A systems perspective on national prioritisation of sustainable development goals:Insights from Australia

Achieving the Sustainable Development Goals(SDGs)requires effective national initiatives and resource allo-cation.Yet,the simultaneous attainment of all goals is hindered by constraints such as limited budgets and resources,varied national priorities,and the intricate nature of the goals.As we approach 2030 and beyond,an urgent need for an effective,data-driven prioritisation system exists to optimise what can be accomplished.A considerable knowledge gap persists in identifying the priority areas that demand concentrated attention and how their improvement would propel overall sustainability goals.To bridge this gap,our study presents a priori-tisation approach that identifies significant SDG indicators based on urgency and impact,utilising Benchmarking,Bivariate,and Network analysis.Furthermore,we introduce an innovative Impact Index(IMIN)to assess an indi-cator’s extensive effect on the SDG network.This system carries significant international relevance by establishing a robust framework to identify key,potent,and interconnected indicators.It supports decision-makers worldwide in comprehending their nation’s SDG performance and promotes efficient resource allocation.In the specific con-text of Australia,our analysis spotlights several impactful,yet underperforming SDG indicators.These include the protection of Freshwater,Terrestrial,and Mountain Key Biodiversity Areas(KBAs),the share of renewable energy and energy intensity level of primary energy,targeted research and development,gender equality in national parliaments,and carbon-efficient manufacturing,amongst others.

Identifying Achilles-heel roads in real-sized networks

Ensuring a minimum operational level of road networks in the presence of unexpected incidents is becoming a hot subject in academic circles as well as industry. To this end, it is important to understand the degree to which each single element of the network contributes to the operation and performance of a network. In other words, a road can become an ＂Achilles-heel＂ for the entire network if it is closed due to a simple incident. Such insight of the detrimental loss of the closure of the roads would help us to be more vigilant and prepared. In this study, we develop an index dubbed as Achilles-heel index to quantify detrimental loss of the closure of the respective roads. More precisely, the Achilles-heel index indicates how many drivers are affected by the closure of the respective roads （the number of affected drivers is also called travel demand coverage）. To this end,roads with maximum travel demand coverage are sorted as the most critical ones, for which a method known as ＂link analysis＂--is adopted. In an iterative process, first, a road with highest traffic volume is first labeled as ＂target link,＂ and second, a portion of travel demand which is captured by the target link is excluded from travel demand. For the next iteration, the trimmed travel demand is then assigned to the network where all links including the target links run on the initial travel times. The process carries on until all links are labeled. The proposed methodology is applied to a large- sized network of Winnipeg, Canada. The results shed light on also bottleneck points of the network which may warrant provision of additional capacity or parallel roads.

Managing underground legal boundaries in 3D-extending the CityGML standard

Legal boundaries are used for delineating the spatial extent of ownership property’s spaces.In underground environments,these boundaries are defined by referencing physical objects,surveying measurements,or projections.However,there is a gap in connecting and managing these boundaries and underground legal spaces,due to a lack of data model.A 3D data model supporting underground land administration(ULA)should define and model these boundaries and the relationships between them and underground ownership spaces.Prominent 3D data models can be enriched to model underground legal boundaries.This research aims to propose a new taxonomy of underground legal boundaries and model them by extending CityGML,which is a widely used 3D data model in the geospatial science domain.We developed,implemented,and tested the model for different types of underground legal boundaries.The implemented prototype showcased the potential benefits of CityGML for managing underground legal boundaries in 3D.The proposed 3D underground model can be used to address current challenges associated with communicating and managing legal boundaries in underground environments.While this data model was specifically developed for Victoria,Australia,the proposed model and approach can be used and replicated in other jurisdictions by adjusting the data requirements for underground legal boundaries.

Sustainable development and geospatial information:a strategic framework for integrating a global policy agenda into national geospatial capabilities

The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.

A collaborative approach for urban underground space development toward sustainable development goals:Critical dimensions and future directions

The utilization of urban underground space(UUS)offers an effective solution to urban problems but may also negatively affect urban development.Therefore,UUS development needs better concerted guidelines to coordinate various urban systems and the multiple components of the underground world.Sustainable Development Goals(SDGs),which should be viewed as important yardsticks for UUS development,do not explicitly mention urban underground space,although many of them are affected by both the positive and negative consequences of its development.To fill this gap,this review lays the foundations of relevant UUS concepts and uses exemplary cases to reveal that 11 out of 17 SDGs can be linked with UUS uses.These linkages also manifest that land administration,integrated planning,architectural design,and construction technology are critical dimensions for increasing the contributions of UUS to the realization of SDGs.To achieve multi-disciplinary synergies among these four critical dimensions,a collaborative approach framework based on spatial data infrastructure is required.Thus,this work provides academics and practitioners with a holistic view of sustainable UUS development.

