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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.
  • 467
  • 20 Dec 2021
Topic Review
Estimate Soil Organic Carbon from Remote Sensing
Monitoring soil organic carbon (SOC) typically assumes conducting a labor-intensive soil sampling campaign, followed by laboratory testing, which is both expensive and impractical for generating useful, spatially continuous data products. 
  • 462
  • 27 Feb 2024
Topic Review
Optimized Deep Learning Model for Flood Detection
The increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection models, deep learning techniques are extensively used in flood control.
  • 459
  • 27 Oct 2023
Topic Review
Application of Vegetation Indices beyond Vegetation Monitoring
Vegetation indices (VIs) have long been a crucial tool for monitoring plant growth and health, assessing the impact of environmental factors on vegetation, and supporting decision-making processes in agriculture and forestry. Traditionally, these mathematical formulations, leveraging the spectral response of plants to sunlight, have been instrumental in assessing vegetation health. However, emerging research suggests some unconventional applications that extend the scope of VIs.
  • 458
  • 08 Aug 2023
Topic Review
Geomatic Sensors for Heritage Documentation
Geomatic technologies have been widely populated for cultural heritage applications, while the scientific field is quite broad: from underwater to close-range to low-altitude and satellite observations. Geomatic sensors have been used in applications such as close-range approaches with red-green-blue (RGB) cameras and Terrestrial Laser Scanners (TLS), as well as underwater studies. Low-altitude sensors on Unmanned Aerial Vehicles (UAVs) have also been widely used with RGB and multispectral cameras, as well as lidar and thermal sensors.
  • 458
  • 25 Oct 2023
Topic Review
Remote Sensing in Water Quality Parameters Monitoring
Remote sensing (RS) applications offer the opportunity for decisionmakers to quantify and monitor water quality parameters (WQPs) on a spatiotemporal scale effectively. The use of RS for water quality monitoring has been explored in many studies using empirical, analytical, semi-empirical, and machine-learning algorithms. RS spectral signatures have been applied for the estimation of WQPs using two categories of RS, namely, microwave and optical sensors. Optical RS, which has been heavily applied in the estimation of WQPs, is further grouped as spaceborne and airborne sensors based on the platform they are on board. The choice of a particular sensor to be used in any RS application depends on various factors including cost, and spatial, spectral, and temporal resolutions of the images.
  • 444
  • 19 Apr 2023
Topic Review
Remote Sensing in Wind Erosion Studies
Remote sensing (RS) has revolutionized field data collection processes and provided timely and spatially consistent acquisition of data on the terrestrial landscape properties. The study of wind erosion involves a range of research techniques, such as laboratory and field measurements, modelling, and the use of remote sensing (RS) technologies.
  • 433
  • 22 Aug 2023
Topic Review
Lava Tubes' Radar Observation on Moon and Mars
Lava tubes are tunnel–like structures within lava flows and can vary in diameter, length, and shape. Due to the Moon and Mars both having low–gravity environments, the lava tubes on these celestial bodies can have volumes that are 1–3 orders of magnitude larger than those found on Earth.
  • 426
  • 08 Jun 2023
Topic Review
Supervised Deep-Learning Models for Multispectral Change Detection
Remote sensing is a tool of interest for a large variety of applications. It is becoming increasingly more useful with the growing amount of available remote sensing data. The large amount of data also leads to a need for improved automated analysis. Deep learning is a natural candidate for solving this need. Change detection in remote sensing is a rapidly evolving area of interest that is relevant for a number of fields. There are a large number of publications and progress, even though the challenge is far from solved. Multispectral images are common in remote sensing and well suited for change detection purposes thanks to their good balance of spatial and spectral resolution, capturing important details. Various data sets for change detection have been openly published online and a growing number of models has been introduced in the literature, both supervised, unsupervised and semi-supervised. 
  • 422
  • 05 May 2023
Topic Review
Contrastive Learning for Hyperspectral Image Classification
Despite the rapid development of deep learning in hyperspectral image classification (HSIC), most models require a large amount of labeled data, which are both time-consuming and laborious to obtain. However, contrastive learning can extract spatial–spectral features from samples without labels, which helps to solve the above problem. 
  • 404
  • 02 Aug 2023
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.
  • 404
  • 08 Aug 2023
Topic Review
Machine Learning in Land Use Change Detection
Land use change detection (LUCD) is a critical technology with applications in various fields, including forest disturbance, cropland changes, and urban expansion.
  • 403
  • 24 May 2023
Topic Review
Mapping and Monitoring Informal Settlements Using RS Technologies
Research on the detection of informal settlements has increased since 1990s owing to the availability of high- to very-high-spatial-resolution satellite imagery. The achievement of development goals, such as the Sustainable Development Goals, requires access to up-to-date information on informal settlements.
  • 393
  • 27 Sep 2023
Topic Review
Deep Learning-Based Weed Detection Using UAV Images
Deep learning-based weed detection using UAV images. Recently, the Unmanned Aerial Vehicle (UAV) has made significant progress in its design and capability, including payload flexibility, communication and connectivity, navigation and autonomy, speed and flight time, which has potential to revolutionize the precision agriculture.
  • 388
  • 13 Oct 2023
Topic Review
Methods for Measuring Landslides
Landslides are among the most destructive geo-disasters, causing substantial property damage and safety problems worldwide. Defined as the gravitational movement of mass down a slope, they can result from various events such as severe precipitation, earthquakes, volcanic activity, and human activities.
  • 388
  • 19 Jan 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.
  • 384
  • 01 Apr 2024
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.
  • 379
  • 24 Oct 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.
  • 376
  • 08 Sep 2023
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.
  • 372
  • 29 Mar 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.
  • 371
  • 13 Mar 2024
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