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A Novel Efficient Method for Land Cover Classification in Fragmented Agricultural Landscapes Using Sentinel Satellite Imagery

Xinyi Li, Chen Sun, Huimin Meng, Xin Ma et al. • Remote Sensing (2022)

Updated and accurate land cover maps are essential and crucial for sustainable crop production and efficient land management. However, accurate and efficient land cover mapping is still a challenge for agricultural regions with complicated ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14092045

Thoracic electrical impedance tomography identifies heterogeneity in lungs associated with respiratory disease in cattle. A pilot study

Olivia Brabant, Yuliya V. Karpievitch, Yuliya V. Karpievitch, Alphons Gwatimba et al. • Frontiers in Veterinary Science (2024)

Respiratory disease in cattle is a significant global concern, yet current diagnostic methods are limited, and there is a lack of crush-side tests for detecting active disease. To address this gap, we propose utilizing electrical impedance ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fvets.2023.1275013

Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Txomin Hermosilla • ELCVIA Electronic Letters on Computer Vision and Image Analysis (2014)

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

DOAJ Open Access (DOAJ) DOI: 10.5565/rev/elcvia.584

SPAF-SegNeXt: Prior-Guided Attention and Frequency-Spatial Hybrid Fusion for Multimodal Sugarcane Segmentation in Remote Sensing

Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2026)

Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2026.3716367

A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method

Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing (2022)

Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14081877