Du et al. (2025) Research on Driving Forces of Spatiotemporal Patterns in Cotton Cultivation Considering Spatial Heterogeneity

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-10-18
• Authors: Meng Du, Danjing Shen, Xun Yang, Fenfang Lin, Chunfa Wu, Dongyan Zhang
• DOI: 10.3390/agriculture15202163

Research Groups

Not explicitly mentioned in the paper.

Short Summary

This study combined the locally explained stratified heterogeneity (LESH) model with geographically weighted regression (GWR) to investigate the spatiotemporal drivers of cotton-planting patterns in the northern slope of the Tianshan Mountains (NSTM), China, from 2000 to 2020, finding that elevation, sunshine duration, slope, temperature, runoff, and gross domestic product are dominant factors, with significant spatial heterogeneity and factor interactions.

Objective

• To investigate the factors shaping cotton-planting patterns in the northern slope of the Tianshan Mountains (NSTM), China, from 2000 to 2020, considering spatial heterogeneity and factor interactions.

Study Configuration

• Spatial Scale: Northern slope of the Tianshan Mountains (NSTM), China.
• Temporal Scale: 2000 to 2020 (21 years).

Methodology and Data

• Models used: Locally explained stratified heterogeneity (LESH) model, Geographically Weighted Regression (GWR).
• Data sources: Long-term Landsat image series (for cotton distribution). Data for drivers (elevation, sunshine duration, slope, temperature, runoff, gross domestic product).

Main Results

• Cotton distribution expanded at an average annual growth rate of 2.10 × 10^3 km^2.
• Intensive cotton cultivation was primarily distributed across the central and western counties of the NSTM.
• The dominant drivers of cotton distribution were elevation (ELE), sunshine duration (SD), slope (SLO), temperature (TEM), runoff (RO), and gross domestic product (GDP).
• Elevation (ELE) explained approximately 40% of the spatial heterogeneity in cotton planting.
• Sunshine duration (SD) showed a declining influence over time, slope (SLO) remained stable, temperature (TEM) increased in importance, and gross domestic product (GDP) exhibited a progressive upward trend, although weaker.
• Nonlinear weakening interactions, particularly between elevation and other factors, as well as between socio-economic and climatic variables, substantially enhanced the explanatory power of the models.

Contributions

• Developed a combined LESH and GWR modeling approach to analyze the spatiotemporal drivers of cotton planting patterns while accounting for spatial heterogeneity.
• Identified specific dominant biophysical and socioeconomic factors influencing cotton distribution in the NSTM and quantified their relative importance and temporal trends.
• Highlighted the critical significance of considering spatial heterogeneity and factor interactions for guiding spatial optimization and sustainable management strategies for cotton cultivation.

Funding

Not explicitly mentioned in the paper.

Citation

@article{Du2025Research,
  author = {Du, Meng and Shen, Danjing and Yang, Xun and Lin, Fenfang and Wu, Chunfa and Zhang, Dongyan},
  title = {Research on Driving Forces of Spatiotemporal Patterns in Cotton Cultivation Considering Spatial Heterogeneity},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15202163},
  url = {https://doi.org/10.3390/agriculture15202163}
}