Special Issue "Advances to GIS for Sensing of Earth and Human Interaction"
Deadline for manuscript submissions: 30 November 2021.
Interests: big geodata mining; geostatistics; urban computation
Interests: application of information and communication technologies; information society development; GIS and remote sensing; methodology and applications of geoinformation systems; analysis, modeling, and simulation of spatial data; monitoring and land use changes; urbanization issues; natural hazard issues
Interests: spatiotemporal data analysis; geographically computational epidemiology; GIS for transportation
Special Issues and Collections in MDPI journals
Interests: big data science and analytics; health and environment; spatially integrated social science; GIS-based modeling
Interests: urban analysis; long-term land change, built environment, time series analysis in remote sensing; integrative approaches using remotely sensed data and other geospatial datasets
Advances in GIS for Sensing of Earth and Human Interactions
Earth and human interaction is one of the core issues in geography. Remotely sensed data and associated analytical methods are essential for detecting changes in the Earth’s surface. Although changes derived from remote sensing data can be used as a proxy to infer the intensity of human activity, the observation of human activities from remote sensing is indirect. With the development of location-aware technologies, alternative data sources measuring human activities have emerged, and social sensing techniques have been developed to reveal human behavior patterns. The combination of remote sensing data and human behavior data provides a new perspective on coupled human-natural systems. For this reason, we have launched this special issue on sensing the interactions between Earth and humans with both types of data. The topics of this issue include but are not limited to:
- Multisource big data processing (e.g., social media data, cellular signaling data, vehicle trajectories, and other VGIs);
- Urban function identification with remote sensed data and human behavior data;
- Simulation models of human–Earth system interactions;
- Urban environment evaluation with multisource data;
- Urban renewal detection based on remote sensing and VGI data;
- Human activity and its environmental effects;
- Evolution of urban systems and populated places based on alternative (non-remote sensing) data.
Prof. Dr. Piotr A. Werner
Prof. Dr. Ling Yin
Dr. Xi Gong
Dr. Johannes H. Uhl
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 papers will be 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 2400 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.
- Coupled human-natural systems
- Social sensing
- Human-environmental interactions
- Human behavior
- Geospatial big data
- Urban analysis