Innovative UAV and Satellite Technologies and Applications for Spatiotemporal Analysis

Dear Colleagues,

Remote sensing from UAVs to spaceborne sensors offers a unique opportunity to measure, analyze, quantify, map, and explore spatiotemporal phenomena at high temporal frequencies. By leveraging these technologies, researchers gain unprecedented insights into the dynamic changes occurring in coastal areas and other environments, facilitating better monitoring, management, and conservation efforts.

This Special Issue aims to collect innovative and high-quality research articles related to current trends and challenges in the field of UAV and satellite mapping for Dynamic Environmental Monitoring. The integration of UAV and satellite technologies with GIS and GeoAI has opened new avenues for the mapping, analysis, and assessment of environmental spatiotemporal phenomena. We invite contributions that explore the latest advancements, methodologies, and applications in this dynamic field.

In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following:

• Monitoring and mapping changes;
• UAV and satellite imagery within GIS are used for emergency planning and recovery;
• UAV and satellite-based GIS applications for environmental monitoring;
• The mapping and quantification of emerging environmental phenomena;
• The use of geo AI for mapping spatial relationships and patterns;
• Machine learning techniques for analyzing spatiotemporal data from UAVs and satellites;
• Machine learning strategies for environmental monitoring and analyzing ecosystem dynamics;
• Fusion techniques for UAV and satellite data;
• The assessment of emerged phenomena using UAS remote sensing;
• Techniques for monitoring environmental changes using UAV and satellite data;
• Rapid assessment and response strategies for natural disasters;
• Damage assessment in coastal areas using remote sensing;
• UAV and remote sensing applications in archeology;
• Temporal analysis of land use and land cover changes using UAV, satellite, and GIS technologies;
• Decision making using remote sensing in coastal environments;
• Applications in forest management, water resource monitoring, and pollution tracking.

These topics cover various applications and innovations at the intersection of UAV, satellite technologies, GeoAI, and GIS in mapping dynamic environmental phenomena, providing a comprehensive scope for research articles and systematic literature reviews on any of the aforementioned topics.

Dr. Apostolos Papakonstantinou
Prof. Eufemia Tarantino
Dr. Alessandra Capolupo
Dr. Athos Agapiou
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.

• UAV and satellite mapping
• spatiotemporal phenomena
• geospatial technologies
• geospatial artificial intelligence (GeoAI)
• aerial and satellite remote sensing
• environmental change detection
• multi-source data integration
• high-resolution imagery
• machine learning in geodata
• natural disaster assessment

Title: Predicting rate of banjhi shoot, yield, total nitrogen and NDF content during the first and second tea seasons using UAV multispectral data
Authors: So Furuya1)2), Kazuya Hasegawa3), Toshikazu Suzuki4), Tetsuya Oishi5), Yuto Tuchiya6) and Chinatsu Yonezawa2)
Affiliation: 1) Shizuoka Prefecture Fuji Agriculture and Forestry Office, 2)Tohoku University Graduate school of Agricultural Science 3) Tea Research Center, Shizuoka Prefectural Research Institute of Agriculture and Forestry 4) Shizuoka Professional University of Agriculture, 5), 6) Shizuoka Prefecture Shida-haibara Agriculture and Forestry Office
Abstract: To efficiently produce high-quality green tea, it is necessary to accurately grasp the growth status of tea fields and appropriately determine the harvest time. In this study, we will examine a labor-saving method of estimating important parameters for determining the harvest time using UAV-mounted multispectral data. In this study, observations were made using a UAV-mounted multispectral sensor during the first and second tea seasons from 2021 to 2023, and actual measurement data on rate of banjhi shoot, yield, total nitrogen, and NDF content were measured. Six vegetation indices, NDVI, SAVI, MTVI2, GNDVI, NDRE, and GRVI, were calculated from the observation data, and estimation models were created for rate of banjhi shoot, yield, total nitrogen, and NDF content by regression analysis, and the estimation accuracy was verified. As a result, it was revealed that the estimation accuracy of SAVI was superior for the first tea season and MTVI2 for the second tea season.

Title: Recent morphological evolution of Stromboli volcano: a UAS-based high-spatiotemporal resolution approach
Authors: Tullio Ricci, Riccardo Civico, Massimo Cantarero, Emanuela De Beni, Piergiorgio Scarlato
Affiliation: Istituto Nazionale di Geofisica e Vulcanologia, Italy
Abstract: Crater terrace and Sciara del Fuoco collapse events at Stromboli volcano during periods of ordinary Strombolian activity did not present a significant threat until 2019. On 3 July and 28 August 2019, two paroxysmal eruptions abruptly changed the morphology of the entire crater terrace, weakening its rim and facilitating the accumulation of loose pyroclastic debris on the Sciara del Fuoco, leading to subsequent collapses. A further eruption occurred in July 2024, again profoundly shaping the morphology of the study sector. The use of more than 20 UAS photogrammetric surveys, conducted with high-spatiotemporal resolution between May 2022 and July 2024, allowed us to investigate the morphological evolution of the Sciara del Fuoco and of the summit area following effusive and paroxysmal eruptions, major explosions, and mass wasting events.