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Topic Review
Application of UAV Photogrammetry in Mining Areas
The geological environmental damage caused by coal mining has become a hot issue in current research. Especially in the western mining area, the size of the mining working face is large, the mining intensity is high, while the surface movement and deformation are more intense and wider. Therefore, it is necessary to effectively monitor the surface using appropriate means and carrying out research on the overlying strata structure of the stope.
  • 774
  • 03 Jul 2023
Topic Review
Deep Learning Methods for Smoke Recognition
Fire accidents cause alarming damage. They result in the loss of human lives, damage to property, and significant financial losses. Early fire ignition detection systems, particularly smoke detection systems, play a crucial role in enabling effective firefighting efforts. In this paper, a novel DL (Deep Learning) method, namely BoucaNet, is introduced for recognizing smoke on satellite images while addressing the associated challenging limitations. BoucaNet combines the strengths of the deep CNN EfficientNet v2 and the vision transformer EfficientFormer v2 for identifying smoke, cloud, haze, dust, land, and seaside classes. Extensive results demonstrate that BoucaNet achieved high performances. BoucaNet also showed a robust ability to overcome challenges, including complex backgrounds; detecting small smoke zones; handling varying smoke features such as size, shape, and color; and handling visual similarities between smoke, clouds, dust, and haze.
  • 757
  • 21 Dec 2023
Topic Review
Remote Sensing for Lithology Mapping in Vegetation-Covered Regions
Accurate lithological mapping is essential in geological surveys and mineral resource exploration. Remote sensing (RS) technology has significantly contributed to geological exploration and mineral resource assessment. Various approaches have been identified to address vegetation obstruction in lithological RS.
  • 747
  • 08 Sep 2023
Topic Review
Define–Investigate–Estimate–Map (DIEM) Framework for Modeling Habitat Threats
The DIEM framework illustrates a method of defining threats on the basis of the derived definition, investigating an area using available spatial data, estimating threat severity using the principles used in existing equations, and mapping threats using spatial analysis methods.
  • 746
  • 20 Dec 2021
Topic Review
Applications of Multispectral Light Detection and Ranging Technology
Light Detection and Ranging (LiDAR) is a well-established active technology for the direct acquisition of 3D data. In recent years, the geometric information collected by LiDAR sensors has been widely combined with optical images to provide supplementary spectral information to achieve more precise results in diverse remote sensing applications. The emergence of active Multispectral LiDAR (MSL) systems, which operate on different wavelengths, has recently been revolutionizing the simultaneous acquisition of height and intensity information.
  • 733
  • 18 Apr 2024
Topic Review
SAR RFI Suppression Method Based on FuSINet
Synthetic Aperture Radar (SAR) is a high-resolution imaging sensor commonly mounted on platforms such as airplanes and satellites for widespread use. In complex electromagnetic environments, radio frequency interference (RFI) severely degrades the quality of SAR images due to its widely varying bandwidth and numerous unknown emission sources. Although traditional deep learning-based methods have achieved remarkable results by directly processing SAR images as visual ones, there is still considerable room for improvement in their performance due to the wide coverage and high intensity of RFI.
  • 728
  • 01 Apr 2024
Topic Review
The Methods Applied in Geo-Registration
In augmented reality applications, geo-registration refers to the process of aligning and matching virtual objects with the geographic location and orientation of the real-world scene. Currently, there are three common methods for pose estimation: sensor-based approaches, vision-based approaches, and hybrid approaches. These methods have been extensively applied in numerous projects and research endeavors.
  • 715
  • 08 Aug 2023
Topic Review
Low-Cost Computer-Vision-Based Embedded Systems for Unmanned Aerial Vehicles
Unmanned Aerial Vehicles (UAVs) are versatile, adapting hardware and software for research. They are vital for remote monitoring, especially in challenging settings such as volcano observation with limited access. In response, economical computer vision systems provide a remedy by processing data, boosting UAV autonomy, and assisting in maneuvering. Through the application of these technologies, researchers can effectively monitor remote areas, thus improving surveillance capabilities. Moreover, flight controllers employ onboard tools to gather data, further enhancing UAV navigation during surveillance tasks. 
  • 715
  • 14 Nov 2023
Topic Review
BCD Datasets and SSL in Remote Sensing CD
The detection of building changes (hereafter ‘building change detection’, BCD) is a critical issue in remote sensing analysis. Accurate BCD faces challenges, such as complex scenes, radiometric differences between bi-temporal images, and a shortage of labelled samples. Traditional supervised deep learning requires abundant labelled data, which is expensive to obtain for BCD. By contrast, there is ample unlabelled remote sensing imagery available. Self-supervised learning (SSL) offers a solution, allowing learning from unlabelled data without explicit labels. Inspired by self-supervised learning (SSL), researchers employed the SimSiam algorithm to acquire domain-specific knowledge from remote sensing data. Then, these well-initialised weight parameters were transferred to BCD tasks, achieving optimal accuracy. A novel framework for BCD was developed using self-supervised contrastive pre-training and historical geographic information system (GIS) vector maps (HGVMs). 
