Earth Science
Paper Review Records
All Paper Review Records
15 valid samples · Newest publication first
Review days = acceptance date − received date. PDF, DOI, and publisher-page sources are retained.
A simple method for large-scale realistic mountain forest scenes reconstruction using visible stereoscopic imagery combined with unmanned aerial vehicle laser scanning data
AuthorsXiaohan Lin; Ainong Li; Jinhu Bian; Guangbin Lei; Zhengjian Zhang; Xi Nan; Limin Chen; Yi Deng
Affiliations1. Research Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences; 2. College of Resources and Environment, University of Chinese Academy of Sciences; 3. Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province
Dynamics of artificial aquaculture ponds in China from 2015 to 2025
AuthorsYao Chen; Xiuyuan Zhang; Shushi Peng; Haoyu Wang; Lubin Bai; Shuping Xiong; Mei Li; Shihong Du
Affiliations1. College of Urban and Environmental Sciences, Peking University; 2. Institute of Remote Sensing and GIS, Peking University
A vision-language model-driven spatiotemporal alignment framework for mitigating cross-sensor inconsistencies in real-world remote sensing image super-resolution
AuthorsYujie Mao; Guojin He; Guizhou Wang; Ranyu Yin; Ziying Chen; Bin Guan; Hongxuan Zhang; Shihao An
Affiliations1. Aerospace Information Research Institute, Chinese Academy of Sciences; 2. University of Chinese Academy of Sciences; 3. Kashgar Aerospace Information Research Institute; 4. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences; 5. School of Remote Sensing and Information Engineering, Wuhan University
Built-up index and fractal dimension clustering of multispectral satellite urban images
AuthorsArmando Delgadillo-Jimenez; Carina Toxqui-Quitl; Aldo Aguilar-Vallejo; Alfonso Padilla-Vivanco; Anna Carbone
Affiliations1. Computer Vision Laboratory, Universidad Politécnica de Tulancingo, Ingeniería; 2. Department of Applied Science and Technology (DISAT), Politecnico di Torino, Corso Duca degli Abruzzi
Global mapping of vegetation solar-induced chlorophyll fluorescence over 1981−2023 with a light-use-efficiency constrained machine-learning approach
AuthorsChaoya Dang; Yuli Yan; Qingwei Zhuang; Zhenfeng Shao; Ya Zhang; Mousong Wu; Jiaxin Qian; Gui Cheng; Yanfeng Ding; Songhan Wang
Affiliations1. Nanjing Agricultural University; 2. Jiangsu Collaborative Innovation Center for Modern Crop Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Nanjing Agricultural University; 3. State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University; 4. The Second Surveying and Mapping Institute of Hunan Province; 5. International Institute for Earth System Sciences, Nanjing University; 6. Institute of Soil Science, Chinese Academy of Sciences; 7. Key Laboratory of Space Precision Measurement Technology, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences
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