Large-Scale Machine Learning in the Earth Sciences

ISBN-13: 9781498703871 / Angielski / Twarda / 2017 / 208 str.

Ashok N. Srivastava; Ramakrishna Nemani; Karsten Steinhaeuser

Opis

Large-scale machine learning, currently focused on the internet and/or social network analysis, could prove highly beneficial in the study of earth science, a broad multidisciplinary field of study that generates huge amounts of data. This comprehensive book is the first to tackle the subject of large-scale machine learning and its applications to the earth sciences. It covers significant issues in earth science and large-scale machine learning techniques with each contributing author recognized as a well-known authority in the field.

Spis treści

Computer science. Ecosystems. Climate/hydrology. Climate/landuse. Climate/carbon. Machine learning. Earth science. Estimation and bias correction in aerosols. Land cover monitoring and change detection. Rainfall prediction. Mining spatio-temporal data sets. Climate systems using earth science models. Ocean eddy monitoring. Class imbalance in earth science. Big data and petascale climate science. Machine learning of precipitation forecasts. Forest fire mapping. Morphological neural networks for hyperspectral data using HPC. Machine learning applications for biomass assessments. Grid computing for remote sensing applications. Deep learning for very high resolution imagery classification.