Assessing spatial information access, use and sharing for catchment management in Australia

Spatial data plays an important role in many social, environmental, economic and political decisions and is increasingly acknowledged as a national resource essential for sustainable development. One of the potential areas where spatial data can make a positive impact is for improved decision making to support catchment management. Reliable spatial data infrastructure (SDI) is needed to record the environmental, social and economic dimensions of catchment management. By building an appropriate SDI, disparate spatial data can be accessed and utilised to facilitate the exchange and sharing of spatial data between stakeholders across catchment communities. The aim of this paper is to identify the factors/variables contributing to spatial information access, sharing and use across catchment management areas and evaluate the current status of spatial information access, sharing and use among Australian states from a catchment management authority perspective. A survey method was used to collect primary data from 56 regional natural resource management (NRM) bodies responsible for catchment management in Australia. Descriptive statistics method was used to show the similarities and differences among Australian states. The key factors which influence sharing and access to spatial information are also explored. We found there is significant for spatial information access, use and sharing to contribute to SDI development

Smartphone-based volunteered geographic information (VGI) for slum mapping in Pokhara City of Nepal

Informal settlements in urban areas are increasing rapidly throughout the world and regularisation of these settlements is being one of the challenging issues. Various study results have shown that conventional cadastral based information system approach and government managed institutional arrangements do not appropriately address land management issues of slum settlements. The aim of this study is to explore application of smartphone based Volunteered Geographic Information (VGI) and open spatial tools for slum mapping in developing countries such as in Nepal. A case of Pokhara Metropolitan city has been considered to explore the potential of utilization of smartphone based VGI and open spatial tools for slum mapping. Attribute and spatial data were collected using Smartphones and community-driven approach. Spatial and attribute data collected from 229 respondents of household’s surveys are integrated, analysed and interpreted and presented in this paper. Open Street Map (OSM) platforms and QGIS open source software have been used for slum mapping. These maps could play an important role in providing spatial information to the local government and planning authority in Nepal. This research paper concludes that smartphone based VGI and open portals such OSM have great potential to contribute to develop slum database and in providing information to plan various strategies, which aims at understanding, regularisation and upgrading slums

Facilitating sustainable catchment management through spatial data infrastructure design and development

This research paper discusses the importance of spatial data and Spatial Data Infrastructure (SDI) for catchment management. It reviews four SDI theories including hierarchical spatial theory, diffusion theory, evolution theory and principal-agent (P-A) theory and discusses their characteristics and potential utilisation for catchment management. As catchment management issues are characterised by multi-level stakeholder participation in SDI implementation, the theory of hierarchy and the P-A theory may assist in exploring in greater depth the context of building SDI at the catchment level. Based upon existing SDI theory, it explores a conceptual framework and its implications for more effective development of catchment-based SDI. The framework which is based upon hierarchical theory, investigates the communitygovernment interaction between various catchment and administrative/political levels for developing SDI. Such a framework is complex and potentially has many levels. Additionally, the cross-jurisdictional linkages required to implement this framework within the existing administrative/political SDI framework also need to be carefully examined. The framework is explored through a case study of the Murray-Darling Basin in Australia, one of the world’s largest catchments. The challenges for developing an SDI which effectively supports the decision making within and across this catchment will be discussed and the potential strengths and weakness of the proposed framework identified in the context of this case study

Combining terrestrial scanned datasets with UAV point clouds for mining operations

