Su et al. (2026) Evolution of Urban–Agricultural–Ecological Spatial Structure Driven by Irrigation and Drainage Projects and Water–Heat–Vegetation Response

Identification

• Journal: Agriculture
• Year: 2026
• Date: 2026-01-06
• Authors: Tianqi Su, Yongmei
• DOI: 10.3390/agriculture16020142

Research Groups

• Institute for the History of Science and Technology, Inner Mongolia Normal University, Hohhot, China

Short Summary

This study investigates the evolution of urban–agricultural–ecological spatial structure and associated water–heat–vegetation responses driven by large-scale irrigation and drainage projects in the Inner Mongolia Hetao Plain from 1985 to 2015, revealing a path of "short-term intense disturbance–long-term stable optimization" and complex LST-VFC relationships.

Objective

• To systematically reveal the spatiotemporal differentiation patterns of urban–agricultural–ecological spatial structure evolution and surface parameter (Land Surface Temperature and Vegetation Fractional Coverage) responses throughout the life cycle of irrigation and drainage projects in arid and semi-arid regions.

Study Configuration

• Spatial Scale: Inner Mongolia Hetao Plain, Bayan Nur City, China, covering an area of approximately 1.68 × 10^4 square kilometers.
• Temporal Scale: 1985 to 2015, divided into three project phases: construction (1985–1997), operational (1997–2009), and post-operation optimization (2009–2015).

Methodology and Data

• Models used:
  • "Multifunctionality–dynamic evolution" dual-principle classification system for urban–agricultural–ecological space.
  • Maximum likelihood algorithm for land use classification.
  • Spectral angle matching (SAM) and neighborhood analysis for conflict pixel resolution.
  • Land use transfer matrix for spatial pattern evolution.
  • Standard deviation ellipse model for spatial migration characteristics.
  • Qin Zhihao single-window algorithm for Land Surface Temperature (LST) retrieval (accuracy: R^2 = 0.84, RMSE = 1.8 °C).
  • Pixel binning model for Vegetation Fractional Coverage (VFC) retrieval.
• Data sources:
  • Multitemporal remote sensing data from Landsat satellite series (LANDSAT 5 Thematic Mapper, LANDSAT 7 Enhanced Thematic Mapper Plus, LANDSAT 8 Operational Land Imager) with 15 meter spatial resolution (pan-sharpened).
  • 1:250,000 basic geographic data.
  • Regional land use statistical yearbooks (1985–2000).
  • Archival high-resolution aerial images (1986, 1995).
  • Google Earth high-resolution images (2013, 2015).
  • Local meteorological station data for atmospheric temperature.

Main Results

• The spatial structure evolution followed a path of "short-term intense disturbance–long-term stable optimization."
  • Urban space expanded from 249.46 square kilometers to 558.58 square kilometers, shifting from external encroachment to internal filling, with urban-to-ecological space conversion increasing from 3.44 square kilometers to 3.76 square kilometers.
  • Agricultural space stability (retention) increased by 4.8%, with a net increase of 260.80 square kilometers, and the conversion intensity from agricultural to ecological space decreased by 42.3%.
  • The ecological core area retention rate exceeded 90%, achieving "stable grain yield with unchanged cultivated land area and improved ecological quality with controlled green space loss."
• Urban, agricultural, and ecological spaces exhibited a consistent "northwest–southeast" coordinated evolution pattern, with ecological space shifting from an independent western distribution to filling gaps between urban and agricultural areas.
• Vegetation Fractional Coverage (VFC) showed spatial differentiation and stage fluctuations:
  • Central area: stable increase (annual growth rate 0.8%).
  • Eastern area: fluctuating recovery (cyclic amplitude ±12%).
  • Western area: local improvement (key patches increased by 18%).
• The Land Surface Temperature (LST) and VFC relationship presented spatiotemporal misalignment:
  • During the construction phase (1985–1997), the central region experienced an anomalous cooling of 0.8–1.2 °C despite a 15% VFC decrease, primarily due to the thermal inertia of irrigation water (8% increase in surface water coverage).
  • After completion (1997–2015), the linear negative correlation between LST and VFC was disrupted, with the central region showing a 1.5–2.0 °C LST increase while VFC increased by 25%, attributed to crop phenology changes, plastic film mulching (78% coverage in 2015, increasing surface albedo by 12%), and a shift to cash crops.
• Irrigation and drainage projects optimize water resource allocation, constructing a hub regulation model integrated with the Water–Energy–Food (WEF) Nexus.

Contributions

• Developed a novel "multifunctionality–dynamic evolution" dual-principle classification system for urban–agricultural–ecological space, overcoming limitations of traditional static classifications.
• Achieved high remote sensing interpretation accuracy (90.82%) through a refined "separate interpretation and merging with conflict pixel resolution" technical process.
• Systematically revealed the full life-cycle evolution path of the ecological thermal environment ("short-term disturbance–long-term steady state") driven by irrigation and drainage projects.
• Identified the phased reversal and spatial heterogeneity mechanisms of the LST-VFC relationship, separating the interactive interference of multiple factors (irrigation thermal effect, planting structure transformation, hydrological redistribution).
• Provided a replicable paradigm for ecological effect assessment of major water conservancy projects in arid regions, particularly through the proposed "hub regulation model" integrated with the Water–Energy–Food (WEF) Nexus.

Funding

• Innovation Team Development Project of Higher Education Institutions in Inner Mongolia Autonomous Region of China (Project Number: NMGIRT2505)

Citation

@article{Su2026Evolution,
  author = {Su, Tianqi and Yongmei},
  title = {Evolution of Urban–Agricultural–Ecological Spatial Structure Driven by Irrigation and Drainage Projects and Water–Heat–Vegetation Response},
  journal = {Agriculture},
  year = {2026},
  doi = {10.3390/agriculture16020142},
  url = {https://doi.org/10.3390/agriculture16020142}
}