Year: 2022
Type: editorial
Abstract: Environmental modeling can be used to understand environmental systems, or for performing interdisciplinary analysis that can support decisions and policy.Model-driven methods have remained dominant, especially for traditional and classical problems that deal with Big Earth Data that come from various data sources with different formats and scales.With recent breakthroughs in data acquisition technology, Big Earth Data can provide globally established, multi-source, multi-scale, high-dimensional, heterogeneous, high-resolution, and highly dynamic datasets.Big Earth Data, with its emerging technologies and approaches, may be an evolution in earth observation, and it also may allow us to use and apply them to various domains in new ways (Sudmanns et al., 2020; Zhang L et al., 2021).At the same time, artificial intelligence is rapidly progressing thanks to advanced algorithm architectures (He et al., 2016), powerful computing devices, and large available datasets (Deng et al., 2009;Liu et al., 2022).The convergence between Big Earth Data and artificial intelligence could open a new era for the advance of environmental modeling.Big Earth Data Intelligence provides new opportunities to understand the environmental modeling of earth systems which helps to resolve problems, such as spatiotemporal complement, data assimilation and fusion (Armstrong et al., 2019;
Authors: Peng Liu, Mohd Anul Haq, Yizhe Zhan
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,490
OpenAlex ID: W4229454478