[HTML][HTML] Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework
Climate change and rapid urbanisation exacerbated multiple urban issues threatening
urban sustainability. Numerous studies integrated machine learning and remote sensing to …
urban sustainability. Numerous studies integrated machine learning and remote sensing to …
[HTML][HTML] Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: paradigms, applications and prospects
W Zhang, W Huang, J Tan, Q Guo, B Wu - Chemosphere, 2022 - Elsevier
Energy crisis and environmental pollution have become the bottleneck of human
sustainable development. Therefore, there is an urgent need to develop new catalysts for …
sustainable development. Therefore, there is an urgent need to develop new catalysts for …
Deep neural networks for spatiotemporal PM2. 5 forecasts based on atmospheric chemical transport model output and monitoring data
Abstract Reliable long-horizon PM 2.5 forecasts are crucial and beneficial for health
protection through early warning against air pollution. However, the dynamic nature of air …
protection through early warning against air pollution. However, the dynamic nature of air …
CFD-and BPNN-based investigation and prediction of air pollutant dispersion in urban environment
This study employed a Computational Fluid Dynamics (CFD)-based back propagation
neural network (BPNN) to investigate and predict the pollutant dispersion in an ideal urban …
neural network (BPNN) to investigate and predict the pollutant dispersion in an ideal urban …
Pollutant specific optimal deep learning and statistical model building for air quality forecasting
Poor air quality is becoming a critical environmental concern in different countries over the
last several years. Most of the air pollutants have serious consequences on human health …
last several years. Most of the air pollutants have serious consequences on human health …
[HTML][HTML] Integration of machine learning algorithms and GIS-based approaches to cutaneous leishmaniasis prevalence risk mapping
N Shabanpour, SV Razavi-Termeh… - International Journal of …, 2022 - Elsevier
Cutaneous leishmaniasis is a complex infection that is caused by different species of
Leishmania and affects more than 2 million people in 88 countries. Identifying the …
Leishmania and affects more than 2 million people in 88 countries. Identifying the …
A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment
M Farahani, SV Razavi-Termeh… - Sustainable Cities and …, 2022 - Elsevier
Mapping individuals' sense of hearing in the urban environment helps urban managers and
planners accomplish goals such as creating a favorable urban environment for the citizens …
planners accomplish goals such as creating a favorable urban environment for the citizens …
Spatial modeling of asthma-prone areas using remote sensing and ensemble machine learning algorithms
In this study, asthma-prone area modeling of Tehran, Iran was provided by employing three
ensemble machine learning algorithms (Bootstrap aggregating (Bagging), Adaptive …
ensemble machine learning algorithms (Bootstrap aggregating (Bagging), Adaptive …
[HTML][HTML] Hazard susceptibility mapping with machine and deep learning: a literature review
AJ Pugliese Viloria, A Folini, D Carrion, MA Brovelli - Remote Sensing, 2024 - mdpi.com
With the increase in climate-change-related hazardous events alongside population
concentration in urban centres, it is important to provide resilient cities with tools for …
concentration in urban centres, it is important to provide resilient cities with tools for …