• Title/Summary/Keyword: Spatial Asset Mapping

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Modeling Community Capacity Building Using Spatial Asset Mapping (공간자산매핑을 이용한 지역사회 능력배양의 모델링에 관한 연구)

  • Liou, Jaeik
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.4
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    • pp.98-108
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    • 2004
  • The concept of community capacity is regarded as the ability of people and communities to do works associated with the determinant factors and indicators of the circumstances of socio-economic, environmental and physical contexts. Building capacity of communities to effectively analyze our problematic issues and planning of community development is often required to scrutinize current status of community of socio-economic and infrastructural capacity development with GIS. We consider community development as a planned effort to build assets that increase the capacity of communities. Spatial asset mapping is the process enabling to identify and make inventories of tangible and intangible assets. This mapping requires developing a capacity inventory that collects individual organizational and community capacities in view of human, socio-cultural, natural, financial, digital, and physical capacity. The purpose of this research is not only designed to suggest a new concept capacity building, but also proposes a more creative framework of asset-based community cap linking to parcel-based spatial asset mapping and capacity mapping process.

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A Tool for Mapping and Measuring Sustainable Capacity Development: Concepts, Methods and Contexts (균형적 능력개발의 매핑 및 측정을 위한 도구 - 개념, 방법론 및 배경 -)

  • Liou, Jae-Ik
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.165-175
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    • 2006
  • The discussion about capacity development (CD) has been spotlighted as significant drivers for sustainable development in recent years. Multi-dimensional natures of capacities would lead to various definitions of CD in international institutes and organizations. CD is perceived as an endogeneous process to improve actionable learning and knowledge, but most of core capacities still remain abstract notion and might be unreliable in sustainable development (SD). The paper first explicates international perspectives of CD in association with SD. An agent-based model is especially proposed to portray more details of CD. It illuminates the role of assets (or capitals, resources) in agents to impact on ingredients of CDs that are drivers or enablers for improvement of SD. A definition of sustainable capacity development is firstly articulated in international society and its conceptual framework is also creatively designed to assist concerned international organizations. The paper concludes by proposing practical spatial asset mapping linking to agent-based organizational capacity as a tool for measuring sustainable capacity development.

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Mapping Poverty Distribution of Urban Area using VIIRS Nighttime Light Satellite Imageries in D.I Yogyakarta, Indonesia

  • KHAIRUNNISAH;Arie Wahyu WIJAYANTO;Setia, PRAMANA
    • Asian Journal of Business Environment
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    • v.13 no.2
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    • pp.9-20
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    • 2023
  • Purpose: This study aims to map the spatial distribution of poverty using nighttime light satellite images as a proxy indicator of economic activities and infrastructure distribution in D.I Yogyakarta, Indonesia. Research design, data, and methodology: This study uses official poverty statistics (National Socio-economic Survey (SUSENAS) and Poverty Database 2015) to compare satellite imagery's ability to identify poor urban areas in D.I Yogyakarta. National Socioeconomic Survey (SUSENAS), as poverty statistics at the macro level, uses expenditure to determine the poor in a region. Poverty Database 2015 (BDT 2015), as poverty statistics at the micro-level, uses asset ownership to determine the poor population in an area. Pearson correlation is used to identify the correlation among variables and construct a Support Vector Regression (SVR) model to estimate the poverty level at a granular level of 1 km x 1 km. Results: It is found that macro poverty level and moderate annual nighttime light intensity have a Pearson correlation of 74 percent. It is more significant than micro poverty, with the Pearson correlation being 49 percent in 2015. The SVR prediction model can achieve the root mean squared error (RMSE) of up to 8.48 percent on SUSENAS 2020 poverty data.Conclusion: Nighttime light satellite imagery data has potential benefits as alternative data to support regional poverty mapping, especially in urban areas. Using satellite imagery data is better at predicting regional poverty based on expenditure than asset ownership at the micro-level. Light intensity at night can better describe the use of electricity consumption for economic activities at night, which is captured in spending on electricity financing compared to asset ownership.

Towards UAV-based bridge inspection systems: a review and an application perspective

  • Chan, Brodie;Guan, Hong;Jo, Jun;Blumenstein, Michael
    • Structural Monitoring and Maintenance
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    • v.2 no.3
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    • pp.283-300
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    • 2015
  • Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.