Surveyors of open cut mining operations employ multiple data acquisition techniques such as the use of Unmanned Aerial Vehicles (UAV), Terrestrial Laser Scanning (TLS) and GNSS positioning for creating 3D surface models. Surveyors, mine planners and geologists are increasingly combining point cloud datasets to achieve more detailed surface models for the use of material reconciliation and volume calculations. Terrestrial Laser Scanning and UAV photogrammetry have enabled large, accurate and time effective data collection and increased computing capacity enables geospatial professionals to create 3D virtual surfaces, through merging UAV point clouds and TLS data combing with GNSS positioning. This research paper investigates the effects of combining data sets for creating 3D surface models from independent spatial data collection methods such as UAV, TLS and GNSS and assess their accuracy for the purpose of volume calculations in mining operation. 3D surface models provide important information for mining operations, planning of resources, material volumes calculation and financial calculations. A case study of two rehabilitation mine sites in Northern Victoria, Australia was selected for this study. Field data were collected using Terrestrial Laser Scanner and UAV. After each dataset was processed and filtered, the data were merged to create surface models. The accuracy of the combined model was assessed comparing height (Z) values using a fishnet point grid of the surfaces. Volumes between surfaces were calculated, and a cost applied to the results based on the current bulk cubic meter (BCM) haulage rates. The outputs from this study will provide scientific contributions to civil and mining industries where the computation of stockpile values is required

Application of mixed methods research in the onshore oil and gas drilling environment

There is significant variance in safety related behaviours between co-workers in a multinational oil and gas drilling operations functioning within South East Asia. Manifestations of this issue within this process driven high risk workplace included extensive variation in safe work performance stemming from individual and collective preparedness to engage in risk taking (Russo 2015). Understanding the identified phenomenon involved the application of a sequential exploratory mixed method study incorporating both a qualitative element in the form of a semi-structured interview, and a quantitative element involving a widely distributed survey within the broader onshore oil and gas industry. Analysis of variances in risk tolerance achieved through the conduct of both methods, permitted an in-depth exploration of antecedents, variables and factors and their manifestation in desirable or undesirable workplace behaviours. Because this research is concerned with longitudinal influences that on safe work performance within onshore oil and gas drilling operations, it is principally concerned with factors involving human behaviour. A multi-faceted data collection and analysis approach was supported by the selection of a pragmatic constructivism paradigm. Mixed methods are useful for practical minded researchers investigating the experience of a population in order to comprehend the situational realities within a professional environment. A sequential exploratory mixed methods research methodology was found to be appropriate in all of these circumstances

Building spatial data infrastructure to support sustainable catchment management

[Abstract]: Catchment management is characterised by multiple stakeholders and multiple goals which cut across traditional as well as administrative boundaries. It requires an integrated management approach as different institutions and individuals work together towards sustainable catchment outcomes. Spatial data plays an important role in formulating many catchment decisions. An increasingly problematic issue for catchment decisions is the availability and access of spatial data. Although the spatial data may be available, they may not be useful due to different standards, content or scale. The importance of spatial data to solving multiple issues concerning catchment management creates a growing need to organise data across disciplines and organisations through the development of Spatial Data Infrastructures (SDI). Due to the increasing development of land and natural resources, the management of rights, restrictions and responsibilities between people and land is becoming an important issue under the catchment management domain. This paper discusses SDI and its importance to catchment management. The role of catchment management authorities is explored and where these groups fit within the SDI development. A case study in Banepa Municipality, Nepal is examined to understand how spatial data infrastructure can assist in catchment decision making and management

Spatial data infrastructure for pro-poor land management

Various organisations are working to improve the living conditions of informal settlement and move them into the formal system. UN-HABITAT is one of the organisations working for the Habitat Agenda and has launched a pro-poor land management concept to improve the lives of slum dwellers through a flexible approach. City authorities generally consider slum or informal settlement as illegal. There is a general lack of reliable information necessary for planning and policy formulation required for upgrading and regularisation of these areas. Spatial data infrastructure (SDI) is critical to planning and decision making for pro-poor land management. However, the conventional spatial data infrastructure (SDI) concept is inadequate for informal settlement upgrading and regularisation. Therefore it is important to explore an appropriate SDI to accommodate new forms of legal evidence, utilisation of new technologies and open spatial information services. The aim of this paper is to explore a SDI model for pro-poor land management in developing countries. In this context, a case study methodology has been adopted. Two cities Kathmandu Valley, Nepal and Allahabad, India are selected for the study. In both of the cities, the informal settlers live without tenure rights, in very poor conditions, and mostly occupy public land. A model of spatial data infrastructure for pro-poor land management has been suggested and its characteristics are described

