Most Viewed

This study provides a comprehensive review of the efforts utilized in the measurement of water quality parameters (WQPs) with a focus on total dissolved solids (TDS) and total suspended solids (TSS). The current method used in the measurement of TDS...

Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for revolutionizing data analysis and applications in many domains of Earth sciences. This review paper synthesizes the existing literature on AI applicatio...

Automatic identification and mapping of tree species is an essential task in forestry and conservation. However, applications that can geolocate individual trees and identify their species in heterogeneous forests on a large scale are lacking. Here,...

In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success...

The theoretical development of Schumann Resonances has spanned more than a century as a form of global natural electromagnetic resonances. In recent years, with the development of electromagnetic detection technology and the improvement in digital pr...

The continuous increase in the volume of geospatial data has led to the creation of storage tools and the cloud to process data. Google Earth Engine (GEE) is a cloud-based platform that facilitates geoprocessing, making it a tool of great interest to...

Drones, also known as unmanned aerial vehicles (UAVs), have gained numerous applications due to their low cost, ease of use, vertical takeover and landing, and ability to operate in high-risk or hard-to-reach areas. The contribution of this review is...

Given the large volume of remote sensing images collected daily, automatic object detection and segmentation have been a consistent need in Earth observation (EO). However, objects of interest vary in shape, size, appearance, and reflecting propertie...

The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community. With its conceptual roots in navigation and mapping, S...

In recent years, major natural disasters and public safety accidents have frequently occurred worldwide. In order to deal with various disasters and accidents using rapidly deployable, reliable, efficient, and stable emergency communication networks,...

Floods are among the most severe and impacting natural disasters. Their occurrence rate and intensity have been significantly increasing worldwide in the last years due to climate change and urbanization, bringing unprecedented effects on human lives...

Change detection is an essential and widely utilized task in remote sensing that aims to detect and analyze changes occurring in the same geographical area over time, which has broad applications in urban development, agricultural surveys, and land c...

This paper presents a critical analysis of image-based 3D reconstruction using neural radiance fields (NeRFs), with a focus on quantitative comparisons with respect to traditional photogrammetry. The aim is, therefore, to objectively evaluate the str...

Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms, sensors and software, UAVs have gained popularity among precision agriculture researchers and stakeholders for estimating traits such as crop yield and diseases. Ear...

The rapid development of uncrewed aerial vehicles (UAVs) has significantly increased their usefulness in various fields, particularly in remote sensing. This paper provides a comprehensive review of UAV path planning, obstacle detection, and avoidanc...

Autonomous unmanned aerial vehicles (UAVs) have several advantages in various fields, including disaster relief, aerial photography and videography, mapping and surveying, farming, as well as defense and public usage. However, there is a growing prob...

With the rapid development of object detection technology for unmanned aerial vehicles (UAVs), it is convenient to collect data from UAV aerial photographs. They have a wide range of applications in several fields, such as monitoring, geological expl...

The rapid development of unmanned aerial vehicle (UAV) technology has contributed to the increasing sophistication of UAV-based object-detection systems, which are now extensively utilized in civilian and military sectors. However, object detection f...

During the past decades, multiple remote sensing data sources, including nighttime light images, high spatial resolution multispectral satellite images, unmanned drone images, and hyperspectral images, among many others, have provided fresh opportuni...

This study provides an overview of the techniques, shortcomings, and strengths of remote sensing (RS) applications in the effective retrieval and monitoring of water quality parameters (WQPs) such as chlorophyll-a concentration, turbidity, total susp...

Metropolitan areas worldwide have grown rapidly and are usually surrounded by peri-urban zones that are neither urban nor rural. Despite widespread use of the term ‘peri-urban’, physical determination of these spaces is difficult due to t...

This systematic literature review (SLR) provides a comprehensive overview of remote sensing (RS) applications in northern peatlands from 2017 to 2022, utilising various platforms, including in situ, UAV, airborne, and satellite technologies. It addre...

In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship detection, with dataset quality as a crucial factor influencing detection accuracy. Datasets...

Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded com...

This study aimed to provide a systematic overview of the progress made in utilizing remote sensing for assessing the impacts of land use and land cover (LULC) changes on water resources (quality and quantity). This review also addresses research gaps...

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. However, the large amount of data also leads to a need for improved automated...

