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A Process-Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2021, 卷号: 13, 期号: 6, 页码: 22
Authors:  Niu, Zhongen;  He, Honglin;  Peng, Shushi;  Ren, Xiaoli;  Zhang, Li;  Gu, Fengxue;  Zhu, Gaofeng;  Peng, Changhui;  Li, Pan;  Wang, Junbang;  Ge, Rong;  Zeng, Na;  Zhu, Xiaobo;  Lv, Yan;  Chang, Qingqing;  Xu, Qian;  Zhang, Mengyu;  Liu, Weihua
Favorite  |  View/Download:2/0  |  Submit date:2021/08/19
CEVSA-ES model  ecosystem services  remote sensing  model-data fusion  China  
Optimization of multi-source UAV RS agro-monitoring schemes designed for field-scale crop phenotyping 期刊论文
PRECISION AGRICULTURE, 2021, 页码: 35
Authors:  Zhu, Wanxue;  Sun, Zhigang;  Huang, Yaohuan;  Yang, Ting;  Li, Jing;  Zhu, Kangying;  Zhang, Junqiang;  Yang, Bin;  Shao, Changxiu;  Peng, Jinbang;  Li, Shiji;  Hu, Hualang;  Liao, Xiaohan
Favorite  |  View/Download:11/0  |  Submit date:2021/06/10
Unmanned aerial vehicle (UAV)  Multispectral  Hyperspectral  Thermal  LiDAR  Phenotyping  
Reference carbon cycle dataset for typical Chinese forests via colocated observations and data assimilation 期刊论文
SCIENTIFIC DATA, 2021, 卷号: 8, 期号: 1, 页码: 13
Authors:  He, Honglin;  Ge, Rong;  Ren, Xiaoli;  Zhang, Li;  Chang, Qingqing;  Xu, Qian;  Zhou, Guoyi;  Xie, Zongqiang;  Wang, Silong;  Wang, Huimin;  Zhang, Qibin;  Wang, Anzhi;  Fan, Zexin;  Zhang, Yiping;  Shen, Weijun;  Yin, Huajun;  Lin, Luxiang;  Williams, Mathew;  Yu, Guirui
Favorite  |  View/Download:66/0  |  Submit date:2021/04/25
Fusion of High- and Medium-Resolution Optical Remote Sensing Imagery and GlobeLand30 Products for the Automated Detection of Intra-Urban Surface Water 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 24, 页码: 21
Authors:  Li, Zhi;  Yang, Xiaomei
Favorite  |  View/Download:7/0  |  Submit date:2021/03/15
urban surface water area  extended morphological profiles  adaptive threshold segmentation  decision-level fusion  GaoFen-1 satellite  Landsat-OLI 8  GlobeLand30 products  three-case study in China  
Spatial Distribution of China's Industrial Output Values under Global Warming Scenarios RCP4.5 and RCP8.5 期刊论文
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 卷号: 9, 期号: 12, 页码: 19
Authors:  Xue, Qian;  Song, Wei
Favorite  |  View/Download:6/0  |  Submit date:2021/03/15
climate change  industrial output value  RCP4  5 and RCP8  5  machine learning  random forest algorithm  China  
Cropland data fusion and correction using spatial analysis techniques and the Google Earth Engine 期刊论文
GISCIENCE & REMOTE SENSING, 2020, 页码: 20
Authors:  Li, Kewei;  Xu, Erqi
Favorite  |  View/Download:6/0  |  Submit date:2021/03/16
Cropland  data fusion  Google Earth Engine  belt and road region  
A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015 期刊论文
SCIENTIFIC DATA, 2020, 卷号: 7, 期号: 1, 页码: 13
Authors:  Niu, Zhongen;  He, Honglin;  Zhu, Gaofeng;  Ren, Xiaoli;  Zhang, Li;  Zhang, Kun
Favorite  |  View/Download:8/0  |  Submit date:2021/03/16
Integrative ecology in the era of big data-From observation to prediction 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1429-1442
Authors:  Niu, Shuli;  Wang, Song;  Wang, Jinsong;  Xia, Jianyang;  Yu, Guirui
Favorite  |  View/Download:6/0  |  Submit date:2021/03/18
Integrative ecology  Meta-analysis  Data mining  Data-model fusion  
The utility of fusing multi-sensor data spatio-temporally in estimating grassland aboveground biomass in the three-river headwaters region of China 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2020, 卷号: 41, 期号: 18, 页码: 7068-7089
Authors:  Zeng, Na;  He, Honglin;  Ren, Xiaoli;  Zhang, Li;  Zeng, Yuan;  Fan, Jiangwen;  Li, Yuzhe;  Niu, Zhongen;  Zhu, Xiaobo;  Chang, Qingqing
Favorite  |  View/Download:3/0  |  Submit date:2021/07/09
Research challenges and opportunities for using big data in global change biology 期刊论文
GLOBAL CHANGE BIOLOGY, 2020, 页码: 22
Authors:  Xia, Jianyang;  Wang, Jing;  Niu, Shuli
Favorite  |  View/Download:6/0  |  Submit date:2021/03/16
big data  Earth system model  global change biology  machine learning  model uncertainty