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Special Issue "Innovative Remote Sensing for Monitoring and Assessment of Natural Resources"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 November 2019).
Interests: LiDAR; Geomatics; Natural Resources; Natural Hazard; Risk
Special Issues and Collections in MDPI journals
Special Issue in Remote Sensing: Point Cloud Processing in Remote Sensing
Interests: remote sensing, natural resources, Ecological Monitoring, hyperspectral
It is well known that natural resources in our planet are under constant pressure, mainly from anthropic-related threats. Causes are varied and numerous: over-exploitation, non-sustainable land-use, climate change, soil and water salinity, just to name a few. Earth observation (EO) via remote sensing is a well-established technique for monitoring and quantifying these phenomena, and for this reason has been the focus of intense efforts for research and development. In the last years innovative technologies in the realm of EO opened new possibilities for investigators. New platforms have been, and still are, sent into orbit, enriching the availability and diversity of data, which are provided with commercial or open channels. New sensors are being engineered and sent to market, providing new challenges related to data that are provided e.g. structure, size and format. Single photon-counting technology in laser scanning is a representative of many examples. New solutions also for data processing and analysis have opened new frontiers; e.g. simultaneous localization and mapping (SLAM) for unstructured point cloud data, and machine/deep learning for data interpretation
Adequate monitoring and assessment of the condition of natural resources remains a prerequisite for supporting environmental decisions and for tracking effects over time. This special issue aims to summarize the latest progress in techniques and algorithms developed for monitoring and assessment of natural resources. Authors are invited to contribute to this special Issue of Remote Sensing by submitting an original manuscript. Contributions may focus on, but are not limited to:
- new and improved algorithms for data processing and information extraction related to natural resources;
- application of multi-sensor and multi-scale approaches;
- multi-temporal analysis of imagery to define trends over time;
- effects of land-cover changes on natural resources - e.g. urbanization, desertification;
- close-range sensing applications, e.g. from remotely piloted aircraft systems;
- quantification of risk and hazard related to natural resources;
- new possibilities available from new sensors and platforms;
Prof. Francesco Pirotti
Dr. Mitsunori Yoshimura
Dr. Baoxin Hu
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 1800 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.
- Natural resources
- Laser scanning / LiDAR
- Hyperspectral Imagery Analysis
- Multi-scale and multi-source remote sensing
- Spatiotemporal analysis