Reliable and timely crop-yield prediction and crop mapping are crucial for food security and decision making in the food industry and in agro-environmental management. The global coverage, rich spectral and spatial information and repetitive nature o...

Plants emit biogenic volatile organic compounds (BVOCs), such as isoprene, significantly influencing atmospheric chemistry and climate. BVOC emissions estimated from bottom-up (BU) approaches (derived from numerical simulations) usually exhibit dense...

Radar automatic target recognition (RATR) technology is fundamental but complicated system engineering that combines sensor, target, environment, and signal processing technology, etc. It plays a significant role in improving the level and capabiliti...

A novel method was developed based on the amplitude data of the EM waves measured by Digisondes to calculate and investigate the relative ionospheric absorption changes. The effect of 13 solar flares (>C8) that occurred from 4 to 10 September 2017...

Continuous and dense time series of satellite remote sensing data are needed for several land monitoring applications, including vegetation phenology, in-season crop assessments, and improving land use and land cover classification. Supporting such a...

Three-dimensional reconstruction is a key technology employed to represent virtual reality in the real world, which is valuable in computer vision. Large-scale 3D models have broad application prospects in the fields of smart cities, navigation, virt...

The surface of the Moon and planets have been covered with loose soil called regolith, and there is a risk that the rovers may stack, so it is necessary for them to recognize the traveling state such as its posture, slip behavior, and sinkage. There...

Geophysical surveys, a means of analyzing the Earth and its environments, have traditionally relied on ground-based methodologies. However, up-to-date approaches encompass remote sensing (RS) techniques, employing both spaceborne and airborne platfor...

Cracks are a common defect in civil infrastructures, and their occurrence is often closely related to structural loading conditions, material properties, design and construction, and other factors. Therefore, detecting and analyzing cracks in civil i...

This paper explores and discusses the revolutionary applications of digital twin technology in space environments and its profound impact on future space exploration activities. Originating from a proposal by the National Aeronautics and Space Admini...

Remote sensing technology is vital for precision agriculture, aiding in early issue detection, resource management, and environmentally friendly practices. Recent advances in remote sensing technology and data processing have propelled unmanned aeria...

Accurate detection and quantification of regional vegetation trends are essential for understanding the dynamics of landscape ecology and vegetation distribution. We applied a comprehensive trend analysis to satellite data to describe geospatial chan...

Remote sensing image scene classification with deep learning (DL) is a rapidly growing field that has gained significant attention in the past few years. While previous review papers in this domain have been confined to 2020, an up-to-date review to...

Remote sensing images provide a valuable way to observe the Earth’s surface and identify objects from a satellite or airborne perspective. Researchers can gain a more comprehensive understanding of the Earth’s surface by using a variety o...

The rapid growth of urban populations and the need for sustainable urban planning and development has made Unmanned Aerial Vehicles (UAVs) a valuable tool for data collection, mapping, and monitoring. This article reviews the applications of UAV tech...

In this paper, we delve into the innovative application of large language models (LLMs) and their extension, large vision-language models (LVLMs), in the field of remote sensing (RS) image analysis. We particularly emphasize their multi-tasking poten...

This article offers a comprehensive AI-centric review of deep learning in exploring landslides with remote-sensing techniques, breaking new ground beyond traditional methodologies. We categorize deep learning tasks into five key frameworks—clas...

Traditional methods for detecting plant diseases and pests are time-consuming, labor-intensive, and require specialized skills and resources, making them insufficient to meet the demands of modern agricultural development. To address these challenges...

Climate change has led to an increase in global temperature and frequent intense precipitation, resulting in a rise in severe and intense urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion...

The integration of optical and SAR datasets through ensemble machine learning models shows promising results in urban remote sensing applications. The integration of multi-sensor datasets enhances the accuracy of information extraction. This research...

With the accelerated development of artificial intelligence, remote-sensing image technologies have gained widespread attention in smart cities. In recent years, remote sensing object detection research has focused on detecting and counting small den...

Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in image processing, signal recognition, and object detection, has facilitated s...

Accurately monitoring aboveground biomass (AGB) and tree mortality is crucial for understanding forest health and carbon dynamics. LiDAR (Light Detection and Ranging) has emerged as a powerful tool for capturing forest structure across different spat...

Remote sensing (RS) and Geographic Information Systems (GISs) provide significant opportunities for monitoring and managing natural resources across various temporal, spectral, and spatial resolutions. There is a critical need for natural resource ma...