Aims & Scope

The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.

Special Issue on UAV Remote Sensing Monitoring and Applications
Submission Date: 2025-04-30

Unmanned Aerial Vehicle (UAV) provides a cost-effective solution for high-frequency, high-resolution, and on-
demand data collection. This affordability allows for more frequent monitoring, which is crucial for tracking dynamic
changes in the environment or emergency situations. The exceptional capabilities of UAV remote sensing in Earth
observation enable its applications across a broad spectrum of monitoring and analytical tasks, encompassing
environmental monitoring, ecological assessment, urban planning, smart agriculture, and disaster management. And
the integration of UAV remote sensing with cutting-edge technologies such as information geography, artificial
intelligence, and big data analytics has significantly enhanced the efficiency and accuracy of data processing and
interpretation. This synergy enables more sophisticated and nuanced analysis of remote sensing data, leading to more
informed decision-making.

This Special Issue intends to highlight the methods and solutions of applying UAV remote sensing data and processing
techniques to gather accurate geometry, physical properties, and evolutionary processes of Earth’s surface targets.
Intelligent imagery processing, application and monitoring technology for UAV remote sensing are encouraged.
Quantitative inversion theories, algorithms, architectures, and applications using UAV remote sensing data, including
RGB, multispectral, and hyperspectral images, LiDAR are welcome.

The broad topics include (but are not limited to):
 UAV remote sensing dataset;
 UAV remote sensing data synthesis, mosaic;
 Cross modal UAV data registration, assimilate;
 UAV remote sensing imagery enhancement (image fusion, feature extraction, noise reduction, shadow removal, defect repair, etc.);
 Object detection and semantic analysis based on UAV remote sensing data;
 3D target reconstruction based on UAV remote sensing technology;
 Analysis of surface morphology changes;
 Theories and methods of quantitative inversion using UAV remote sensing;
 Advancements in quantitative remote sensing inversion based on UAV data;
 Monitoring natural resources and disasters with UAV remote sensing;
 Applications of UAV remote sensing in precision agriculture, urban environments, lakes and oceans.

Schedule
Aug 1, 2024, Submission system opening
Apr 30, 2025, Submission system closing

Format
All submissions will be peer reviewed according to the IEEE Geoscience and Remote Sensing Society guidelines.
Submitted articles should not have been published or be under review elsewhere. Submit your manuscript on
http://mc.manuscriptcentral.com/jstars, using the Manuscript Central interface and select the “UAV Remote Sensing
Monitoring and Applications” special issue manuscript type. Prospective authors should consult the site
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9082768 for guidelines and information on paper
submission. All submissions must be formatted using the IEEE standard format (double column, single spaced). Please
visit http://www.ieee.org/publications_standards/publications/authors/author_templates.html to download a template
for transactions. Please note that since Jan. 1, 2024, IEEE J-STARS, as a fully open-access journal, is charging a flat
publication fee $1,496 per paper.

Guest Editors
Dr. Qingwang Wang Kunming University of Science and Technology, Kunming, China (wangqingwang@kust.edu.cn)
Dr. Zhen Zhang Kunming University of Science and Technology, Kunming, China (zhangzhen@kust.edu.cn)
Dr. Wenguan Wang Zhejiang University, Hangzhou, China (wenguanwang@zju.edu.cn)
Dr. Nan Su Harbin Engineering University, Harbin, China (sunan08@hrbeu.edu.cn)
Dr. Junshi Xia Geoinformatics Team, RIKEN Center, Tokyo, Japan (junshi.xia@riken.jp)

Special Issue on Intelligent Sensing and Navigation Technologies for 6G
Submission Date: 2025-06-30

Sensing stands as a foundational capability to address the diverse requirements of forthcoming 6G application scenarios,
enabling the detection and recognition of environmental data. Modern Remote Sensing (RS) technologies offer broad
observation ranges, swift speeds, and short period, finding widespread utility in agriculture, environmental monitoring,
disaster prevention, mapping, urban construction, and management. Their deployment significantly enhances human
productivity and quality of life. As communication and sensing technologies advance, the concept of Integrated Sensing
and Communication (ISAC) has garnered attention, promising improvements in system spectrum efficiency, hardware
utilization, and information processing efficiency while seamlessly blending sensing and communication functionalities.
Navigation Sensing (NS) technology also plays a crucial role in this landscape. Moreover, to meet the demands of diverse
future application scenarios, there's a growing concept of integrating communication, navigation, and remote sensing. In
recent years, Artificial Intelligence (AI) has undergone continuous evolution, reaching the realm of perceptual intelligence.
Leveraging AI in sensing scenarios holds the promise of substantially enhancing sensing capabilities and recognition
accuracy. This special issue seeks contributions from researchers, practitioners, and scholars in relevant fields to showcase
their research findings, delving into the current research landscape of 6G-assisted intelligent sensing technologies.

