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Canadian Journal of Remote Sensing最新文献

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Crop Classification Using Multi-Temporal RADARSAT Constellation Mission Compact Polarimetry SAR Data 利用多时雷达卫星星座任务紧凑极化合成孔径雷达数据进行作物分类
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-08-20 DOI: 10.1080/07038992.2024.2384883
Ramin Farhadiani, Saeid Homayouni, Avik Bhattacharya, Masoud Mahdianpari
The RADARSAT Constellation Mission (RCM) Compact Polarimetry (CP) data has become a key asset in crop mapping and monitoring for diverse agricultural landscapes. This study utilizes the unique capa...
雷达卫星星座任务(RCM)的紧凑型测极仪(CP)数据已成为绘制作物分布图和监测各种农业景观的关键资产。这项研究利用了雷达卫星星座任务(RCM)的独特能力。
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引用次数: 0
A Bi-Temporal Airborne Lidar Shrub-to-Tree Aboveground Biomass Model for the Taiga of Western Canada 加拿大西部泰加针叶林双时空激光雷达灌木-树木地上生物量模型
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-08-06 DOI: 10.1080/07038992.2024.2379915
Linda Flade, Chris Hopkinson, Laura Chasmer
Monitoring aboveground biomass (AGB) is critical for carbon reporting and quantifying ecosystem change. AGB from field data can be scaled to the region using airborne lidar. However, lidar-based AG...
监测地上生物量(AGB)对于碳报告和量化生态系统变化至关重要。利用机载激光雷达可将野外数据中的 AGB 按比例放大到区域中。然而,基于激光雷达的 AG...
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引用次数: 0
Estimating GDP by Fusing Nighttime Light and Land Cover Data 通过融合夜间光照和土地覆盖数据估算 GDP
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-31 DOI: 10.1080/07038992.2024.2377641
Nan Xu, Shiyi Zhang, Shuai Jiang
Accurate information on gross domestic product (GDP) is essential for better understanding the dynamics of regional economies and urbanization processes. Satellite based nighttime light datasets ca...
准确的国内生产总值 (GDP) 信息对于更好地了解地区经济和城市化进程的动态至关重要。基于卫星的夜间光照数据集可帮助我们更好地了解城市化进程。
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引用次数: 0
Active Reinforcement Learning for the Semantic Segmentation of Urban Images 城市图像语义分割的主动强化学习
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-30 DOI: 10.1080/07038992.2024.2374788
Mahya Jodeiri Rad, Costas Armenakis
Image segmentation using supervised learning algorithms usually requires large amounts of annotated training data, while urban datasets frequently contain unbalanced classes leading to poor detecti...
使用监督学习算法进行图像分割通常需要大量注释训练数据,而城市数据集经常包含不平衡的类别,导致检测效果不佳。
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引用次数: 0
Enhanced Wheat Head Detection in Images Using Fourier Domain Adaptation and Random Guided Filter 利用傅立叶域自适应和随机引导滤波器增强图像中的麦头检测
IF 2 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-26 DOI: 10.1080/07038992.2024.2367479
Sylvester C. Okafor, Linjing Wei, Solomon Boamah, Le Zhang, Mamadou B. Diallo
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引用次数: 0
Rice Phenology Classification Model Based on Sentinel-1 Using Machine Learning Method on Google Earth Engine 利用谷歌地球引擎上的机器学习方法,建立基于哨兵 1 号的水稻物候分类模型
IF 2 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-17 DOI: 10.1080/07038992.2024.2368036
Hengki Muradi, Dede Dirgahayu Domiri, I. M. Parsa, I. K. Yoga, A. Bustamam, Anisa Rarasati, Sri Harini, R. J. Manalu, M. Subehi
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引用次数: 0
Cumulative Changes in Minimum Snow/Ice Extent over Canada and Northern USA for 2000–2023 2000-2023 年加拿大和美国北部最小积雪/冰雪面积的累积变化
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-08 DOI: 10.1080/07038992.2024.2371359
Alexander P. Trishchenko, Calin Ungureanu
The Minimum Snow/Ice (MSI) extent is an important climate and environmental indicator related to surface hydrology and freshwater resources. Variations in the MSI extent over the four first-order r...
最小积雪/结冰(MSI)范围是与地表水文和淡水资源有关的重要气候和环境指标。最小积雪/结冰范围在四个一阶范围内的变化是由气候和环境因素决定的。
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引用次数: 0
Automated Rooftop Solar Panel Detection Through Convolutional Neural Networks 通过卷积神经网络自动检测屋顶太阳能电池板
IF 2.6 4区 地球科学 Q3 REMOTE SENSING Pub Date : 2024-07-04 DOI: 10.1080/07038992.2024.2363236
Simon Pena Pereira, Azarakhsh Rafiee, Stef Lhermitte
Transforming the global energy sector from fossil-fuel based to renewable energy sources is crucial to limiting global warming and achieving climate neutrality. The decentralized nature of the rene...
将全球能源部门从以化石燃料为基础转变为可再生能源,对于限制全球变暖和实现气候中和至关重要。可再生能源的分散性、可再生性和可持续发展性使其在全球范围内发挥着重要作用。
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引用次数: 0
Changes in Water and Carbon Fluxes in the USA Southern Great Plains Grassland Due to Evergreen Forest Encroachment 常绿森林侵蚀导致美国南部大平原草地水通量和碳通量的变化
IF 2.6 4区 地球科学 Pub Date : 2024-06-14 DOI: 10.1080/07038992.2024.2333976
Xuebin Yang, Xiangming Xiao, Chenchen Zhang, Jorge Celis
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引用次数: 0
Comparison of Deep and Machine Learning Approaches for Quebec Tree Species Classification Using a Combination of Multispectral and LiDAR Data 使用多光谱和激光雷达数据组合进行魁北克树种分类的深度学习和机器学习方法比较
IF 2.6 4区 地球科学 Pub Date : 2024-06-11 DOI: 10.1080/07038992.2024.2359433
Omid Reisi Gahrouei, Jean-François Côté, Philippe Bournival, Philippe Giguère, Martin Béland
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引用次数: 0
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Canadian Journal of Remote Sensing
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