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A GIS-Based Support Vector Machine Model for Flash Flood Vulnerability Assessment and Mapping in China 期刊论文
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2019, 卷号: 8, 期号: 7, 页码: 23
Authors:  Xiong, Junnan;  Li, Jin;  Cheng, Weiming;  Wang, Nan;  Guo, Liang
Favorite  |  View/Download:1/0  |  Submit date:2019/09/24
GIS  flash flood vulnerability assessment  exposure  disaster reduction capability  SVM  China  
An Improved Multi-temporal and Multi-feature Tea Plantation Identification Method Using Sentinel-2 Imagery 期刊论文
SENSORS, 2019, 卷号: 19, 期号: 9, 页码: 16
Authors:  Zhu, Jun;  Pan, Ziwu;  Wang, Hang;  Huang, Peijie;  Sun, Jiulin;  Qin, Fen;  Liu, Zhenzhen
Favorite  |  View/Download:1/0  |  Submit date:2019/09/24
remote sensing  Sentinel-2  tea plantation identification  Random Forest algorithm  feature selection  China  
Evaluating the effectiveness of fusing remote sensing images with significantly different spatial resolutions for thematic map production 期刊论文
PHYSICS AND CHEMISTRY OF THE EARTH, 2019, 卷号: 110, 页码: 71-80
Authors:  Chen, Shaohui;  Wang, Weimin;  Liang, Hong
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Image fusion  Intensity hue saturation  Support vector machine  A trous wavelet  Thematic map production  
Integration of two semi-physical models of terrestrial evapotranspiration using the China Meteorological Forcing Dataset 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 卷号: 40, 期号: 5-6, 页码: 1966-1980
Authors:  Liu, Meng;  Tang, Ronglin;  Li, Zhao-Liang;  Yan, Guangjian
Favorite  |  View/Download:45/0  |  Submit date:2019/05/22
Understanding the spatiotemporal variation of urban land expansion in oasis cities by integrating remote sensing and multi-dimensional DPSIR-based indicators 期刊论文
ECOLOGICAL INDICATORS, 2019, 卷号: 96, 页码: 23-37
Authors:  Liu, Yaqun;  Song, Wei;  Deng, Xiangzheng
Favorite  |  View/Download:10/0  |  Submit date:2019/05/22
Urbanization  Urban land use changes  Economic-socio-ecological indicators  Support vector machine  Sustainable urban development  Urban management and planning  
Water Resources Assessment of China's Transboundary River Basins Using a Machine Learning Approach 期刊论文
WATER RESOURCES RESEARCH, 2019, 卷号: 55, 期号: 1, 页码: 632-655
Authors:  Yan, Jiabao;  Jia, Shaofeng;  Lv, Aifeng;  Zhu, Wenbin
Favorite  |  View/Download:19/0  |  Submit date:2019/05/22
water resources  runoff coefficient  machine learning  transboundary river  China  
An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support 期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2018, 卷号: 146, 页码: 347-359
Authors:  Hu, Yunfeng;  Dong, Yu;  Batunacun
Favorite  |  View/Download:12/0  |  Submit date:2019/05/23
Automatic update  Change detection  Land use/land cover  Time-series analysis  
Retrieval of Daily PM2.5 Concentrations Using Nonlinear Methods: A Case Study of the Beijing-Tianjin-Hebei Region, China 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 17
Authors:  Li, Lijuan;  Chen, Baozhang;  Zhang, Yanhu;  Zhao, Youzheng;  Xian, Yue;  Xu, Guang;  Zhang, Huifang;  Guo, Lifeng
Favorite  |  View/Download:11/0  |  Submit date:2019/05/23
daily PM2  5concentrations  remote sensing  MODIS AOD  machine learning algorithm  spatial and temporal distribution  
A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 16
Authors:  Hu, Yunfeng;  Zhang, Qianli;  Zhang, Yunzhi;  Yan, Huimin
Favorite  |  View/Download:10/0  |  Submit date:2019/05/23
land cover/land use  image classification  automatic mapping  accuracy evaluation  methods comparison  Landsat OLI imagery  
Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2018, 卷号: 38, 期号: 13, 页码: 4891-4902
Authors:  Wang, Bin;  Zheng, Lihong;  Liu, De Li;  Ji, Fei;  Clark, Anthony;  Yu, Qiang
Favorite  |  View/Download:7/0  |  Submit date:2019/05/23
GCMs  machine learning  multi-model ensemble  random forest  support vector machine