Mukesh Kumar Verma^1,2,*, Manohar Yadav¹

Revue Internationale de Géomatique, Vol.34, pp. 855-879, 2025, DOI:10.32604/rig.2025.069914 - 17 November 2025

Abstract Precision Agriculture (PA) is revolutionizing modern farming by leveraging remote sensing (RS) technologies for continuous, non-destructive crop monitoring. This review comprehensively explores RS systems categorized by platform—terrestrial, airborne, and space-borne—and evaluates the role of multi-sensor fusion in addressing the spatial and temporal complexity of agricultural environments. Emphasis is placed on data from LiDAR, GNSS, cameras, and radar, alongside derived metrics such as plant height, projected leaf area, and biomass. The study also highlights the significance of data processing methods, particularly machine learning (ML) and deep learning (DL), in extracting actionable insights from large datasets. By More >

Ahmad S. Azzahrani^*

Energy Engineering, Vol.122, No.11, pp. 4703-4713, 2025, DOI:10.32604/ee.2025.067398 - 27 October 2025

Abstract The Light Detection and Ranging (LiDAR) data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media. In the context of renewable energy, particularly wind energy, LiDAR is increasingly utilized to analyze wind flow, turbine wake effects, and turbulence in complex terrains. This study focuses on advancing LiDAR data interpretation through the development and application of the LiDAR Statistical Barnes Objective Analysis (LiSBOA) method. LiSBOA enhances the capacity of scanning LiDAR systems by enabling more precise optimization of scan configurations and improving the retrieval… More >

Irfan Abbas, Robertas Damaševičius^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 483-502, 2025, DOI:10.32604/cmc.2025.066578 - 29 August 2025

Abstract Forests are vital ecosystems that play a crucial role in sustaining life on Earth and supporting human well-being. Traditional forest mapping and monitoring methods are often costly and limited in scope, necessitating the adoption of advanced, automated approaches for improved forest conservation and management. This study explores the application of deep learning-based object detection techniques for individual tree detection in RGB satellite imagery. A dataset of 3157 images was collected and divided into training (2528), validation (495), and testing (134) sets. To enhance model robustness and generalization, data augmentation was applied to the training part… More >

Kelvin Kang Wee Tang^1,*, Muhammad Hafiz Mohd Yatim¹, Norhadija Darwin², Wan Anom Wan Aris¹, Sim Ching Yen³, Nurfazira Mohamed Fadil³

Revue Internationale de Géomatique, Vol.34, pp. 587-602, 2025, DOI:10.32604/rig.2025.065583 - 06 August 2025

Abstract The integration of Unmanned Aerial Vehicles (UAVs) and Uncrewed Surface Vehicles (USVs) has revolutionized topographic and bathymetric mapping, significantly enhancing the accuracy and efficiency of geospatial data acquisition processes. This innovative approach synergistically combines terrestrial data collected by UAVs with underwater data obtained through USVs, culminating in the creation of unified high-resolution Digital Elevation Models (DEMs) of the river basin region represents a vital step toward understanding the dynamic interactions between land and water bodies. Hence, the seamless Topo-Bathymetric Elevation Model offers a detailed perspective of the river system, supporting informed decision-making in addressing sediment… More >

Francisco J. Soler Mora^1,*, Adrián Peidró Vidal¹, Marc Fabregat-Jaén¹, Luis Payá Castelló^1,2, Óscar Reinoso García ^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3167-3195, 2025, DOI:10.32604/cmes.2025.064510 - 30 June 2025

Abstract Reticular structures are the basis of major infrastructure projects, including bridges, electrical pylons and airports. However, inspecting and maintaining these structures is both expensive and hazardous, traditionally requiring human involvement. While some research has been conducted in this field of study, most efforts focus on faults identification through images or the design of robotic platforms, often neglecting the autonomous navigation of robots through the structure. This study addresses this limitation by proposing methods to detect navigable surfaces in truss structures, thereby enhancing the autonomous capabilities of climbing robots to navigate through these environments. The paper… More >

Yuxin Yan, Huirui Wang, Jingyi Wen, Zerong Lan, Liang Wang^*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3059-3073, 2025, DOI:10.32604/cmc.2024.057949 - 16 April 2025

Abstract The development of artificial intelligence (AI) technologies creates a great chance for the iteration of railway monitoring. This paper proposes a comprehensive method for railway utility pole detection. The framework of this paper on railway systems consists of two parts: point cloud preprocessing and railway utility pole detection. This method overcomes the challenges of dynamic environment adaptability, reliance on lighting conditions, sensitivity to weather and environmental conditions, and visual occlusion issues present in 2D images and videos, which utilize mobile LiDAR (Laser Radar) acquisition devices to obtain point cloud data. Due to factors such as… More >

Xu Liu¹, Qiujie Li^1,*, Youlin Xu¹, Musaed Alhussein², Khursheed Aurangzeb^2,*, Fa Zhu¹

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 575-593, 2025, DOI:10.32604/cmc.2025.062445 - 26 March 2025

Abstract The correction of Light Detection and Ranging (LiDAR) intensity data is of great significance for enhancing its application value. However, traditional intensity correction methods based on Terrestrial Laser Scanning (TLS) technology rely on manual site setup to collect intensity training data at different distances and incidence angles, which is noisy and limited in sample quantity, restricting the improvement of model accuracy. To overcome this limitation, this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning (MLS) technology. The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point… More >

Afaq Khattak^1,*, Pak-wai Chan², Feng Chen³, Abdulrazak H. Almaliki⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1565-1584, 2025, DOI:10.32604/cmes.2025.059914 - 27 January 2025

Abstract Intense wind shear (I-WS) near airport runways presents a critical challenge to aviation safety, necessitating accurate and timely classification to mitigate risks during takeoff and landing. This study proposes the application of advanced Residual Network (ResNet) architectures including ResNet34 and ResNet50 for classifying I-WS and Non-Intense Wind Shear (NI-WS) events using Doppler Light Detection and Ranging (LiDAR) data from Hong Kong International Airport (HKIA). Unlike conventional models such as feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), ResNet provides a distinct advantage in addressing key challenges such as capturing intricate… More >

Yiqing Lu¹, Liutao Zhao^2,*, Qiankun Zhao³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1401-1416, 2025, DOI:10.32604/cmc.2024.058757 - 03 January 2025

Abstract Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors. These vehicles are crucial in various fields, including environmental science research, ecological and environmental monitoring projects, disaster response, and emergency management. A key method employed in these vehicles for achieving high-precision positioning is LiDAR (lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping (SLAM). However, maintaining high-precision localization in complex scenarios, such as degraded environments or when dynamic objects are present, remains a significant challenge. To address this issue, we integrate both semantic and… More >

Mohamed Rabik Mohamed Ismail¹, Muthuramalingam Thangaraj^1,*, Khaja Moiduddin^2,*, Zeyad Almutairi^2,3, Mustufa Haider Abidi²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4263-4279, 2024, DOI:10.32604/cmc.2024.055271 - 12 September 2024

Abstract The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems, as well as satellites. More recently, unmanned aerial vehicles have also been employed for this purpose. The accurate detection and mapping of a target such as buildings, trees, and terrains are of utmost importance in various applications of unmanned aerial vehicles (UAVs), including search and rescue operations, object transportation, object detection, inspection tasks, and mapping activities. However, the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,… More >