Big Data Analytics for Secure and Smart Environmental Services

Dear Colleagues,

Today, the volume of remote sensing (RS) data has grown considerably, leading to a new research domain, termed big RS data. Analyzing, modeling, and interpreting RS big data through descriptive, predictive, and prescriptive analytics will aid users to make correct decisions in many fields related to RS. On the other hand, the evolution of Internet of Things (IoT) and cybersecurity technologies is continuing to play an important role in developing smart cities of tomorrow.

The growing combination of big data analytics, IoT, and cybersecurity offer the potential to learn and extract knowledge from heterogeneous RS big data collected from different sources, in order to develop real-world environmental services implemented through secure IoT infrastructures.

This timely Special Issue invites submissions on a range of related topics, including, but not limited to, the following:

• Novel machine learning algorithms for big RS data (e.g., deep learning, active learning, reinforcement learning, evolutionary computing, etc.);
• Methods and techniques for collection, cleaning, analyzing, distribution, and visualization of big RS data;
• Unceratinty modeling in IoT and big RS data;
• Cybersecurity methods and techniques to enable secure and privacy-assured IoT Big Data analytics for smart environmental services;
• Infrastructure for IoT applied to big RS data (including cloud and edge computing, high performance computing, emerging hardware architectures, optimization, control, automation, security, etc.);
• Environmental services, such as regional planning, climate forecasting, crowd management, resources management, land use/cover management, urban sprawl planning, water resource management,

Prof. Amir Hussain
Prof. Ahmed Al-Dubai
Prof. Bill Buchanan
Prof. Jonathan Wu
Prof. Kaizhu Huang
Prof. Bin Luo
Prof. Jin Tang
Dr. Wadii Boulila
Prof. Adel M. Alimi
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 250 words) can be sent to the Editorial Office for assessment.

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.