Environment Observation Analysis Based on Remote Sensing and Geospatial Artificial Intelligence

Dear Colleagues,

Satellite remote sensing provides a direct method for the global observation of environmental concerns, such as land-use/land-cover changes, soil moisture, precipitation, floods, or surface water dynamics. The utilization of remote sensing big data to make environmental observations could prove vital to disaster management, information analysis, and risk preparations. With the development of geospatial artificial intelligence, the ability to handle hundreds of or thousands of satellite images has been greatly improved and the large-scale urban, hydrological, meteorological, and ecological retrieval of land-surface parameters is possible. Therefore, it would be interesting to use satellite remote sensing and AI approaches to reveal large-scale geographical phenomena and laws in order to better understand the hydrosphere, lithosphere, biosphere, atmosphere, and anthroposphere.
Anthropogenic activities have been changing the Earth’s environment, and it is necessary to monitor the incoming changes on a regular basis. We invite your insights and contributions in various research areas involving remote sensing combined with a GeoAI approach. Papers can focus on, but are not limited to, the following topics:

• Monitoring of floods, droughts, and other disasters on large spatial scales;
• Spatiotemporal monitoring and prediction of spatiotemporal processes;
• Urban, hydrological, meteorological, and ecological retrieval of land-surface parameters;
• Fine-scale monitoring of anthropogenic activities and their impacts;
• Novel GeoAI approaches for environmental analysis and prediction;
• Multisource data fusion using GeoAI approaches;
• Global environmental risk analysis using big data;
• Data–knowledge fusion for environmental remote sensing.

Prof. Dr. Lei Xu
Dr. Peyman Abbaszadeh
Dr. Wenying Du
Dr. Min Huang
Guest Editors

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