中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究所 [4]
采集方式
OAI收割 [4]
内容类型
期刊论文 [4]
发表日期
2026 [1]
2025 [1]
2023 [2]
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A Novel Sampling Design That Considers Local Soil Heterogeneity in Both Geographical and Feature Spaces for Mapping Multiple Soil Properties at the Farm Level
期刊论文
OAI收割
IEEE ACCESS, 2026, 卷号: 14, 页码: 424-440
作者:
Wang, Yongji
;
Li, Shaoqi
;
Wang, Meizi
;
Qi, Qingwen
;
Li, Peng
  |  
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2026/02/09
Soil
Soil properties
Vegetation mapping
Predictive models
Normalized difference vegetation index
Indexes
Design methodology
Accuracy
Robustness
Image resolution
Soil variability
digital soil mapping (DSM)
sampling design
local heterogeneity of soil
subregion division
effective coverage in both geographical and feature spaces
A novel potential outlier recognition approach considering local heterogeneity enhancement to improve the quality of soil datasets
期刊论文
OAI收割
GEODERMA, 2025, 卷号: 454, 页码: 117200
作者:
Wang, Yongji
;
Yang, Mingjun
;
Wang, Meizi
;
Lv, Jiayang
;
Yuan, Shuhao
  |  
收藏
  |  
浏览/下载:55/0
  |  
提交时间:2025/03/18
Digital soil mapping (DSM)
Quality of soil datasets
Soil samples
Soil map product
Outlier recognition
Local heterogeneity enhancement
The potential of image segmentation applied to sampling design for improving farm-level multi-soil property mapping accuracy
期刊论文
OAI收割
PRECISION AGRICULTURE, 2023, 页码: 24
作者:
Wang, Yongji
;
Qi, Qingwen
;
Wang, Jun
;
Wang, Meizi
;
Ye, Yanjun
  |  
收藏
  |  
浏览/下载:53/0
  |  
提交时间:2023/10/09
Digital soil mapping (DSM)
Sampling design
Local environmental similarity
Within-region homogeneity and between-region heterogeneity
Optimal sample size and locations
Recognition of potential outliers in soil datasets from the perspective of geographical context for improving farm-level soil mapping accuracies
期刊论文
OAI收割
GEODERMA, 2023, 卷号: 431, 页码: 116374
作者:
Wang, Yongji
;
Qi, Qingwen
;
Zhou, Lin
;
Wang, Meizi
;
Wang, Qinqin
  |  
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2024/01/04
Digital soil mapping (DSM)
Soil samples
Outlier recognition
Geographical context
Local spatial autocorrelation and heterogeneity