Satellite Image Processing and Applications

Dear Colleagues,

Satellite remote sensing data has been rapidly used from a wide range of sensors and plays an important roles in earth surface material monitoring. Most of the optical satellite sensors provide multispectral bands and finer spatial resolution for panchromatic band. Landsat-8 and Sentinel2A/B data are among freely available satellite data. Landsat-8 Operational Land Imager (OLI) was launched on 2013 and has been improved compared with Landsat-7 Enhanced Thematic Mapper (ETM+) in calibration, signal to noise ratio, radiometric resolution and spectral wavebands. European Space Agency (ESA) launched Sentinel-2A and Sentinel-2B satellite sensors on 2015 and 2017, respectively; providing multispectral imagery in 13 spectral bands at different spatial resolutions (10 to 60 m). The commercially available very-high-resolution (VHR) sensors such as IKONOS, QuickBird, GeoEye-1, WorldView-2/3 and many other VHR satellites have contributed to finer/detailed characterization of earth surface features. Moreover, SAR imagery are also available from different sources such as Cosmo-Skymed, Sentinel-1 and TerraSAR-X, etc.

In consequence, the advancement in sensor technology and image processing algorithms enable the potential to develop novel methodologies and improve upon traditional processing methods in terms of cost, quantitative and qualitative accuracy, and objectivity. Satellite image processing may include wide spectrum of applications including imagery classification, multi-temporal image classification, multi-sensor data fusion, characterization of earth ecosystem processes and environmental monitoring, etc.

The goal of this special issue is to collect latest developments, methodologies and applications of satellite image data for remote sensing. We welcome submissions which provide the community with the most recent advancements on all aspects of satellite remote sensing processing and applications, including but not limited to:

• Data fusion and integration of multi-sensor data
• Image segmentation and classification algorithms
• Feature selection algorithms
• Machine learning techniques
• Geographic Object-Based Image Analysis
• Deep learning
• Change detection and multi-temporal analysis
• Urban mapping
• Vegetation and species detection within complex environment
• Impervious surface detection
• Natural hazard assessment

Dr. Alireza Hamedianfar
Prof. Petri Pellikka
Assoc. Prof. Dr. Helmi Shafri
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.