6. Tracking New Jersey’s Changing Landscape

Lathrop, Richard H.; Hasse, John

doi:10.36019/9780813539225-007

Cited by 2 publications

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“…The rich information obtained is embedded within remote-sensing data sets, and deep-learning approaches to facilitate accurate and efficient analysis of urban environmental characteristics (Liu and Weng 2012;Wichansky et al 2006;Zhang and Fu 2020). The integration of these diverse datasets through deep-learning techniques enables a comprehensive understanding of urban environmental processes (Dacic et al 2020;Lathrop and Hasse 2006;Meerow 2020;Wichansky et al 2006). Urban environmental hazards involve complete monitoring, effective management, and proactive mitigation strategies and some key aspects of studying, monitoring, managing, and mitigating includes:…”

Section: Introductionmentioning

confidence: 99%

Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability

Kumar,

Bassill,

Ghosh

2024

International Journal on Smart Sensing and Intelligent Systems

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Deep learning has changed the approach of urban environmental risk assessment and management. These methods enable solid models for large data sets, enabling early identification, prediction, and description of environmental risks. The current work analyses the advances in deep learning for urban environmental hazard assessments and disaster studies to provide monitoring, management, and mitigation measures. It reports the improvement in self-supervised learning, transformer architectures, persistent learning, attention mechanisms, adversarial robustness, associated learning, meta-learning, and multimodal learning within the domain of urban environmental hazard analysis. These approaches allow the creation of robust models for handling vast data volumes, facilitating early detection, prediction, and characterisation of diverse environmental threats. This trends analysis for urban applications will bring insights for connecting deep-learning models for effective and proactive approaches to tackle urban environmental hazards and disasters.

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Section: Introductionmentioning

confidence: 99%

Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability

Kumar,

Bassill,

Ghosh

2024

International Journal on Smart Sensing and Intelligent Systems

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Extreme Climate Events, Household Decision-Making and Transitions in the Immediate Aftermath of Hurricane Sandy

Solecki

Leichenko

Eisenhauer

2017

Miscellanea Geographica

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It is five years since Hurricane Sandy heavily damaged the New YorkNew Jersey Metropolitan region, and the fuller character of the long-term response can be better understood. The long-term response to Hurricane Sandy and the flooding risks it illustrated are set in myriad of individual and collective decisions taken during the time following the event. While the physical vulnerability of this region to storm surge flooding and climate change risks including sea level rise has been well-documented within the scholarly literature, Sandy's impact placed decision-makingpost extreme events into the forefront of public and private discussions about the appropriate response.Some of the most fundamental choices were made by individual homeowners who houses were damaged and in some cases made uninhabitable following the storm. These individuals were forced to make decisions regarding where they would live and whether Sandy's impact would result in their moving. In the disaster recovery and rebuilding context, these early household struggles about whether to leave or stay are often lost in the wider and longer narrative of recovery. To examine this early phase, this paper presents results of a research study that documented the ephemeral evidence of the initial phase of recovery in coastal communities that were heavily impacted by Hurricane Sandy's storm surge and flooding. Hurricane Sandy and the immediate response to the storm created conditions for a potential large-scale transformation with respect to settlement of the coastal zone. In the paper, we examine and analyze survey and interview results of sixty-one residents and two dozen local stakeholders and practitioners to understand the stresses and transitions experienced by flooded households and the implications for the longer term resiliency of the communities in which they are located.

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6. Tracking New Jersey’s Changing Landscape

Cited by 2 publications

References 0 publications

Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability

Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability

Extreme Climate Events, Household Decision-Making and Transitions in the Immediate Aftermath of Hurricane Sandy

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