  • 714
  • 21 Dec 2023
Topic Review
Rise in Mid-Tropospheric Temperature Trend over the Tibet
The Hindu Kush-Himalayan region (HKH), situated at high altitudes (~5 km above sea level), and the adjoining Indo-Gangetic plains (IG plains, ~0–250 m above sea level) are notably responsive to climatic shifts due to their geographic location and intricate topography. Ongoing research reveals that climate change's consequences and linked alterations in water resources—comprising glacial/snow meltwater and rainfall—hold diverse impacts on ecosystems, agriculture, industries, and inhabitants within this area. This investigation delved into a 45-year span of data (1978–2022) derived from Microwave Sounding Unit/Advanced Microwave Sounding Unit (MSU/AMSU) instruments provided by Remote Sensing Systems (RSS Version 4.0). The goal was to scrutinize changes in mid-tropospheric temperature (TMT, 3–7 km altitude) and lower tropospheric temperature (TLT, 0–3 km altitude) concerning annual/monthly trends and anomalies. A noteworthy rise in mid-tropospheric temperatures (0–3 km altitude) across the HKH region, with increases of 1.49 °K in Tibet, 1.30 °K in the western Himalayas, and 1.35 °K in the eastern Himalayas over the 45-year timeframe. By contrast with an earlier 30-year period study (1979–2008), the present study observed a substantial percentage change of TMT trends for the high-altitude areas, including Tibet, the western Himalayas, and the eastern Himalayas—approximately 310%, 80%, and 170%, respectively. Conversely, the neighboring plains (western and eastern IG plains) exhibited negligible or considerably lower percent alterations (0% and 40%, respectively) over the past 14 years.
  • 707
  • 21 Aug 2023
Topic Review
Building Damage Identification Methods and Transfer Learning Methods
The building damage caused by natural disasters seriously threatens human security. Applying deep learning algorithms to identify collapsed buildings from remote sensing images is crucial for rapid post-disaster emergency response.
  • 707
  • 04 Sep 2023
Topic Review
Quantum Dilated Convolutional Neural Network
Road network extraction is a significant challenge in remote sensing (RS). Automated techniques for interpreting RS imagery offer a cost-effective solution for obtaining road network data quickly, surpassing traditional visual interpretation methods.
  • 702
  • 21 Nov 2023
Topic Review
Urban Flood Monitoring Technology
Owing to rapid climate change, large-scale floods have occurred yearly in cities worldwide, causing serious damage. General flooding and overflow modeling was performed based on a model that utilizes the flow of water and its geographical characteristics. More detailed geographical data and drainage network information are utilized in urban regions.
  • 702
  • 27 Nov 2023
Topic Review
The Existing Remote Sensing Index Resources
Remote sensing indices are widely used in various fields of geoscience research. However, there are limits to how effectively the knowledge of indices can be managed or analyzed. One of the main problems is the lack of ontology models and research on indices, which makes it difficult to acquire and update knowledge in this area. 
  • 700
  • 18 Feb 2024
Topic Review
Muddy Waters Mapping Using Machine Learning
The quality of drinking water is a critical factor for public health and the environment. Inland drinking water reservoirs are essential sources of freshwater supply for many communities around the world. However, these reservoirs are susceptible to various forms of contamination, including the presence of muddy water, which can pose significant challenges for water treatment facilities and lead to serious health risks for consumers. In addition, such reservoirs are also used for recreational purposes which supports the local economy. 
  • 689
  • 12 Oct 2023
Topic Review
Validation of Aerosol Optical Depth and Characterization
The validation of aerosol optical depth and its characterization describes how important the use of multiple instrument in the study of aerosols. The content of this work highlights recent results in the use of satellite, ground-based and modeling method to study aerosols. 
  • 686
  • 25 Jul 2023
Topic Review
Drone Photogrammetry for Underwater Cutural Heritage Documentation
Underwater cultural heritage (UCH) is an irreplaceable resource with intrinsic value that requires preservation, documentation, and safeguarding. Documentation is fundamental to increasing UCH resilience, providing a basis for monitoring, conservation, and management. Advanced UCH documentation and virtualization technologies are increasingly important for dissemination and visualization purposes, domain expert study, replica reproduction, degradation monitoring, and all other outcomes after a metric survey of cultural heritage (CH). Among the different metric documentation techniques, underwater photogrammetry is the most widely used for UCH documentation. It is a non-destructive and relatively inexpensive method that can produce high-resolution 3D models and 2D orthomosaics of underwater sites and artifacts. However, underwater photogrammetry is challenged by the different optical properties of water, light penetration, visibility and suspension, radiometric issues, and environmental drawbacks that make underwater documentation difficult. 
  • 684
  • 11 Mar 2024
Topic Review
Cloud-Based Remote Sensing for Wetland Monitoring
The rapid expansion of remote sensing provides recent and developed advances in monitoring wetlands. Integrating cloud computing with these techniques has been identified as an effective tool, especially for dealing with heterogeneous datasets.
  • 681
  • 29 Mar 2023
Topic Review
DCNN in Remote Sensing Domain
The use of deep learning methods to extract buildings from remote sensing images is a key contemporary research focus, and traditional deep convolutional networks continue to exhibit limitations in this regard. 
  • 674
  • 14 Dec 2023
Topic Review
A Sub-Second Method for SAR Image Registration
For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks.
  • 661
  • 24 Oct 2023
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