Remote Sensing Application in Sustainable Urban Planning and Environmental Services in the Big Data Era (Second Edition)

Dear Colleagues,

We are launching the second Special Issue of Remote Sensing to be released under the title “Remote Sensing Application in Sustainable Urban Planning and Environmental Services in the Big Data Era”.

During the past decades, multiple remote sensing data sources, including nighttime light images, high-spatial-resolution multispectral satellite images, unmanned drone images, and hyperspectral images, among many others, have provided novel opportunities for an examination of the dynamics of urban landscapes. Urban scholars are now equipped with abundant data to examine many theoretical arguments that often resulted from limited and indirect observations and less-than-ideal controlled experiments, manifested using only surveys or statistical yearbooks.

In the meantime, the rapid development of telecommunications and mobile technology and the emergence of online search engines and social media platforms has fundamentally altered human activities and the urban landscape. The availability of abundant real-time, geotagged individual pieces of information has drastically changed how scholars see the dynamic urban landscape; for the first time, it can be considered from both a micro and macro level. This type of data, while often regarded as one type of “Big Data,” is also known as “social sensing” data; these are different from the traditional electric–optical remote sensing data acquired through electromagnetic sensors, yet still qualifies as a new type of “remote sensing” data. This new type of “remote sensing” data carries a vast quantity of information. With advanced computational technology and algorithms, this seemingly chaotic “large amount of” micro pieces of individual activities contained in the social sensing data can now be assembled into macro patterns in almost real time, exhibiting the constantly moving, changing, and evolving urban landscape to urban scholars. Yet, combining traditional EO remote sensing data and social sensing remote sensing data to study dynamic urban patterns requires further exploration; this will be achieved by employing newly developed tools and approaches.

The combination of these two types of data sources results in explosive and mind-blowing discoveries in contemporary urban studies, especially for the purposes of sustainable urban planning and development and urban health. Urban scholars are now, for the first time, able to model, simulate, and predict changes in the urban landscape using real-time data to produce the most realistic modeling results; this will provide invaluable information for urban planners and governments, and promote the establishment of a sustainable and healthy urban future. This Special Issue attempts to assemble a cohort of studies that specifically examine how the most up-to-date remote sensing data sources and geotagged social media/search engine data can be incorporated in order to support sustainable urban planning and development and to promote urban health in this new era.

The scope of this Special Issue includes the following topics:

• Urban simulations supported by remote sensing and big data;
• Mechanisms of urban landscape change;
• Spatiotemporal examination of the urban landscape;
• Noval analytical approaches utilizing remote sensing and big data in urban studies;
• Studies of urban vibrancy with remote sensing and big data analytical approaches;
• Integrating RS and big data (social sensing data) to investigate healthy and sustainable urban development;
• Investigating urban environmental services via urban remote sensing and big data;
• Application of hyperspectral remote sensing data and/or combination of hyperspectral and social sensing data to study urban dynamics;
• Application of remote sensing technologies, including both EO remote sensing and social sensing, to study urban lead poisoning, water pollution, air pollution, and other environmental disasters.

Prof. Dr. Danlin Yu
Guest Editor

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.

• big data described urban landscape
• urban remote sensing
• sustainable urban development
• urban health under the lens of remote sensing and social sensing technologies
• spatiotemporal data analysis in urban studies
• remote sensing and big data supported urban simulation
• urban vibrancy
• multispectral, hyperspectral, and social sensing applications in urban studies

• Remote Sensing Application in Sustainable Urban Planning and Environmental Services in the Big Data Era in Remote Sensing (8 articles)