A framework for a microscale flood damage assessment and visualization for a building using BIM-GIS integration

Flood damage assessment(FDA)is a key component of risk-based method for flood management.In the current FDA approaches,generally the uniqueness of the building is disregarded in the analysis.Therefore,they are unfit for detailed applications in which case-by-case analysis of building damage is an essential requirement.This limitation is compounded by the use of incomplete and often low-quality data inputs about the building and the assumptions and approximations made regarding the geometry and materials of its components.Such shortcomings may result in incomplete and uncertain outcomes.Considering the benefits and increasing use of three-dimensional(3D)urban modeling and Building Information Model in various urban management processes,in this paper,an integrated framework for utilization of detailed 3D building models for the assessment and 3D visualization of flood damage to building according to its distinct behavior against flood is presented.A proof-ofconcept demonstration of the framework in a case study underlined the feasibility of implementation of the framework,which can potentially benefit a variety of users and be used as a complementary approach to the current FDA methods for improving the resilience of the community toward floods and their adverse impacts.

An IFC-based database schema for mapping BIM data into a 3D spatially enabled land administration database

There are different processes in 3D urban land administration in which spatial analysis plays an underpinning role.Among 3D data models,Industry Foundation Class(IFC)provides the potential capabilities for modelling legal and physical dimensions of urban properties.However,performing spatial analysis using IFC files cannot address the on-demand spatial analysis requirements of 3D urban land administration.In response to this limitation,3D data needs to be stored in a spatial database to enable spatial analyses required by different stakeholders.Therefore,in this paper,by considering spatial analysis requirements in 3D-enabled urban land administration,an IFC-based database schema is designed.Moreover,a methodology for transforming Building Information Modelling(BIM)data into the proposed schema is provided.This methodology includes seven steps:designing the architectural model and adding legal data,georeferencing,IFC data validation and cleaning,mapping process,database data validation and cleaning,spatial analysis,and visualisation.To demonstrate the feasibility of the proposed database,three datasets are implemented in the database.Moreover,a new method for modelling legal spaces with oblique structures and two applications of spatial analysis in 3D urban land administration are provided.

Design and development of a web-based 3D cadastral visualisation prototype

Three-dimensional(3D)developments of land,such as complex high-rises,put enormous pressure on current land administration systems that have ad hoc approaches to 3D property management.These approaches are unable to support effective 3D storage,analysis and visualisation of property information.Effective visualisation is one of the essential components in realisation of a truly 3D cadastre.Currently,several 3D visualisation applications and cadastral prototypes have been developed around the world.However,they do not effectively represent ownership information in 3D because they have not been developed based on 3D cadastral visualisation requirements.After candidate 3D visualisation solutions were compared with user-derived visualisation criteria,a web-based 3D visualisation prototype was designed and developed.The functionality,usability and efficiency of the prototype were evaluated by potential users involved in the registration and management of property.While there was a high level of enthusiasm for the features of the prototype,the results also suggest further directions for development of 3D cadastral visualisation.

Expanding the SDI environment:comparing current spatial data infrastructure with emerging indoor location-based services

The authors compare key elements of the emerging field of Indoor Location-Based Services(Indoor LBS)to those currently found in spatial data infrastructure(SDI)programs.After a brief review of SDIs and Location-Based Services,the corresponding drivers,characteristics and emerging issues within the field of Indoor LBS are introduced and discussed.A comparative framework relates the two in terms of the criteria‘People’,‘Data’,‘Technologies’,‘Standards’and‘Policies/Institutional Arrangements’.After highlighting key similarities and differences,the authors suggested three areas–definition of common framework datasets in Indoor LBS,more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities–that may benefit from sharing‘lessons learned’.

Integration of cadastral survey data into building information models

Cadastral surveying plays an important role in defining legal boundaries of land and property.The current practice for recording cadastral survey data mainly relies on 2D digital or analog documents.This practice is efficient for simple land parcels but can be challenged in complex building developments.To address the issues stemmed from 2D methods of representing cadastral survey data,3D spatial information models can be considered as a viable solution for managing cadastral survey data.Building Information Modeling(BIM)enables colsslaborative 3D management of the design,construction,and operation of buildings.There have been extensive studies conducted to investigate the connectivity between BIM and 3D cadaster.Most of these studies focus on managing legal information,such as ownership boundaries and attributes,in BIM-based environments.However,there is limited investigation on how survey-ing measurements can be mapped into BIM.In this study,the proposed method for integrating the cadastral survey data into the BIM environment includes identifying cadastral survey requirements,using BIM entities relevant to cadastral survey data,enrichment of a BIM proto-type,and evaluation of the prototype.The major contribution of this study is to demonstrate the storage of cadastral survey data such as survey marks and traverse lines in the BIM environment.Therefore,this research contributes to the further enrichment of BIM with incorporating data elements related to cadastral surveying practices.It is confirmed that current BIM-based tools provide restricted capabilities for explicit management and visualiza-tion of cadastral survey data.This limitation can be addressed in the future enhancements of BIM in terms of supporting important elements for cadastral survey data.

