Remote Sensing and Geospatial Analysis in the Big Data Era

Dear Colleagues,

Remote sensing techniques revolutionized our ability to observe and understand the Earth’s surface and processes. With advancements in technology, remote sensing has become a crucial tool for collecting enormous amounts of geospatial data. In the era of Big Data, the availability of massive datasets presents both challenges and opportunities for geospatial analysis and their practical applications. By employing advanced algorithms, statistical techniques, and spatial modeling, geospatial analysis provides valuable information about complex spatial patterns, relationships, and processes. It enables the identification of land cover changes, monitoring of environmental conditions, assessment of natural hazards, and planning of urban infrastructure, among many other applications. This allows researchers to address critical environmental and societal challenges.

The aim of this Special Issue is to explore the advancements, challenges, and opportunities in exploiting the potential of geospatial Big Data. The objective is to present research that addresses scientific and technical aspects of processing a large amount and variety of geospatial datasets collected by remote sensing (and other) sensors. This Special Issue aims to showcase innovative methodologies, algorithms, and applications that effectively handle and analyze geospatial data in order to better understand and tackle complex societal and environmental challenges. This special issue aligns closely with the scope of the Remote Sensing journal by focusing on aspects associated with the geospatial analysis of remote sensing data.

We invite articles focusing on the advancement and integration of techniques applied for the analysis and interpretation of geospatial data acquired by remote sensing sensors. This involves studies dealing with data processing strategies, data management, machine learning, data fusion, and their applications in environmental monitoring, urban planning, disaster response, and other applications. The space will be given also for studies that focus on a combination and fusion of geospatial data acquired by terrestrial and remote sensing sensors.

Dr. Robert Tenzer
Dr. Hok Sum Fok
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.

• remote sensing
• geospatial analysis
• Big Data
• machine learning
• data fusion and integration
• spatial modeling
• advanced algorithms