Algorithm Development in Earth Observation Modeling Using Multi-sensor Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 15 November 2024 | Viewed by 172
Special Issue Editors
Interests: mapping; topography; algorithms; earthquakes; observation; SAR; tectonics; satellite; radar; remote sensing
Interests: InSAR; GPS; surface displacements; earthquake; numerical modeling, natural and anthropogenic crustal deformation processes
Special Issue Information
Dear Colleagues,
Our planet’s dynamic nature, exemplified by shifting tectonic plates and the resulting seismic activity, necessitates advanced, comprehensive monitoring systems. The discipline of remote sensing stands at the forefront in this regard, providing a powerful toolkit to track, interpret, and predict these changes. Sophisticated algorithms lie at the core of these tools which transform multisensor data into invaluable insights into the Earth’s geomorphological processes.
This Special Issue titled “Algorithm Development in Earth Observation Modeling Using Multi-sensor Data” focuses on the evolution and significance of these algorithms, especially as they apply to understanding active tectonic and volcanic geomorphology processes. This Special Issue will delve into the use of radar remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR), which are essential for mitigating natural hazards, and optical remote sensing involving multispectral and hyperspectral sensors, which are vital for environmental monitoring and land-use changes.
As we grapple with escalating environmental concerns and an unprecedented influx of data from various satellite systems, this research field has become indispensable. It invites contributions exploring both short-term and long-term deformations that inform the geomorphology and tectonic processes across various tectonic regimes worldwide. With a broad scope covering major geological hazards like earthquakes, volcanoes, landslides, and debris flows, we welcome studies that harness multisource data integration tools, such as satellite remote sensing, InSAR, high-resolution drone airborne optical images, remote spectral datasets, and LiDAR. Through fostering algorithmic advancements in remote sensing, we aim to better equip ourselves to understand and respond to our rapidly changing planet.
Dr. Sanaz Vajedian
Dr. Rishabh Dutta
Dr. Indhu Varatharajan
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.
Keywords
- remote sensing
- multisensor data
- earth observation modeling
- satellite data
- algorithm development
- radar remote sensing
- InSAR
- tectonic geomorphology
- optical remote sensing
- multispectral sensors
- hyperspectral sensors
- seismic activity
- geological hazards
- multisource data integration
- LiDAR
