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Multivariable cokriging prediction and source analysis of potentially toxic elements (Cr, Cu, Cd, Pb, and Zn) in surface sediments from Dongting Lake, China 期刊论文
ECOLOGICAL INDICATORS, 2018, 卷号: 94, 页码: 312-319
Authors:  Wang, Lingqing;  Dai, Lijun;  Li, Lianfang;  Liang, Tao
Favorite  |  View/Download:9/0  |  Submit date:2019/05/23
Sediment  Potentially toxic elements  Multivariable cokriging  Potential ecological risk  Factor analysis of mixed data  
Predicting Grassland Leaf Area Index in the Meadow Steppes of Northern China: A Comparative Study of Regression Approaches and Hybrid Geostatistical Methods SCI/SSCI论文
2016
Authors:  Li Z. W.;  Wang, J. H.;  Tang, H.;  Huang, C. Q.;  Yang, F.;  Chen, B. R.;  Wang, X.;  Xin, X. P.;  Ge, Y.
View  |  Adobe PDF(5259Kb)  |  Favorite  |  View/Download:22/4  |  Submit date:2017/11/09
leaf area index  grassland  predict  geostatistics  regression  remote  sensing  artificial neural-networks  airborne hyperspectral imagery  support  vector regression  modis-lai product  squares regression  random  forests  vegetation indexes  satellite data  spatial-distribution  aboveground biomass  
基于时空地统计学的监测网布局优化与时空插值研究 学位论文
博士, 北京: 中国科学院研究生院, 2015
Authors:  王江浩
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A Geostatistical Approach to Upscale Soil Moisture With Unequal Precision Observations 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2014, 卷号: 11, 期号: 12, 页码: 2125-2129
Authors:  Wang, Jianghao(王江浩);  Ge, Yong;  Song, Yongze;  Li, Xin
Adobe PDF(784Kb)  |  Favorite  |  View/Download:123/47  |  Submit date:2014/12/10
Block Kriging (Bk)  Heihe Watershed Allied Telemetry Experimental Research (Hiwater)  Monte Carlo Simulation  Remote Sensing Product Validation  
Modeling the Concentrations of On-Road Air Pollutants in Southern California SCI/SSCI论文
2013
Authors:  Li L. F.;  Wu J.;  Hudda N.;  Sioutas C.;  Fruin S. A.;  Delfino R. J.
Adobe PDF(404Kb)  |  Favorite  |  View/Download:56/19  |  Submit date:2014/12/24
Land-use Regression  Los-angeles  Ultrafine Particles  Particulate  Matter  Commuter Exposure  Pollution  Freeways  Exhaust  Trends  Time