Evolutionary Characteristics of Rural Settlements and the Spatial Differentiation of Human–Earth Coupling in Irrigated Arid Areas: A Case Study of the Yellow River Irrigation Area of Inner Mongolia

Rural settlements, cropland, and canal systems represent the fundamental spatial components of rural human–environment systems in irrigated arid regions. Their coordinated development is essential for regional sustainability, especially in light of the dual pressures posed by stringent water resource constraints and ecological conservation. This study focuses on the Yellow River Irrigation Area of Inner Mongolia within the Yellow River Basin, addressing the practical challenge of systemic imbalance among rural residential space, water system ecology, and cropland resources in rural development. To achieve this, we developed a spatial coupling framework that integrates rural settlements, canals, and cropland systems. We employed a combination of GIS spatial analysis, landscape pattern metrics, and spatial coupling models to analyze land-use data from 2000 to 2020, thereby examining the evolutionary characteristics of rural settlements and their human–Earth spatial coupling relationships. The results indicate that (1) the landscape pattern of rural settlements underwent a phased transition from contraction to scale-oriented reorganization, characterized by a “dense south, sparse north” spatial distribution. The global Moran’s I increased from 0.328 to 0.437 (p < 0.001), reflecting a continuous strengthening of agglomeration intensity. (2) Human–land coupling was primarily dominated by the Cropland-Rich Type, while the Settlement–Cropland Coordinated Type experienced a sharp decline before partially recovering. Human–water coupling was mainly defined by the Canal-Abundant Type, whereas the Settlement–Canal Coordinated Type decreased significantly, indicating a shift from relative equilibrium to polarization. (3) The human–water–land system followed a staged evolutionary pathway, shifting from an engineering-driven tension period (2000–2010) to an efficiency-driven transition period (2010–2020) within the human–Earth relationship. Overall, the coupling relationships within the human–water–land system in the study area exhibit significant spatial heterogeneity, with persistent human–Earth conflicts in certain sub-regions presenting challenges to the ecological security of the Yellow River Basin and the sustainable development of rural areas.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-09-24
DOI
https://doi.org/10.3390/su18199789
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Evolutionary Characteristics of Rural Settlements and the Spatial Differentiation of Human–Earth Coupling in Irrigated Arid Areas: A Case Study of the Yellow River Irrigation Area of Inner Mongolia

Xiaohai Hu, Pinyuan Wang
Sustainability
Land Use and Ecosystem Services
article

Evolutionary Characteristics of Rural Settlements and the Spatial Differentiation of Human–Earth Coupling in Irrigated Arid Areas: A Case Study of the Yellow River Irrigation Area of Inner Mongolia

Xiaohai Hu, Pinyuan Wang
article en

Abstract

Rural settlements, cropland, and canal systems represent the fundamental spatial components of rural human–environment systems in irrigated arid regions. Their coordinated development is essential for regional sustainability, especially in light of the dual pressures posed by stringent water resource constraints and ecological conservation. This study focuses on the Yellow River Irrigation Area of Inner Mongolia within the Yellow River Basin, addressing the practical challenge of systemic imbalance among rural residential space, water system ecology, and cropland resources in rural development. To achieve this, we developed a spatial coupling framework that integrates rural settlements, canals, and cropland systems. We employed a combination of GIS spatial analysis, landscape pattern metrics, and spatial coupling models to analyze land-use data from 2000 to 2020, thereby examining the evolutionary characteristics of rural settlements and their human–Earth spatial coupling relationships. The results indicate that (1) the landscape pattern of rural settlements underwent a phased transition from contraction to scale-oriented reorganization, characterized by a “dense south, sparse north” spatial distribution. The global Moran’s I increased from 0.328 to 0.437 (p < 0.001), reflecting a continuous strengthening of agglomeration intensity. (2) Human–land coupling was primarily dominated by the Cropland-Rich Type, while the Settlement–Cropland Coordinated Type experienced a sharp decline before partially recovering. Human–water coupling was mainly defined by the Canal-Abundant Type, whereas the Settlement–Canal Coordinated Type decreased significantly, indicating a shift from relative equilibrium to polarization. (3) The human–water–land system followed a staged evolutionary pathway, shifting from an engineering-driven tension period (2000–2010) to an efficiency-driven transition period (2010–2020) within the human–Earth relationship. Overall, the coupling relationships within the human–water–land system in the study area exhibit significant spatial heterogeneity, with persistent human–Earth conflicts in certain sub-regions presenting challenges to the ecological security of the Yellow River Basin and the sustainable development of rural areas.

SustainabilityVol. 18(19)
Inner Mongolia University of Technology (CN)
Life in Land
Openalex Percentile: Top 14%
Land Use and Ecosystem Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.