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Topic Review
Satellite Altimetry for Ocean and Coastal Applications
More than 30 years of observations from an international suite of satellite altimeter missions continue to provide key data enabling research discoveries and a broad spectrum of operational and user-driven applications. These missions were designed to advance technologies and to answer scientific questions about ocean circulation, ocean heat content, and the impact of climate change on these Earth systems. They are also a valuable resource for the operational needs of oceanographic and weather forecasting agencies that provide information to shipping and fishing vessels and offshore operations for route optimization and safety, as well as for other decision makers in coastal, water resources, and disaster management fields. This time series of precise measurements of ocean surface topography (OST)—the “hills and valleys” of the ocean surface—reveals changes in ocean dynamic topography, tracks sea level variations at global to regional scales, and provides key information about ocean trends reflecting climate change in our warming world. Advancing technologies in new satellite systems allows measurements at higher spatial resolution ever closer to coastlines, where the impacts of storms, waves, and sea level rise on coastal communities and infrastructure are manifest. 
  • 652
  • 24 Aug 2023
Topic Review
Single-Image Super-Resolution Techniques
The purpose of multisource map super-resolution is to reconstruct high-resolution maps based on low-resolution maps, which is valuable for content-based map tasks such as map recognition and classification. However, there is no specific super-resolution method for maps, and the existing image super-resolution methods often suffer from missing details when reconstructing maps.
  • 651
  • 10 Jul 2023
Topic Review
A Lightweight Remote Sensing Aircraft Object Detection Network
Remote sensing aircraft object detection is crucial in various applications. In civil aviation and the aerospace industry, it helps identify other aircraft, drones, or obstacles around an aircraft to prevent collisions and enhance aviation safety. It also aids in the real-time monitoring and tracking of civil aviation flights, cargo planes, and private aircrafts to ensure their flight path and status.
  • 646
  • 13 Mar 2024
Topic Review
MSGFNet for Remote Sensing Image Change Detection
Change detection (CD) stands out as a pivotal yet challenging task in the interpretation of remote sensing images. Significant developments have been witnessed, particularly with the rapid advancements in deep learning techniques. Nevertheless, challenges such as incomplete detection targets and unsmooth boundaries remain as most CD methods suffer from ineffective feature fusion.
  • 642
  • 08 Feb 2024
Topic Review
Aircraft Based on Regional Scene Perception
Scene matching plays a vital role in the visual positioning of aircraft. The position and orientation of aircraft can be determined by comparing acquired real-time imagery with reference imagery. To enhance precise scene matching during flight, it is imperative to conduct a comprehensive analysis of the reference imagery’s matchability beforehand. Conventional approaches to image matchability analysis rely heavily on features that are manually designed.
  • 632
  • 17 Oct 2023
Topic Review
Detection Principles of Mars Orbital Radars
The planet Mars, which is in the habitable zone of the solar system and is one of the closest planets to Earth, stands in contrast to Venus; therefore, it has attracted much attention and exploration as the most likely planet for future human colonization. 
  • 632
  • 07 Feb 2024
Topic Review
Methods for Remote Sensing Image Clouds
Remote sensing images are very vulnerable to cloud interference during the imaging process. Cloud occlusion, especially thick cloud occlusion, significantly reduces the imaging quality of remote sensing images, which in turn affects a variety of subsequent tasks using the remote sensing images.
  • 631
  • 24 Nov 2023
Topic Review
The Implementation of Water Framework Directive in Europe
The development of a sustainable water quality monitoring system at national scale remains a big challenge until today, acting as a hindrance for the efficient implementation of the Water Framework Directive (WFD).
  • 617
  • 04 May 2023
Topic Review
PVTv2 for Deep Hash Remote Sensing Image Retrieval
For high-resolution remote sensing image retrieval tasks, single-scale features cannot fully express the complexity of the image information. Due to the large volume of remote sensing images, retrieval requires extensive memory and time. Researchers propose an end-to-end deep hash remote sensing image retrieval model (PVTA_MSF) by fusing multi-scale features based on the Pyramid Vision Transformer network (PVTv2).
  • 610
  • 16 Oct 2023
Topic Review
Requirement on Mapping High-Resolution Urban Impervious Surfaces
Urban impervious surface (UIS) refers to a land surface paved with impervious or low permeability materials within the urban development boundary. UIS generally consists of materials such as tile, impervious asphalt, and impervious concrete. It typically includes buildings, structures, impervious roads, plazas, parking lots, etc. UIS is a key parameter in climate change, environmental change, and sustainability. High-resolution impervious surface mapping is a long-term need. There is an urgent requirement for impervious surface mapping from high-resolution remote sensing imagery. High-resolution images can capture details and spatial relationships among different objects, gradually becoming an important data source for fine-grained urban impervious surface extraction.
