REKA GEOMATIKA ◽

10.26760/jrg.v2017i1.1466 ◽

2018 ◽

Vol 2017 (1) ◽

Author(s):

Herlina ◽

Sumarno ◽

Indrianawati

Keyword(s):

Decision Making ◽

Disaster Management ◽

Spatial Data ◽

Data Access ◽

Spatial Data Infrastructure ◽

Data Availability ◽

Geospatial Information ◽

Data Infrastructure ◽

Ease Of Access ◽

Interview Questionnaire

ABSTRAK Akses data spasial yang cepat dan akurat mempunyai peranan yang penting dalam pengambilan keputusan untuk manajemen penanggulangan bencana. Infrastruktur Data Spasial (IDS) merupakan suatu cara untuk memudahkan pengguna untuk mengakses data spasial secara konsisten, mudah, dan aman. Dengan kata lain, IDS dapat meningkatkan ketersediaan data, kemudahan dalam akses, dan implementasi data spasial dalam pengambilan keputusan. Dalam hal manajemen penanggulangan bencana, BPBD dan stakeholder kebencanaan Kabupaten Bandung belum mengimplementasikan IDS kebencanaan. Tujuan penelitian ini adalah menentukan model IDS kebencanaan dan mengevaluasi kesiapan implementasi dalam manajemen penanggulangan bencana di Kabupaten Bandung. Metode yang digunakan dalam penelitian adalah penentuan model IDS kebencanaan yang mengacu pada model IDS yang dirumuskan oleh Rajabifard kemudian didetailkan dengan indikator penilaian IDS yang dikeluarkan Badan Informasi Geospasial tahun 2016. Pengambilan data dilakukan pada 18 stakeholder kebencanaan Kabupaten Bandung dengan wawancara, kuesioner, dan penilaian melalui website. Hasil evaluasi dari kesiapan implementasi IDS kebencanaan Kabupaten Bandung adalah 45,8%. Kata kunci: Infrastruktur Data Spasial, Manajemen Penanggulangan Bencana, Kabupaten Bandung ABSTRACT Fast and accurate spatial data access has an important role in decision making for disaster management. Spatial Data Infrastructure (SDI) is a way to facilitate the users to access spatial data consistently, easily, and safety. In the case, SDI can improve data availability, ease of access and implementation of spatial data for decision making. In disaster management, BPBD and disaster stakeholders in Bandung District have not implemented SDI of disaster. The objective of this study is to determine the SDI model of disaster and evaluate the readiness of implementation in disaster management in Bandung District. The method used in this study is determining SDI model of disaster, referred to IDS model which is formulated by Rajabifard, and then the SDI model of disaster is detailed by SDI assessment indicator issued by Geospatial Information Agency (2016). The data collection has been taken on 18 disaster stakeholders in Bandung District with interview, questionnaire, and assessment through the website. The evaluation result of the readiness of implementation the SDI of disaster in Bandung District is 45.8%. Keywords: Spatial Data Infrastructure, Disaster Management, Bandung District

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GeoSpatial IoT - the Need for an Event-Driven Spatial Data Infrastructure

10.20944/preprints201808.0132.v1 ◽

2018 ◽

Author(s):

Matthes Rieke ◽

Lorenzo Bigagli ◽

Stefan Herle ◽

Simon Jirka ◽

Alexander Kotsev ◽

...

Keyword(s):

Real Time ◽

Spatial Data ◽

Spatial Data Infrastructure ◽

Geospatial Information ◽

Data Infrastructure ◽

Event Driven ◽

Data Infrastructures ◽

Spatial Data Infrastructures ◽

Real Time Information ◽

Time Information

The nature of contemporary Spatial Data Infrastructures lies in the provision of geospatial information in an on-demand fashion. Though recent applications identified the need to react to real-time information in a time-critical way. In particular, research efforts in the field of geospatial Internet of Things have identified substantial gaps in this context, ranging from a lack of standardization for event-based architectures to the meaningful handling of real-time information as ''events''. This manuscript presents work in the field of Event-driven Spatial Data Infrastructures with a particular focus on sensor networks and the devices capturing in-situ measurements. The current landscape of Spatial Data Infrastructures is outlined and used as the basis for identifying existing gaps that retain certain geospatial applications from using real-time information. We present a selection of approaches - developed in different research projects - to overcome these gaps. Being designed for specific application domains, these approaches share commonalities as well as orthogonal solutions and can build the foundation of an overall Event-driven Spatial Data Infrastructure.

