HYPERSPECTRAL

作品数：231被引量：518H指数：11
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相关机构：中国农业大学国家农业信息化工程技术研究中心哈尔滨工程大学北京航空航天大学更多>>
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A hyperspectral detection model for permeability coefficient of debris flow fine-grained sediments, Southwestern China
《International Journal of Digital Earth》2023年第1期1589-1606,共18页Qinjun Wang Jingjing Xie Jingyi Yang Peng Liu Dingkun Chang Wentao Xu 
funded in part by the Innovative Research Program of the International Research Center of Big Data for Sustainable Development Goals[grant number CBAS2022IRP03];the National Natural Science Foundation of China[grant number 42071312];the Hainan Hundred Special Project[grant number 31,JTT[2018]].
Fine-grained sediments are Quaternary sediments with grain sizes of not more than 2 mm.They startfirst when meeting water,their stability is related to the initial water volume triggering debrisflow,and thus plays an ...
关键词：Beichuan debris flow fine-grained sediments permeability coefficient hyperspectral detection model 
HyperRefiner:a refined hyperspectral pansharpening network based on the autoencoder and self-attention
《International Journal of Digital Earth》2023年第1期3268-3294,共27页Bo Zhou Xianfeng Zhang Xiao Chen Miao Ren Ziyuan Feng 
supported by the National Natural Science Foundation of China[grant number 42171327];the International Research Center of Big Data for Sustainable Development Goals,China[grant number CBAS2022GSP06].
Deep learning has been developed to generate promising super resolution hyperspectral imagery by fusing hyperspectral imagery with the panchromatic band.However,it is still challenging to maintain edge spectral inform...
关键词：Image fusion HYPERSPECTRAL self-attention autoencoder edge spectrum 
Spectral clustering eigenvector selection of hyperspectral image based on the coincidence degree of data distribution
《International Journal of Digital Earth》2023年第1期3489-3512,共24页Zhongliang Ren Qiuping Zhai Lin Sun 
supported by the[National Key Research and Development Program]under Grant[number 2019YFE0126700];[Shandong Provincial Natural Science Foundation]under Grant[number ZR2020QD018].
Spectral clustering is a well-regarded subspace clustering algorithm that exhibits outstanding performance in hyperspectral image classification through eigenvalue decomposition of the Laplacian matrix.However,its cla...
关键词：Eigenvector selection spectral clustering coincidence degree of data distribution hyperspectral mineral mapping 
Hyperspectral anomaly detection:a performance comparison of existing techniques被引量：2
《International Journal of Digital Earth》2022年第1期2078-2125,共48页Noman Raza Shah Abdur Rahman M.Maud Farrukh Aziz Bhatti Muhammad Khizer Ali Khurram Khurshid Moazam Maqsood Muhammad Amin 
supported by Pakistan Space and Upper Atmosphere Research Commission[grant number NSP-654-20].
Anomaly detection in Hyperspectral Imagery(HSI)has received considerable attention because of its potential application in several areas.Numerous anomaly detection algorithms for HSI have been proposed in the literatu...
关键词：Anomaly detection algorithms hyperspectral imagery deep learning dimensionality reduction 
Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machinelearning workflow
《International Journal of Digital Earth》2018年第7期670-690,共21页Michael J.Friedel Massimo Buscema Luiz Eduardo Vicente Fabio Iwashita Andréa Koga-Vicente 
An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery.The workflow is applied to EO-1 Hyperion satellite i...
关键词：HYPERSPECTRAL machine learning remote sensing soils and vegetation unsupervised workflow 
Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China被引量：5
《International Journal of Digital Earth》2013年第1期76-93,共18页Yingcheng Lu Qingjiu Tian Xinyuan Wang Guang Zheng Xiang Li 
supported by National Natural Science Foundation of China(Grant No.41001196);the Open Research Fund of Key Laboratory of Marine Spill Oil Identification and Damage Assessment Technology,SOA(Grant No.201212);the Open Research Fund of Key Laboratory of Digital Earth,Center for Earth Observation and Digital Earth,Chinese Academy of Sciences(Grant No.2010LDE007).
Determining oil slick thickness plays an important role in assessing oil spill volume and its environmental impacts on the ocean.In this study,we used a Hyperion image of an oil spill accident area and seawater and fr...
关键词：HYPERSPECTRAL optical remote sensing reflectance oil slick thickness oil spill 
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