Remote Sensing Application in the Socioeconomic Impact of Climate Change

Dear Colleagues,

“Climate change is happening now and to all of us. No country or community is immune,” said United Nation Secretary-General António Guterres. However, people will not bear the impact of climate change equally and fairly. For example, communities that are dependent on agriculture may be most affected while having contributed least to climate change; or in cities, low-income households may live in hotter suburbs than wealthy families, and thus, those households pay more for cooling energy consumption and are also more vulnerable to heat risks. As a result, there is a growing focus on the relationship between climate change and social inequality, also known as climate justice. 

Taking action on climate adaptation and mitigation in ways that respond effectively to the issue of climate change and social inequality is dependent on insights into various matters, such as physical conditions of the Earth’s surface, community and socioeconomic factors and land use and urban development policies. Remote sensing data and methodologies are valuable assets to obtain such insights. However, there has been limited attention to the potential of remote sensing to contribute to investigate the relationship between climate change and social inequality. Accordingly, the main focus of this open-access Special Issue is to compile the state-of-the-art in understanding the role of remote sensing data and methodologies to understand and act on issues of climate change and social inequality.

We are inviting submissions including but not limited to:

1. Developing new and robust remote sensing indices for monitoring the status of climate justice in regional and local scales;
2. Geospatial analysis of potential spatial inequality relating to thermal characteristics and green cover in urban areas;
3. Scale and level of analysis in the integration of remote sensing and demography factors to improve climate justice;
4. Remote sensing applications in investigating the impact of urban development indicators and land use policies to improve the climate justice;
5. Machine learning methods in climate justice analysis using big remote sensing data.

Dr. Kaveh Deilami
Dr. Chayn Sun
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.

• Climate change
• Climate justice
• Environmental justice
• Thermal inequality
• Satellite images
• Inequality and green growth