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A review on deep learning in UAV remote sensing
Osco, Lucas Prado, Marcato Junior, José, Marques Ramos, Ana Paula, de Castro Jorge, Lúcio André, Fatholahi, Sarah Narges, de Andrade Silva, Jonathan, Matsubara, Edson Takashi, Pistori, Hemerson, Gonçalves, Wesley Nunes, Li, Jonathan
Published in International journal of applied earth observation and geoinformation (01.10.2021)
Published in International journal of applied earth observation and geoinformation (01.10.2021)
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The Segment Anything Model (SAM) for remote sensing applications: From zero to one shot
Osco, Lucas Prado, Wu, Qiusheng, de Lemos, Eduardo Lopes, Gonçalves, Wesley Nunes, Ramos, Ana Paula Marques, Li, Jonathan, Marcato, José
Published in International journal of applied earth observation and geoinformation (01.11.2023)
Published in International journal of applied earth observation and geoinformation (01.11.2023)
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Object detection from UAV thermal infrared images and videos using YOLO models
Jiang, Chenchen, Ren, Huazhong, Ye, Xin, Zhu, Jinshun, Zeng, Hui, Nan, Yang, Sun, Min, Ren, Xiang, Huo, Hongtao
Published in International journal of applied earth observation and geoinformation (01.08.2022)
Published in International journal of applied earth observation and geoinformation (01.08.2022)
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The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil
Silva Rotta, Luiz Henrique, Alcântara, Enner, Park, Edward, Negri, Rogério Galante, Lin, Yunung Nina, Bernardo, Nariane, Mendes, Tatiana Sussel Gonçalves, Souza Filho, Carlos Roberto
Published in International journal of applied earth observation and geoinformation (01.08.2020)
Published in International journal of applied earth observation and geoinformation (01.08.2020)
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MCANet: A joint semantic segmentation framework of optical and SAR images for land use classification
Li, Xue, Zhang, Guo, Cui, Hao, Hou, Shasha, Wang, Shunyao, Li, Xin, Chen, Yujia, Li, Zhijiang, Zhang, Li
Published in International journal of applied earth observation and geoinformation (01.02.2022)
Published in International journal of applied earth observation and geoinformation (01.02.2022)
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High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques
Li, Shuang, Xu, Liang, Jing, Yinghong, Yin, Hang, Li, Xinghua, Guan, Xiaobin
Published in International journal of applied earth observation and geoinformation (25.12.2021)
Published in International journal of applied earth observation and geoinformation (25.12.2021)
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Integrating remote sensing and geospatial big data for urban land use mapping: A review
Yin, Jiadi, Dong, Jinwei, Hamm, Nicholas A.S., Li, Zhichao, Wang, Jianghao, Xing, Hanfa, Fu, Ping
Published in International journal of applied earth observation and geoinformation (01.12.2021)
Published in International journal of applied earth observation and geoinformation (01.12.2021)
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Identifying core driving factors of urban land use change from global land cover products and POI data using the random forest method
Wu, Hao, Lin, Anqi, Xing, Xudong, Song, Danxia, Li, Yan
Published in International journal of applied earth observation and geoinformation (01.12.2021)
Published in International journal of applied earth observation and geoinformation (01.12.2021)
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High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data
Li, Wang, Niu, Zheng, Shang, Rong, Qin, Yuchu, Wang, Li, Chen, Hanyue
Published in International journal of applied earth observation and geoinformation (01.10.2020)
Published in International journal of applied earth observation and geoinformation (01.10.2020)
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A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability
Chakraborty, T., Lee, X.
Published in International journal of applied earth observation and geoinformation (01.02.2019)
Published in International journal of applied earth observation and geoinformation (01.02.2019)
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Ten deep learning techniques to address small data problems with remote sensing
Safonova, Anastasiia, Ghazaryan, Gohar, Stiller, Stefan, Main-Knorn, Magdalena, Nendel, Claas, Ryo, Masahiro
Published in International journal of applied earth observation and geoinformation (01.12.2023)
Published in International journal of applied earth observation and geoinformation (01.12.2023)
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Digital twin of a city: Review of technology serving city needs
Lehtola, Ville V., Koeva, Mila, Elberink, Sander Oude, Raposo, Paulo, Virtanen, Juho-Pekka, Vahdatikhaki, Faridaddin, Borsci, Simone
Published in International journal of applied earth observation and geoinformation (01.11.2022)
Published in International journal of applied earth observation and geoinformation (01.11.2022)
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ADS-Net:An Attention-Based deeply supervised network for remote sensing image change detection
Wang, Decheng, Chen, Xiangning, Jiang, Mingyong, Du, Shuhan, Xu, Bijie, Wang, Junda
Published in International journal of applied earth observation and geoinformation (01.09.2021)
Published in International journal of applied earth observation and geoinformation (01.09.2021)
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Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley
Bendig, Juliane, Yu, Kang, Aasen, Helge, Bolten, Andreas, Bennertz, Simon, Broscheit, Janis, Gnyp, Martin L., Bareth, Georg
Published in International journal of applied earth observation and geoinformation (01.07.2015)
Published in International journal of applied earth observation and geoinformation (01.07.2015)
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Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
Berger, Katja, Verrelst, Jochem, Féret, Jean-Baptiste, Hank, Tobias, Wocher, Matthias, Mauser, Wolfram, Camps-Valls, Gustau
Published in International journal of applied earth observation and geoinformation (01.10.2020)
Published in International journal of applied earth observation and geoinformation (01.10.2020)
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