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HELP - An Early warning dashboard System, built for the prevention, mitigation and assessment of disasters, with a flexible approach using open data and open source technologies

10.7287/peerj.preprints.2229v1 ◽

2016 ◽

Cited By ~ 1

Author(s):

Lorenzo Amato ◽

Dimitri Dello Buono ◽

Francesco Izzi ◽

Giuseppe La Scaleia ◽

Donato Maio

Keyword(s):

Early Warning ◽

Spatial Data ◽

Emergency Preparedness ◽

Risk Mitigation ◽

Open Data ◽

National Research Council ◽

Civil Defense ◽

Main Role ◽

Cooperation Agreement ◽

Data Infrastructure

H.E.L.P is an early warning dashboard system built for the prevention, mitigation and assessment of disasters, be they earthquakes, fires, or meteorological systems. It was built to be easily manageable, customizable and accessible to all users, to facilitate humanitarian and governmental response. In its essence it is an emergency preparedness web tool, which can be used for decision making for a better level of mitigation and response on any level.Risks or disasters are not events in our control, rather, they are situations to which we can better manage with a framework based on preparedness. The earlier and more precise the monitoring of hazards allow for faster response to manage and mitigate a disaster’s impact on a society, economy and environment.This is exactly what HELP offers, it plays a main role in the cycle of early warning and risk (Preparedness, Risk, Mitigation, and Resilience). It provides information in real time on events and hazards, allowing for the possibility to analyze the situation and find a solution whose outcome protects the most lives and has the least economic impact. As a tool it also provides the opportunity to respond to a hazard with resilience in mind, this means that not only does HELP prepare for and mitigate events, it can also be used to implement better organizational methods for future events, thus, minimizing overall risk. Providing people with the means to better be able to take care of themselves, lessening the effects of future hazards each and every time. HELP is a tool in a framework which was created to support governments in their efforts to protect their people, building their response efficiency and resilience. HELP (with the name of E.W.A.R.E. Early Warning and Awareness of Risks and Emergencies) was born as WFP (The World Food Program) and IMAA-CNR (Institute of Methodologies for Environmental Analysis of the National Research Council of Italy) entered into a Cooperation Agreement concerning the development of a Geo-Spatial Data Infrastructure System for the Palestinian Civil Defense with the aim of building an enhanced preparedness capacity in Palestine.HELP has a simple and flexible but very effective logic to perform the early warning: Watch to open data sources on risk themes (NASA satellite data, Weather Forecast, world wide seismic networks, etc); Apply (programmable) “intelligence” to detect critical situations, exceeding of thresholds, population potentially involved by events, etc; Highlight critical elements on the map; Send alerts to emergency managers.

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HELP - An Early warning dashboard System, built for the prevention, mitigation and assessment of disasters, with a flexible approach using open data and open source technologies

10.7287/peerj.preprints.2229v2 ◽

2016 ◽

Cited By ~ 1

Author(s):

Lorenzo Amato ◽

Dimitri Dello Buono ◽

Francesco Izzi ◽

Giuseppe La Scaleia ◽

Donato Maio

Keyword(s):

Early Warning ◽

Spatial Data ◽

Emergency Preparedness ◽

Risk Mitigation ◽

Open Data ◽

National Research Council ◽

Civil Defense ◽

Main Role ◽

Cooperation Agreement ◽

Data Infrastructure

H.E.L.P is an early warning dashboard system built for the prevention, mitigation and assessment of disasters, be they earthquakes, fires, or meteorological systems. It was built to be easily manageable, customizable and accessible to all users, to facilitate humanitarian and governmental response. In its essence it is an emergency preparedness web tool, which can be used for decision making for a better level of mitigation and response on any level.Risks or disasters are not events in our control, rather, they are situations to which we can better manage with a framework based on preparedness. The earlier and more precise the monitoring of hazards allow for faster response to manage and mitigate a disaster’s impact on a society, economy and environment.This is exactly what HELP offers, it plays a main role in the cycle of early warning and risk (Preparedness, Risk, Mitigation, and Resilience). It provides information in real time on events and hazards, allowing for the possibility to analyze the situation and find a solution whose outcome protects the most lives and has the least economic impact. As a tool it also provides the opportunity to respond to a hazard with resilience in mind, this means that not only does HELP prepare for and mitigate events, it can also be used to implement better organizational methods for future events, thus, minimizing overall risk. Providing people with the means to better be able to take care of themselves, lessening the effects of future hazards each and every time. HELP is a tool in a framework which was created to support governments in their efforts to protect their people, building their response efficiency and resilience. HELP (with the name of E.W.A.R.E. Early Warning and Awareness of Risks and Emergencies) was born as WFP (The World Food Program) and IMAA-CNR (Institute of Methodologies for Environmental Analysis of the National Research Council of Italy) entered into a Cooperation Agreement concerning the development of a Geo-Spatial Data Infrastructure System for the Palestinian Civil Defense with the aim of building an enhanced preparedness capacity in Palestine.HELP has a simple and flexible but very effective logic to perform the early warning: Watch to open data sources on risk themes (NASA satellite data, Weather Forecast, world wide seismic networks, etc); Apply (programmable) “intelligence” to detect critical situations, exceeding of thresholds, population potentially involved by events, etc; Highlight critical elements on the map; Send alerts to emergency managers.

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