An evaluation of integrating multisourced sensors for disaster management

Disaster management and in particular disaster response phase are highly timesensitive and dynamic processes,demanding that real-time information reaches disaster responders prior making critical decisions.During the last decade,disaster management has been widely enabled through utilizing spatial data sourcing and related technologies in the whole process of collection,access,and usage of disaster information.Currently,there are unique challenges that cannot be met without incorporating in situ sensing as an emerging technology for sourcing and managing disaster information.These include(1)high temporal and spatial resolution of information,(2)broad range of disaster data,and(3)automated operations.Incorporating in situ sensing into the disaster management process can potentially address such challenges by providing data that support all of these requirements.Following an examination of current concepts and methods for integrating multisourced sensors,a framework of the requirements for integrating in situ sensors for disaster management,is suggested.Based on this framework and its components,an evaluation of the methods is developed and applied.The results highlight that information integration of multisourced sensors is a major challenge and has not yet adequately addressed for sensor data enablement of disaster management.

Using open data to detect the structure and pattern of informal settlements:an outset to support inclusive SDGs’achievement

The detection of informal settlements is the first step in planning and upgrading deprived areas in order to leave no one behind in SDGs.Very High-Resolution satellite images(VHR),have been extensively used for this purpose.However,as a cost-prohibitive data source,VHR might not be available to all,particularly nations that are home to many informal settlements.This study examines the application of open and freely available data sources to detect the structure and pattern of informal settlements.Here,in a case study of Jakarta,Indonesia,Medium Resolution satellite imagery(MR)derived from Landsat 8(2020)was classified to detect these settlements.The classification was done using Random Forest(RF)classifier through two complementary approaches to develop the training set.In the first approach,available survey data sets(Jakarta’s informal settlements map for 2015)and visual interpreta-tion using High-Resolution Google Map imagery have been used to build the training set.Throughout the second round of classifica-tion,OpenStreetMap(OSM)layers were used as the complementary approach for training.Results from the validation test for the second round revealed better accuracy and precision in classi-fication.The proposed method provides an opportunity to use open data for informal settlements detection,when:1)more expen-sive high resolution data sources are not accessible;2)the area of interest is not larger than a city;and 3)the physical characteristics of the settlements differ significantly from their surrounding formal area.The method presents the application of globally accessible data to help the achievement of resilience and SDGs in informal settlements.

Evaluating the role of partnerships in increasing the use of big Earth data to support the Sustainable Development Goals:an Australian perspective

Leaders are increasingly calling for improved decision support to manage human and environmental challenges in the 21^(st)Century.The 17 United Nations Sustainable Development Goals(SDGs)pro-vide a framing of these challenges,wherein 169 targets require significant data to be monitored and pursued effectively.However,many targets are still not connected with big Earth data capabilities.In this conceptual paper,the authors sought to answer the question“How are partnerships influencing progress in using big Earth data to address the SDGs?”Using the Pivotal Principles for Digital Earth,we reflect on the geospatial sector’s partnering efforts and opportunities for enhancing the use of big Earth data.We use Australia as a case study to explore partnering for action towards one or more SDGs.We conclude that partnerships are emerging for big Earth data use in addressing the SDGs,but much can still be done to harness the power of partnerships for transformative SDG outcomes.We propose four key enabling priorities:1)multiple-stakeholder collaboration,2)regular enactment of the problem-solving cycle,3)transparent and reliable georeferenced data,and 4)development and preservation of trust.Five“next steps”are outlined for Australia,which can also benefit practitioners and leaders globally in problem-solving for the SDGs.

A discussion of irrational stockpiling behaviour during crisis

One of the ubiquitous human behaviours observed in natural disasters and humanitarian crisis is irrational stock-piling(also known as hoarding or panic buying).Limited,distorted and exaggerated information during crisis disturbs people’s judgement and results in aberrant actions which can be explained with economics and psychol-ogy theories.The objective of this paper is to examine the perplexing stockpiling phenomena during disasters like COVID-19 pandemic and discuss its immediate and long-term impact on economy,society and local communities.