The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …

The analysis of travel mode choice is an important task in transportation planning and policy
making in order to understand and predict travel demands. While advances in machine …

In ecological analyses of species and community distributions there is interest in the nature
of their responses to environmental gradients and in identifying the most important …

This is largely due to 1) a lack of communication and collaboration between the machine
learning research community and natural scientists, 2) a lack of communication about …

In this paper we present a general overview of several supervised machine learning (ML)
algorithms and illustrate their use for the prediction of mass mortality events in the coastal …

Land subsidence (LS) is among the most critical environmental problems, affecting both
agricultural sustainability and urban infrastructure. Existing methods often use either simple …

Abstract Machine learning (ML) expands traditional data analysis and presents a range of
opportunities in ecosystem service (ES) research, offering rapid processing of 'big data'and …

Under future climate change, modification of temperature and salinity are expected to result
in distribution shifts of marine organisms, including commercial fish and shellfish. Changes …

Air temperature is an essential component in microclimate and environmental health
research, but difficult to map in urban environments because of strong temperature …