How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions
AY Sun, BR Scanlon - Environmental Research Letters, 2019 - iopscience.iop.org
Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …
of environment and water management (EWM). Big Data are information assets …
Social media data for environmental sustainability: A critical review of opportunities, threats, and ethical use
Social media data are transforming sustainability science. However, challenges from
restrictions in data accessibility and ethical concerns regarding potential data misuse have …
restrictions in data accessibility and ethical concerns regarding potential data misuse have …
Social media for intelligent public information and warning in disasters: An interdisciplinary review
Social media offers participatory and collaborative structure and collective knowledge
building capacity to the public information and warning approaches. Therefore, the author …
building capacity to the public information and warning approaches. Therefore, the author …
Participatory sensing and digital twin city: Updating virtual city models for enhanced risk-informed decision-making
The benefits of a digital twin city have been assessed based on real-time data collected from
preinstalled Internet of Things (IoT) sensors (eg, traffic, energy use, air pollution, water …
preinstalled Internet of Things (IoT) sensors (eg, traffic, energy use, air pollution, water …
Management of climate resilience: exploring the potential of digital twin technology, 3D city modelling, and early warning systems
Cities, and in particular those in coastal low-lying areas, are becoming increasingly
susceptible to climate change, the impact of which is worsened by the tendency for …
susceptible to climate change, the impact of which is worsened by the tendency for …
Citizens AND HYdrology (CANDHY): conceptualizing a transdisciplinary framework for citizen science addressing hydrological challenges
F Nardi, C Cudennec, T Abrate, C Allouch… - Hydrological …, 2022 - Taylor & Francis
Widely available digital technologies are empowering citizens who are increasingly well
informed and involved in numerous water, climate, and environmental challenges. Citizen …
informed and involved in numerous water, climate, and environmental challenges. Citizen …
Identifying disaster-related tweets and their semantic, spatial and temporal context using deep learning, natural language processing and spatial analysis: a case …
We introduce an analytical framework for analyzing tweets to (1) identify and categorize fine-
grained details about a disaster such as affected individuals, damaged infrastructure and …
grained details about a disaster such as affected individuals, damaged infrastructure and …
Data deprivations, data gaps and digital divides: Lessons from the COVID-19 pandemic
This paper draws lessons from the COVID-19 pandemic for the relationship between data-
driven decision making and global development. The lessons are that (i) users should keep …
driven decision making and global development. The lessons are that (i) users should keep …
A systematic review of existing early warning systems' challenges and opportunities in cloud computing early warning systems
This paper assessed existing EWS challenges and opportunities in cloud computing through
the PSALSAR framework for systematic literature review and meta-analysis. The research …
the PSALSAR framework for systematic literature review and meta-analysis. The research …
Disaster damage assessment based on fine-grained topics in social media
Social media data have been widely used to enrich human-centric information for situational
awareness and disaster assessment. Owing to the granularity of topics detected from …
awareness and disaster assessment. Owing to the granularity of topics detected from …