Special Issue "Computer Vision and Machine Learning Application on Earth Observation"
Deadline for manuscript submissions: 31 December 2021.
With the rapid development of computing, the interest, power, and advantages of automatic computer-aided processing techniques in science and engineering have become clear—in particular, automatic computer vision (CV) techniques together with machine learning (ML, a.k.a. computational intelligence or machine intelligence) systems, in order to reach both a very high degree of automation and high accuracy. CV in conjunction with ML may be applied to a high number of problems of interest, such as in remote Earth sensing, mainly through different nature remote imaging and remote video processing approaches that have been made possible due to the very rapid development and growth of high-resolution, high-SNR, and low-cost imaging sensors and devices of various types, including single or multiple sensor, visible-range CCD/CMOS, hyper-spectral, multi-spectral, infrared, ultraviolet, and thermal, to name a few.
At the same time, it is clear how the use of autonomous ML systems—including expert systems, neural networks, and genetic algorithms, among others—has recently seen very rapid development, allowing computer-aided diagnosis, automatic classification, pattern recognition, and regression using ML techniques and learning algorithms with either supervised or unsupervised learning and reinforcement or deep learning paradigms.
Given the reasons above, the application of CV and ML to remote Earth observation and sensing is becoming highly attractive and popular, making it possible to reach a very high degree of autonomous functioning, accuracy, and promising results, including the following applications among others of interest:
- Aerial imaging systems;
- Agriculture field and aquaculture open-air automatic image classification systems;
- Air traffic, airways, and plane pathways observation;
- Climate and atmospheric/tropospheric observation, prediction, classification, and sensing systems;
- Crops, crop yield, vegetation, and forest remote imaging sensing systems;
- Deep-space star sensing;
- Earth-surface remote sensing;
- Earth-surface traffic, street, road and highway detection, classification, and sensing systems;
- Ecology, eco-systems, wild life and migratory remote observation and monitoring;
- Electrical power lines and power supply system remote imaging;
- Fire detection and monitoring systems;
- Hybrid automatic sensing systems;
- Hyper-spectral imaging remote sensing systems;
- Maritime/ship traffic observation, classification, or estimation;
- Multi-sensor array remote sensing systems;
- Multi-spectral automatic remote imaging systems;
- Navigation, GPS, and other Earth-surface geodesic and localization systems;
- Open-air orchard/vineyard imaging sensing;
- Population, people, and crowd remote imaging estimation or counting;
- Railway traffic lines remote observation;
- Satellite Earth observation;
- Storm, cloud, rainfall, and water diffraction sensing;
- Time-lapse and seasonal Earth observation;
- UAV/drone imaging systems;
- Water, river, lake, sea, and flooding remote observation and monitoring.
Dr. Juan Ignacio Arribas
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 papers will be 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 2400 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.
- computer vision
- detection and estimation
- expert systems
- learning systems
- machine learning
- neural networks
- pattern recognition
- receiver operating characteristic
- remote sensing applications
- video processing