scholarly journals Cross-Border Urban Change Detection and Growth Assessment for Mexican-USA Twin Cities

2021 ◽  
Vol 13 (21) ◽  
pp. 4422
Author(s):  
Alexander Fekete ◽  
Peter Priesmeier
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Risk Reduction ◽  
Urban Growth ◽  
Social Vulnerability ◽  
Disaster Risk Reduction ◽  
Open Data ◽  
Disaster Risk ◽  
Hazard Mapping ◽  
Risk Monitoring

Remote sensing applications of change detection are increasingly in demand for many areas of land use and urbanization, and disaster risk reduction. The Sendai Framework for Disaster Risk Reduction and the New Urban Agenda by the United Nations call for risk monitoring. This study maps and assesses the urban area changes of 23 Mexican-USA border cities with a remote sensing-based approach. A literature study on existing studies on hazard mapping and social vulnerability in those cities reveals a need for further studies on urban growth. Using a multi-modal combination of aerial, declassified (CORONA, GAMBIT, HEXAGON programs), and recent (Sentinel-2) satellite imagery, this study expands existing land cover change assessments by capturing urban growth back to the 1940s. A Geographic Information System and census data assessment results reveal that massive urban growth has occurred on both sides of the national border. On the Mexican side, population and area growth exceeds the US cities in many cases. In addition, flood hazard exposure has grown along with growing city sizes, despite structural river training. These findings indicate a need for more risk monitoring that includes remote sensing data. It has socio-economic implications, too, as the social vulnerability on Mexican and US sides differ. This study calls for the maintenance and expansion of open data repositories to enable such transboundary risk comparisons. Common vulnerability variable sets could be helpful to enable better comparisons as well as comparable flood zonation mapping techniques. To enable risk monitoring, basic data such as urban boundaries should be mapped per decade and provided on open data platforms in GIS formats and not just in map viewers.

Disaster risk reduction by measuring social vulnerability around the Merapi Volcano

2020 ◽  
Author(s):  
Yohana Noradika Maharani ◽  
Arif Rianto Budi Nugroho ◽  
Dzikrina Farah Adiba ◽  
Iin Sulistiyowati
Keyword(s):  
Risk Reduction ◽  
Social Vulnerability ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Merapi Volcano

scholarly journals Social resilience: the forgotten dimension of disaster risk reduction

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
Guy Sapirstein
Keyword(s):  
United Nations ◽  
International Development ◽  
Risk Reduction ◽  
Social Vulnerability ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Social Resilience ◽  
Individual Vulnerability ◽  
Individual Resilience ◽  
Current Thinking

The current thinking in the Disaster Risk Reduction field emphasizes assessment and reduction of vulnerability and especially social vulnerability as an important factor in mitigating the effects of disasters. In the process of emphasizing vulnerability, the role and complexity of social resilience was somewhat lost and at times minimized. For example, Terry Cannon and his colleagues include resilience as a factor of social vulnerability in a report to United Kingdom Department for International Development (DFID) (Cannon, Twigg and Rowell, 2002). The United Nations University, Institute for Environment and Human Security (UNU-EHS) delineates “Social Vulnerability” and “Individual Vulnerability” as working areas, but does not mention Social or Individual Resilience (Bogardi, 2006).

scholarly journals Disaster Risk Reduction Regime in Japan: An Analysis in the Perspective of Open Data, Open Governance

2021 ◽  
Vol 14 (1) ◽  
pp. 19
Author(s):  
Sakiko Kanbara ◽  
Rajib Shaw
Keyword(s):  
Community Engagement ◽  
Risk Reduction ◽  
Data Privacy ◽  
Disaster Risk Reduction ◽  
Emerging Technologies ◽  
Spatial Information ◽  
Open Data ◽  
Disaster Risk ◽  
Data Movement ◽  
Governance Systems

This paper addresses open data, open governance, and disruptive/emerging technologies from the perspectives of disaster risk reduction (DRR). With an in-depth literature review of open governance, the paper identifies five principles for open data adopted in the disaster risk reduction field: (1) open by default, (2) accessible, licensed and documented, (3) co-created, (4) locally owned, and (5) communicated in ways that meet the needs of diverse users. The paper also analyzes the evolution of emerging technologies and their application in Japan. The four-phased evolution in the disaster risk reduction is mentioned as DRR 1.0 (Isewan typhoon, 1959), DRR 2.0 (the Great Hanshin Awaji Earthquake, 1995), DRR 3.0 (the Great East Japan Earthquake and Tsunami: GEJE, 2011) and DRR 4.0 (post GEJE). After the GEJE of 2011, different initiatives have emerged in open data, as well as collaboration/partnership with tech firms for emerging technologies in DRR. This paper analyzes the lessons from the July 2021 landslide in Atami, and draws some lessons based on the above-mentioned five principles. Some of the key lessons for open data movement include characterizing open and usable data, local governance systems, co-creating to co-delivering solutions, data democratization, and interpreting de-segregated data with community engagement. These lessons are useful for outside Japan in terms of data licensing, adaptive governance, stakeholder usage, and community engagement. However, as governance systems are rooted in local decision-making and cultural contexts, some of these lessons need to be customized based on the local conditions. Open governance is still an evolving culture in many countries, and open data is considered as an important tool for that. While there is a trend to develop open data for geo-spatial information, it emerged from the discussion in the paper that it is important to have customized open data for people, wellbeing, health care, and for keeping the balance of data privacy. The evolution of emerging technologies and their usage is proceeding at a higher speed than ever, while the governance system employed to support and use emerging technologies needs time to change and adapt. Therefore, it is very important to properly synchronize and customize open data, open governance and emerging/disruptive technologies for their effective use in disaster risk reduction.

scholarly journals Remote Sensing Derived Built-Up Area and Population Density to Quantify Global Exposure to Five Natural Hazards over Time

2018 ◽  
Vol 10 (9) ◽  
pp. 1378 ◽  
Author(s):  
Daniele Ehrlich ◽  
Michele Melchiorri ◽  
Aneta Florczyk ◽  
Martino Pesaresi ◽  
Thomas Kemper ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Population Density ◽  
Risk Reduction ◽  
Natural Hazards ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Earth Observation ◽  
Human Settlement ◽  
Global Population ◽  
Over Time

Exposure is reported to be the biggest determinant of disaster risk, it is continuously growing and by monitoring and understanding its variations over time it is possible to address disaster risk reduction, also at the global level. This work uses Earth observation image archives to derive information on human settlements that are used to quantify exposure to five natural hazards. This paper first summarizes the procedure used within the global human settlement layer (GHSL) project to extract global built-up area from 40 year deep Landsat image archive and the procedure to derive global population density by disaggregating population census data over built-up area. Then it combines the global built-up area and the global population density data with five global hazard maps to produce global layers of built-up area and population exposure to each single hazard for the epochs 1975, 1990, 2000, and 2015 to assess changes in exposure to each hazard over 40 years. Results show that more than 35% of the global population in 2015 was potentially exposed to earthquakes (with a return period of 475 years); one billion people are potentially exposed to floods (with a return period of 100 years). In light of the expansion of settlements over time and the changing nature of meteorological and climatological hazards, a repeated acquisition of human settlement information through remote sensing and other data sources is required to update exposure and risk maps, and to better understand disaster risk and define appropriate disaster risk reduction strategies as well as risk management practices. Regular updates and refined spatial information on human settlements are foreseen in the near future with the Copernicus Sentinel Earth observation constellation that will measure the evolving nature of exposure to hazards. These improvements will contribute to more detailed and data-driven understanding of disaster risk as advocated by the Sendai Framework for Disaster Risk Reduction.

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