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Muhammad Akhtar, Iqbal Murtza, Muhammad Adnan and Ayesha Saadia
Natural scene classification, which has potential applications in precision agriculture, environmental monitoring, and disaster management, poses significant challenges due to variations in the spatial resolution, spectral resolution, texture, and size o...
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Chengzhe Lv, Yuefeng Lu, Miao Lu, Xinyi Feng, Huadan Fan, Changqing Xu and Lei Xu
In object-oriented remote sensing image classification experiments, the dimension of the feature space is often high, leading to the ?dimension disaster?. If a reasonable feature selection method is adopted, the classification efficiency and accuracy of ...
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Jianxin Qin, Wenjie Yang, Tao Wu, Bin He and Longgang Xiang
GPS trajectory and remote sensing data are crucial for updating urban road networks because they contain critical spatial and temporal information. Existing road network updating methods, whether trajectory-based (TB) or image-based (IB), do not integrat...
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Abbas Najmi, Caroline M. Gevaert, Divyani Kohli, Monika Kuffer and Jati Pratomo
Mapping slums is vital for monitoring the Sustainable Development Goal (SDG) indicators. In the absence of reliable data, Remote Sensing (RS)-based approaches, particularly the Deep Learning (DL) methods, have gained recognition and high accuracies for s...
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Kai Zhou, Yan Xie, Zhan Gao, Fang Miao and Lei Zhang
Road semantic segmentation is unique and difficult. Road extraction from remote sensing imagery often produce fragmented road segments leading to road network disconnection due to the occlusion of trees, buildings, shadows, cloud, etc. In this paper, we ...
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Yong Mei, Hao Chen and Shuting Yang
High-resolution remote sensing image building target detection has wide application value in the fields of land planning, geographic monitoring, smart cities and other fields. However, due to the complex background of remote sensing imagery, some detaile...
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Paidamwoyo Mhangara, Willard Mapurisa and Naledzani Mudau
Nanosatellites are increasingly being used in space-related applications to demonstrate and test scientific capability and engineering ingenuity of space-borne instruments and for educational purposes due to their favourable low manufacturing costs, chea...
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Aleksandar Milosavljevic
The proliferation of high-resolution remote sensing sensors and platforms imposes the need for effective analyses and automated processing of high volumes of aerial imagery. The recent advance of artificial intelligence (AI) in the form of deep learning ...
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Haifei Liu, Minhua Yang, Jie Chen, Jialiang Hou and Min Deng
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Rui Guo, Jianbo Liu, Na Li, Shibin Liu, Fu Chen, Bo Cheng, Jianbo Duan, Xinpeng Li and Caihong Ma
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Yang Chen, Rongshuang Fan, Muhammad Bilal, Xiucheng Yang, Jingxue Wang and Wei Li
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Jie Chen, Haifei Liu, Jialiang Hou, Minhua Yang and Min Deng
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Li Chen, Qing Zhu, Xiao Xie, Han Hu and Haowei Zeng
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Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
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Francesco Lodato, Nicola Colonna, Giorgio Pennazza, Salvatore Praticò, Marco Santonico, Luca Vollero and Maurizio Pollino
This study analyzes, through remote sensing techniques and innovative clouding services, the recent land use dynamics in the North-Roman littoral zone, an area where the latest development has witnessed an important reconversion of purely rural areas to ...
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Usman Ali, Travis J. Esau, Aitazaz A. Farooque, Qamar U. Zaman, Farhat Abbas and Mathieu F. Bilodeau
Land use and land cover (LULC) classification maps help understand the state and trends of agricultural production and provide insights for applications in environmental monitoring. One of the major downfalls of the LULC technique is inherently linked to...
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Grayson R. Morgan, Cuizhen Wang, Zhenlong Li, Steven R. Schill and Daniel R. Morgan
Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments, in comparison with the popularly of applied machine le...
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Shayan Salavitabar, S. Samuel Li and Behzad Lak
Rivers play an important role in water supply, waterway transport, and riverine species habitations. The underwater depth of a river channel is a fundamental geometric element and a key input to studies for the aforementioned and other applications. Trad...
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Michaela Doukari, Stelios Katsanevakis, Nikolaos Soulakellis and Konstantinos Topouzelis
Marine conservation and management require detailed and accurate habitat mapping, which is usually produced by collecting data using remote sensing methods. In recent years, unmanned aerial systems (UAS) are used for marine data acquisition, as they prov...
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Andrés Menéndez Blanco, Jesús García Sánchez, José Manuel Costa-García, João Fonte, David González-Álvarez and Víctor Vicente García
Sixty-six new archaeological sites have been discovered thanks to the combined use of different remote sensing techniques and open access geospatial datasets (mainly aerial photography, satellite imagery, and airborne LiDAR). These sites enhance the foot...
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