Annual winter wheat mapping dataset in China from 2001 to 2020
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a new phenology-based algorithm to map winter wheat distribution in China from 2001-2020 at 30m resolution. The accurate maps are crucial for food security and understanding agricultural patterns.
Area Of Science
- Agricultural Science
- Remote Sensing
- Geospatial Analysis
Background
- Winter wheat is a global staple, with China producing 19% of the world's supply.
- Accurate, long-term winter wheat distribution data is vital for food security and spatiotemporal pattern analysis.
- Existing remote sensing maps lack the required spatial resolution, temporal coverage, and scale for China.
Purpose Of The Study
- To develop and validate a high-resolution, long-term winter wheat distribution dataset for China.
- To address the gap in available remote sensing data for winter wheat cultivation.
- To support national food security initiatives and agricultural research.
Main Methods
- Developed a phenology-based algorithm integrating three key winter wheat growing features.
- Calculated planting probability using the integrated variable.
- Utilized a fusion dataset to produce winter wheat maps at 30-m resolution from 2001 to 2020.
Main Results
- Generated a long-term (2001-2020) winter wheat map dataset for China at 30-m resolution.
- Achieved high accuracy with user's (91.17%), producer's (90.92%), and overall (91.6%) accuracies based on field samples.
- Demonstrated good correlation between mapped winter wheat areas and agricultural statistical data at municipal and county levels.
Conclusions
- The phenology-based algorithm effectively identifies winter wheat locations with high accuracy.
- The produced dataset provides a valuable resource for understanding winter wheat cultivation in China.
- The high-resolution, long-term maps are critical for food security assessment and agricultural monitoring.
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