  • 608
  • 23 May 2023
Topic Review
Merits and Challenges in Geographic-Information-Systems and Remote-Sensing Application
Geographic Information Systems (GIS) and remote sensing (RS) have evolved into distinct disciplines within geospatial technology, each with well-established theoretical foundations and methodologies. They now encompass various methodologies and software tools(ArcGIS Pro, GRASS GIS, QGIS, ENVI, ERDAS Imagine etc.), expanding their applications in spatial data collection, measurement, analysis, storage, management, display, dissemination, and deployment. GIS has moved beyond just creating digital maps. It has evolved into a comprehensive framework for integrating, storing, analyzing, and presenting geospatial data. RS involves observational and investigative activities in the environmental realm. By continuously monitoring the surface environment, GIS and RS integrate temporal and spatial dimensions, enhancing our understanding of the natural world and the human–nature relationship. This understanding is crucial for recognizing, managing, and preserving archaeological and cultural heritage (ACH).
  • 590
  • 05 Jan 2024
Topic Review
Autonomous Navigation Framework for Holonomic Mobile Robots
Due to the accelerated growth of the world’s population, food security and sustainable agricultural practices have become essential. The incorporation of Artificial Intelligence (AI)-enabled robotic systems in cultivation, especially in greenhouse environments, represents a promising solution, where the utilization of the confined infrastructure improves the efficacy and accuracy of numerous agricultural duties.
  • 563
  • 13 Nov 2023
Topic Review
Tectonic Geodesy Synthesis of the North Aegean Region
Satellite geodesy, an indispensable modern tool for determining upper-crust deformation, can be used to assess tectonically active structures and improve our understanding of the geotectonic evolution in tectonically active regions. A region fulfilling these criteria is the North Aegean, part of the Eastern Mediterranean. It is one of the most tectonically, and hence, seismically, active regions worldwide, which makes it ideal for applying a satellite geodesy investigation. 
  • 549
  • 11 Sep 2023
Topic Review
Remote Sensing Image Feature Learning Approaches
Deep learning approaches are gaining popularity in image feature analysis and in attaining state-of-the-art performances in scene classification of remote sensing imagery. There is an increase of remote sensing datasets with diverse scene semantics; this renders computer vision methods challenging to characterize the scene images for accurate scene classification effectively.
  • 533
  • 21 Jun 2023
Topic Review
Deep Learning for Land Use
Image super-resolution (SR) techniques can improve the spatial resolution of remote sensing images to provide more feature details and information, which is important for a wide range of remote sensing applications, including land use/cover classification (LUCC). Convolutional neural networks (CNNs) have achieved impressive results in the field of image SR, but the inherent localization of convolution limits the performance of CNN-based SR models. 
  • 463
  • 24 Nov 2023
Topic Review
Semi-Supervised Learning for Forest Cover Mapping
Forest cover mapping is of paramount importance for environmental monitoring, biodiversity assessment, and forest resource management. In the realm of forest cover mapping, significant advancements have been made by leveraging fully supervised semantic segmentation models. However, the process of acquiring a substantial quantity of pixel-level labelled data is prone to time-consuming and labour-intensive procedures. 
  • 438
  • 28 Sep 2023
Topic Review
Early Crop Mapping Using Dynamic Ecoregion Clustering
Mapping target crops earlier than the harvest period is an essential task for improving agricultural productivity and decision-making. Early crop mapping provides valuable information for crop management, such as predicting yield, monitoring crop growth, and identifying areas with high production potential.
  • 435
  • 10 Nov 2023
Topic Review
Flood Segmentation in Post-Disaster High Resolution Aerial Images
Floods are the most frequent natural disasters, occurring almost every year around the globe. To mitigate the damage caused by a flood, it is important to timely assess the magnitude of the damage and efficiently conduct rescue operations, deploy security personnel and allocate resources to the affected areas. To efficiently respond to the natural disaster, it is very crucial to swiftly obtain accurate information, which is hard to obtain during a post-flood crisis. Generally, high resolution satellite images are predominantly used to obtain post-disaster information. Deep learning models have achieved superior performance in extracting high-level semantic information from satellite images. 
  • 408
  • 11 Oct 2023
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