Deep Learning of Climate Change and Extreme Events, Hydrological Processes and Land Use Dynamics Relationships

Hydrological Extremes in a Warming Climate: Nonstationarity, Uncertainties and Impacts

Deep Learning Methods for Remote Sensing

Deep Learning and Computer Vision in Remote Sensing

Disaster Risk Reduction and Climate Change Adaptation: An Interdisciplinary Approach

AI for Marine, Ocean and Climate Change Monitoring

Assessing Hydrological Drought in a Climate Change: Methods and Measures

Deep Learning and Computer Vision in Remote Sensing-II

Deep Learning and Edge Computing for Internet of Things

Sustainability with Changing Climate and Extremes

Deep Learning Applications in Remote Sensing for Climate Change Monitoring

Deep Learning in Image Processing and Pattern Recognition

Big Data Analytics and Machine Learning for Smart Agriculture

Modeling Forest Response to Climate Change

Elsevier Deep Learning for Earth Observation and Climate Monitoring

Elsevier

The Application of Machine Learning in Geotechnical Engineering

Geo-Information for Watershed Processes

Responses of Soil Carbon and Nitrogen Dynamics and GHG Fluxes in Forest Ecosystems to Climate Change and Human Activity

Artificial Intelligence-Based Learning Approaches for Remote Sensing

Remote Sensing and Artificial Intelligence in Inland Waters Monitoring

Artificial Intelligence and Deep Learning in Sensors and Applications

Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring

Urban Forest and Urban Microclimate

Managed Aquifer Recharge for Water Resilience

New Insights in Machine Learning and Deep Neural Networks