Spatial information sharing for catchment management in Australia

Spatial information plays an important role in many social, environmental, economic and political decisions and is increasingly acknowledged as a national resource essential for wider societal benefits. Natural Resource Management (NRM) is one area where spatial information can be used for improved planning and decision-making processes. Traditionally, state government organisations and mapping agencies have been the custodians of spatial information necessary for catchment management. Recent developments in Information Communication Technology (ICT) tools and spatial technology have provided community groups and grass-root citizens with no prior experience in spatial technology with a new opportunity to collect and manage spatial information. With these opportunities, regional NRM bodies in Australia are collecting a significant amount of property and catchment scale spatial information. The access and sharing of spatial information between state government agencies and regional NRM bodies is therefore emerging as an important issue for sub-national spatial data infrastructure (SDI) development. The aim of this research is to identify key factors which influence spatial information sharing between state government organisations and regional NRM bodies/catchment management authorities within Australia and to formulate strategies to facilitate spatial information sharing and hence support SDI development. The hypothesis is that the spatial information sharing in natural resource management needs to be improved and that a networked based spatial data infrastructure model may be an appropriate approach. This research explored the theoretical foundation for SDI development and utilised social network theory to explore spatial information sharing arrangements between regional NRM bodies and state government organisations. A mixed method research approach was utilised where a survey and the case study data were collected and analysed sequentially (i e in two phases). The findings from the national survey of NRM bodies and the case study were integrated and interpreted to identify the key factors influencing spatial information sharing and catchment SDI development in Australia. A national survey of regional NRM bodies investigated the spatial information access, use and sharing arrangements between regional NRM bodies and state government organisations. The results of the survey indicate that the spatial data access policy of state government organisations impacts on spatial information sharing across NRM bodies. The regional NRM bodies have a strong spatial capacity and are emerging as key players in spatial data infrastructure development in the natural resource management sector. An ongoing issue is the difficulty to locate which organisation holds each type of spatial data and accessing these datasets. Data sharing and spatial information management is a key area of collaboration and is based on the partnerships with state government organisations or community organisations. An emerging area for collaboration in the NRM sector is knowledge sharing. The case study explored the effectiveness of the Knowledge and Information Network (KIN) project in promoting spatial information sharing arrangements between regional NRM bodies and state government organisations. It identified the role of intermediary organisations and professionals such as the Regional Groups Collective (RGC) and knowledge coordinators as being critical to improving the communication and spatial information sharing across catchments. Using the mixed method design framework, the key factors which influence spatial information sharing between state government organisations and regional NRM bodies/catchment management authorities were classified into six major classes as organisational, economic, policy, legal, cultural and technical. Major strategies were formulated and it is suggested that the adoption and implementation of these strategies can facilitate spatial information sharing and hence SDI development across the natural resource management sector

Spatially enablement of NRM communities through spatial knowledge and information network development

A spatially enabled society (SES) is an emerging concept to make spatial information accessible and available for the benefit of society. It is a concept where location, place and other spatial information are available to government, community and citizens. This is an important extension to the generational development and progression of Spatial Data Infrastructure (SDI) as it seeks to contribute to wider societal benefits and sustainable development objectives. This research paper investigates the social dimension of SDI and the theoretical foundation for spatially enablement of catchment communities. Two social science theories, namely, actor network theory (ANT) and social network theory are utilized to better understand the relationships in spatial information sharing and knowledge sharing across catchments. A network perspective of SDI was explored through a case study of the Queensland Knowledge and Information Network (KIN) project. Spatial information sharing processes among regional Natural Resource Management (NRM) bodies were analyzed using an object oriented modelling technique to assess the impact on catchment management outcomes. The relationships among the knowledge network stakeholders and the influence of these relationships to spatial information and knowledge sharing was analyzed using social network analysis. The findings from this study suggest that a network perspective of SDI assists in understanding the spatial information management issues of catchment management and the broader goal of spatially enablement of society