Suchergebnisse - "IEEE journal of selected topics in applied earth observations and remote sensing"

  1. 1

    Hyper-Sharpening: A First Approach on SIM-GA Data von Selva, Massimo, Aiazzi, Bruno, Butera, Francesco, Chiarantini, Leandro, Baronti, Stefano

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: IEEE 01.06.2015
    “… This paper aims at defining a new paradigm (hypersharpening) in remote sensing image fusion. In fact, due to the development of new instruments, thinking only …”
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  2. 2

    IA-CIOU: An Improved IOU Bounding Box Loss Function for SAR Ship Target Detection Methods von Huang, Pingping, Tian, Shihao, Su, Yun, Tan, Weixian, Dong, Yifan, Xu, Wei

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2024
    “… Ship detection in synthetic aperture radar (SAR) images is crucial in both civilian and military fields, offering extensive application prospects. Nonetheless, …”
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  3. 3

    Quantitative Assessment of Scots Pine (Pinus Sylvestris L.) Whorl Structure in a Forest Environment Using Terrestrial Laser Scanning von Pyorala, Jiri, Liang, Xinlian, Vastaranta, Mikko, Saarinen, Ninni, Kankare, Ville, Wang, Yunsheng, Holopainen, Markus, Hyyppa, Juha

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.10.2018
    “… State-of-the-art technology available at sawmills enables measurements of whorl numbers and the maximum branch diameter for individual logs, but such …”
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  4. 4

    Remotely Sensed Vegetation Green-Up Onset Date on the Tibetan Plateau: Simulations and Future Predictions von Cao, Ruyin, Ling, Xiaofang, Liu, Licong, Wang, Weiyi, Li, Luchun, Shen, Miaogen

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2023
    “… Vegetation green-up onset date (VGD) is a key indicator of ecosystem structure and processes. As the largest and highest alpine ecoregion, the Tibetan plateau …”
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    A Multi-kernel Joint Sparse Graph for SAR Image Segmentation von Gu, Jing, Jiao, Licheng, Yang, Shuyuan, Liu, Fang, Hou, Biao, Zhao, Zhiqiang

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.03.2016
    “… Recently, more and more attention has been drawn on the study of sparse graph-based classification with respect to pattern recognition and computer vision …”
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  7. 7

    Mapping Impervious Cover Using Multi-Temporal MODIS NDVI Data von Knight, Joseph, Voth, Margaret

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.06.2011
    “… Mapping impervious surfaces over regional or continental scale study areas with high spatial resolution imagery is difficult due to the cost and time involved …”
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  8. 8

    Clutter Modeling for Ground-Penetrating Radar Measurements in Heterogeneous Soils von Takahashi, Kazunori, Igel, Jan, Preetz, Holger

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.12.2011
    “… Ground-penetrating radar (GPR) measurement and its interpretation/analysis are challenging when soil is heterogeneous. Soil heterogeneity causes unwanted …”
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  9. 9

    Infrared Remote Sensing of Surf-Zone Eddies von Marmorino, George O., Smith, Geoffrey B., Miller, W. David

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.06.2013
    “… Airborne infrared imagery is used for the first time to investigate characteristics of surf-zone eddies, occurring along an along-shore uniform beach. Eddies …”
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  10. 10

    Sea-Ice Production in Antarctic Coastal Polynyas Estimated From AMSR2 Data and Its Validation Using AMSR-E and SSM/I-SSMIS Data von Nihashi, Sohey, Ohshima, Kay I., Tamura, Takeshi

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.09.2017
    “… Antarctic coastal polynyas are very high sea-ice production areas. The resultant large amount of brine rejection leads to the formation of dense water. The …”
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    Evaluation of Marine Surface Wind Speed Observations From AMSR2 on GCOM-W Satellite von Ebuchi, Naoto

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.09.2017
    “… Observations of marine surface scalar wind speeds from the advanced microwave scanning radiometer 2 (AMSR2), onboard the global change observation …”
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    EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification von Helber, Patrick, Bischke, Benjamin, Dengel, Andreas, Borth, Damian

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.07.2019
    “… In this paper, we present a patch-based land use and land cover classification approach using Sentinel-2 satellite images. The Sentinel-2 satellite images are …”
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    DASNet: Dual Attentive Fully Convolutional Siamese Networks for Change Detection in High-Resolution Satellite Images von Chen, Jie, Yuan, Ziyang, Peng, Jian, Chen, Li, Huang, Haozhe, Zhu, Jiawei, Liu, Yu, Li, Haifeng

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2021
    “… Change detection is a basic task of remote sensing image processing. The research objective is to identify the change information of interest and filter out …”
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  14. 14

    Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities von Cheng, Gong, Xie, Xingxing, Han, Junwei, Guo, Lei, Xia, Gui-Song

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2020
    “… Remote sensing image scene classification, which aims at labeling remote sensing images with a set of semantic categories based on their contents, has broad …”
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    Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review von Amani, Meisam, Ghorbanian, Arsalan, Ahmadi, Seyed Ali, Kakooei, Mohammad, Moghimi, Armin, Mirmazloumi, S. Mohammad, Moghaddam, Sayyed Hamed Alizadeh, Mahdavi, Sahel, Ghahremanloo, Masoud, Parsian, Saeid, Wu, Qiusheng, Brisco, Brian

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2020
    “… Remote sensing (RS) systems have been collecting massive volumes of datasets for decades, managing and analyzing of which are not practical using common …”
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    Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review von Sheykhmousa, Mohammadreza, Mahdianpari, Masoud, Ghanbari, Hamid, Mohammadimanesh, Fariba, Ghamisi, Pedram, Homayouni, Saeid

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2020
    “… Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning …”
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    Progress and Challenges in Intelligent Remote Sensing Satellite Systems von Zhang, Bing, Wu, Yuanfeng, Zhao, Boya, Chanussot, Jocelyn, Hong, Danfeng, Yao, Jing, Gao, Lianru

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2022
    “… Due to advances in remote sensing satellite imaging and image processing technologies and their wide applications, intelligent remote sensing satellites are …”
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    Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects von Ahmad, Muhammad, Shabbir, Sidrah, Roy, Swalpa Kumar, Hong, Danfeng, Wu, Xin, Yao, Jing, Khan, Adil Mehmood, Mazzara, Manuel, Distefano, Salvatore, Chanussot, Jocelyn

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2022
    “… Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained …”
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    A CNN-Transformer Network With Multiscale Context Aggregation for Fine-Grained Cropland Change Detection von Liu, Mengxi, Chai, Zhuoqun, Deng, Haojun, Liu, Rong

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2022
    “… Nonagriculturalization incidents are serious threats to local agricultural ecosystem and global food security. Remote sensing change detection (CD) can provide …”
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    YOLOv5-tassel: Detecting Tassels in RGB UAV Imagery with Improved YOLOv5 Based on Transfer Learning von Liu, Wei, Quijano, Karoll, Crawford, Melba

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 2022
    “… Unmanned Aerial Vehicles (UAVs) equipped with lightweight sensors such as RGB cameras and LiDAR have significant potential in precision agriculture, including …”
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