Innovation and Sustainable Development of Remote Sensing Technology—2nd Edition

Dear Colleagues,

Through the research and application of Earth and humanities–social sciences, we can better understand the Earth system and develop effective sustainable development strategies to contribute to the future of people and the planet. The fundamental elements in the pursuit of Earth science research are image processing and information extraction (such as land cover and land use (LCLU), geological disasters, geological lithology, etc.) by using machine learning and deep learning algorithms, which are gleaned from the advancements in remote sensing technology. Fusion and modeling of Earth and humanities–social data serve as a cornerstone for policy development and scientific research of sustainable development. This Special Issue, titled “Innovation and Sustainable Development of Remote Sensing Technology—2nd Edition”, welcomes original studies on datasets, methodologies, and applications. Topics of interest include but are not limited to the following:

• Image processing based on machine learning and deep learning algorithms;
• Information extraction based on machine learning and deep learning algorithms;
• Remote sensing information extraction and sustainable development;
• Remote sensing information extraction and urbanization;
• Remote sensing information extraction and ecological security;
• Remote sensing information extraction and ecosystem service value;
• Remote sensing information change detection and driving forces;
• Remote sensing information extraction and socio-economic system coupling;
• Remote sensing information extraction and climate change;
• Remote sensing information extraction and land resource management;
• Remote sensing information extraction and water resource management;
• Remote sensing information extraction and spatiotemporal changes;
• Remote sensing information extraction and industrial development;
• Remote sensing information extraction and environmental protection;
• Fusion and modeling of Earth and humanities–social data;
• Applications of multi-source data for sustainable development.

Dr. Xianju Li
Dr. Pan Zhu
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. Sustainability 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.

• remote sensing
• machine learning
• land cover and land use
• urbanization
• ecological security
• ecosystem service value

• Remote Sensing Technology Innovation for Sustainable Development Goals in Sustainability (3 articles)