Environment Observation Analysis Based on Remote Sensing and Geospatial Artificial Intelligence
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 28 November 2024 | Viewed by 42
Special Issue Editors
Interests: remote sensing; forecasting; artificial intelligence; spatiotemporal data mining; uncertainty analysis
Interests: hydrologic modeling; data assimilation; soil moisture remote sensing and machine learning
Interests: flood monitoring; geospatial analysis; smart city; sensor web
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; machine learning; classification; land use land cover; time-series analysis; urban informatics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
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
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- remote sensing
- big data
- GeoAI
- spatiotemporal processes
- disaster analysis
- large-scale monitoring and prediction