The broad topics include (but are not limited to):
 RS/NS information recognition based on lightweight deep learning models
 AI assisted/enhanced NS/RS technology
 Basic theoretical performance limitations of ISAC in 6G
 Performance analysis/optimization of Space-Air-Ground-Sea Integrated Networks supported by ISAC
 The ISAC and RS/NS with state-of-the-art wireless technologies (e.g., RIS，ambient backscatter, massive MIMO, mmWave/THz, privacy/security, NOMA, covert communication, etc.)
 Positioning, timing, and navigation of ISAC
 Centralized/distributed machine learning of ISAC and RS/NS
 ISAC and RS/NS system based on spectrum sharing
 Transfer learning and domain adaptation techniques for improving RS/NS sensing performance
 AI platforms, frameworks, and systems used to support sensing
 Development of a test bench for ISAC and RS/NS coexistence experiments

Schedule
October 1, 2024, Submission system opening
June 30, 2025, Submission system closing

Format
All submissions will be peer reviewed according to the IEEE Geoscience and Remote Sensing Society guidelines.
Submitted articles should not have been published or be under review elsewhere. Submit your manuscript on
http://mc.manuscriptcentral.com/jstars, using the Manuscript Central interface and select the “Intelligent Sensing and
Recognition Technologies for Remote Sensing” special issue manuscript type. Prospective authors should consult
the site https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9082768 for guidelines and information on paper
submission. All submissions must be formatted using the IEEE standard format (double column, single spaced). Please
visit http://www.ieee.org/publications_standards/publications/authors/author_templates.html to download a template
for transactions. Please note that since Jan. 1, 2024, IEEE J-STARS, as a fully open-access journal, is charging a flat
publication fee $1,496 per paper.

Guest Editors
Xingwang Li Henan Polytechnic University, China (lixingwang@hpu.edu.cn)
Arumugam Nallanathan Queen Mary University of London, UK. (a.nallanathan@qmul.ac.uk)
Shuanggen Jin Henan Polytechnic University, China (sgjin@hpu.edu.cn)
Derrick Wing Kwan Ng University of New South Wales, Australia (w.k.ng@unsw.edu.au)
Zhiyong Feng Beijing University of Post & Telecommunication, China (fengzy@bupt.edu.cn)
Chau Yuen Nanyang Technological University, Singapore (chau.yuen@ntu.edu.sg)

Special Issue on Enhancing Remote Sensing of Coastal Areas through Multi-Sensor Data Fusion
Submission Date: 2025-06-30

The rapid advancement of remote sensing technology has led to the emergence of very high-resolution (VHR) imaging
sensors and other technologies deployed on both visible and spaceborne vehicles. Additionally, one of the most
popular methods, remote sensing data fusion, combines data from sensors installed on satellites, airliners, and
popularity structures with varying geographic and frequency objectives to create fused data that becomes more
specific than data collected from all the sensors separately. Coastal areas are remarkably relevant to humankind,
serving as vital hubs for progress in society and the economy. Multiple sensors must be used since a single sensor or
survey cannot accurately capture a component's whole set of attributes. Numerous applications may be found for the
commercial internet of things. For this reason, handling multi-sensor fusion data is crucial. A particular combination,
or the integration of data, can create more. The Multi-Sensor Data Fusion aspects all emphasize the necessity of
creating novel data analysis techniques that can manage remote sensing data, supporting the use of integrated and
sustainable systems. Throughout the field of remote sensing analysis, characteristic partitioning is among the most
applicable methods for data pretreatment. In order to increase the effectiveness of smart image analyzing techniques
and make it easier for specialists to comprehend and apply the collected remote sensing intelligence, its primary
objective is to constantly convert visual features into isolated ones. The analysis makes use of the Special Issue on
Remote Sensing of the Coastal Area to emphasize recent developments in the field's understanding of the coastal area's
remote sensing and to establish several development goals for the area. Multi-sensor data fusion techniques were
developed from several fields, such as neural networks, analytical forecasting, recognizing trends, and others. An
introduction to data fusion applications, process diagrams, and the identification of relevant methodologies are all
covered in this instructional section.

Papers are invited that consider, but are not limited to, the following themes:

The broad topics include (but are not limited to):
 An evaluation of effective uses for spacecraft remote sensing in coastal areas
 Analysis of spectrum and landcover projection with multi-sensor data fusion methods
 Geomorphological and ecological vulnerability indicator modelling using multi-sensor data fusion
 Coastal area recognition using a combination of information and multi-sensor data
 Understanding eddy-induced the rise in the southern coastal area using remote sensing
 Multi-sensor data fusion for resource transfer and hydrology prediction of parameters
 Utilizing multi-sensor fusion methods for coastal mangrove ecosystem remote sensing
 Integration of multi-sensor features for high-spatial location extraction in transitory developments
 Land-surface temporal recovery using multi-sensor fusion at high geographical improvements
 Coastal area tracking using a multi-sensor setting: a method for developing

Schedule
01 Oct 2024 Submission system opening
30 Jun 2025 Submission system closing

Format
All submissions will be peer reviewed according to the IEEE Geoscience and Remote Sensing Society guidelines.
Submitted articles should not have been published or be under review elsewhere. Submit your manuscript on
http://mc.manuscriptcentral.com/jstars, using the Manuscript Central interface and select the “Enhancing Remote
Sensing of Coastal Areas through Multi-Sensor Data Fusion” special issue manuscript type. Prospective authors
should consult the site https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9082768 for guidelines and
information on paper submission. All submissions must be formatted using the IEEE standard format (double column,
single spaced). Please visit http://www.ieee.org/publications_standards/publications/authors/author_templates.html to
download a template for transactions. Please note that since Jan. 1, 2024, IEEE J-STARS, as a fully open-access
journal, is charging a flat publication fee $1,496 per paper.

Guest Editors
Alireza Sharifi Shahid Rajaee Teacher Training University, Iran (a_sharifi@sru.ac.ir)
Hadi Mahdipour University of Oviedo, Spain (mahdipourhadi@uniovi.es)
Khilola Amankulova University of Szeged, Szeged, Hungary (amankulova.khilola@stud.u-szeged.hu)