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森 杜

Lanzhou Jiaotong University

SCHOLARLY PAPERS

2

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78

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Scholarly Papers (2)

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1.

Evaluating the Spatial Dependence of Urban Water Supply and Demand in the Yellow River Basin: A Comprehensive Analysis of Urban, Land, Population, and Industry Driving Factors

Downloads 48 (1,133,231)

Evaluating the Spatial Dependence of Urban Water Supply and Demand in the Yellow River Basin: A Comprehensive Analysis of Urban, Land, Population, and Industry Driving Factors

Number of pages: 53 Posted: 25 Jul 2025
森 杜, deze Xu, Hualan Wang and Tianhong Zhou
Lanzhou Jiaotong University, Lanzhou Jiaotong University, Lanzhou Jiaotong University and Lanzhou Jiaotong University
Downloads 27 (1,415,710)

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Water Supply and Demand Capacity, Urban-land-population-industry relationships, Driving factors, Yellow River Basin, Geographically and Temporally Weighted Regression model

Evaluating the Spatial Dependence of Urban Water Supply and Demand in the Yellow River Basin: A Comprehensive Analysis of Urban, Land, Population, and Industry Driving Factors

Number of pages: 37 Posted: 25 Mar 2025
森 杜, deze Xu, Hualan Wang, Tianhong Zhou and Guozhen Zhang
Lanzhou Jiaotong University, Lanzhou Jiaotong University, Lanzhou Jiaotong University, Lanzhou Jiaotong University and Lanzhou Jiaotong University
Downloads 21 (1,525,626)

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Water Supply and Demand Capacity, Urban-land-population-industry relationships, Driving factors, Yellow River Basin, Geographically and Temporally Weighted Regression model

2.

Evaluating the Spatial Dependence of Urban Water Supply and Demand in the Yellow River Basin: A Comprehensive Analysis of Urban-Land-Population-Industry Driving Factors

Number of pages: 46 Posted: 11 Feb 2025
森 杜, deze Xu, Hualan Wang, Tianhong Zhou and Guozhen Zhang
Lanzhou Jiaotong University, Lanzhou Jiaotong University, Lanzhou Jiaotong University, Lanzhou Jiaotong University and Lanzhou Jiaotong University
Downloads 30 (1,345,526)

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Water Supply and Demand Capacity, urban-land-population-industry relationships, driving factors, Yellow River Basin, Geographically and Temporally Weighted Regression model