AIMC Topic: Climate Change

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Predictive pollen-based biome modeling using machine learning.

PloS one
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published Af...

Estimating regional effects of climate change and altered land use on biosphere carbon fluxes using distributed time delay neural networks with Bayesian regularized learning.

Neural networks : the official journal of the International Neural Network Society
The ability to accurately predict changes of the carbon and energy balance on a regional scale is of great importance for assessing the effect of land use changes on carbon sequestration under future climate conditions. Here, a suite of land cover-sp...

Can China fulfill its commitment to reducing carbon dioxide emissions in the Paris Agreement? Analysis based on a back-propagation neural network.

Environmental science and pollution research international
Due to the increasingly severe situation regarding adaptation to climate change, global attention has focused on whether China can fulfill its commitment to the Paris Agreement as the largest producer of carbon dioxide (CO) emissions. In this study, ...

Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil.

The Science of the total environment
Models to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition in...

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

Environmental science and pollution research international
The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neu...

Using fuzzy logic to determine the vulnerability of marine species to climate change.

Global change biology
Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biolog...

An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor.

Global change biology
Wetlands are important providers of ecosystem services and key regulators of climate change. They positively contribute to global warming through their greenhouse gas emissions, and negatively through the accumulation of organic material in histosols...

The Knowledge Base for Achieving the Sustainable Development Goal Targets on Water Supply, Sanitation and Hygiene.

International journal of environmental research and public health
Safe drinking water, sanitation, and hygiene (WASH) are fundamental to an improved standard of living. Globally, 91% of households used improved drinking water sources in 2015, while for improved sanitation it is 68%. Wealth disparities are stark, wi...

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

Sensors (Basel, Switzerland)
Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and obj...

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity.

PloS one
Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the m...