The Spatiotemporal Pattern and Driving Factors of Vegetation in Zhejiang Province over the Past 20 Years

FANG Xiaoyan; CHEN Binghong; JIN Quanfeng

doi:10.3969/j.issn.1001-3776.2024.06.012

Journal of Zhejiang Forestry Science and Technology > 2024 > 44(6): 88-97. > DOI: 10.3969/j.issn.1001-3776.2024.06.012

FANG Xiaoyan, CHEN Binghong, JIN Quanfeng. The Spatiotemporal Pattern and Driving Factors of Vegetation in Zhejiang Province over the Past 20 Years[J]. Journal of Zhejiang Forestry Science and Technology, 2024, 44(6): 88-97. DOI: 10.3969/j.issn.1001-3776.2024.06.012

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The Spatiotemporal Pattern and Driving Factors of Vegetation in Zhejiang Province over the Past 20 Years

1.
Qingyuan Haixi Forestry Planning and Design, Lishui 323000, China
2.
Lishui Vocational and Technical College, Lishui 323000, China
3.
Forestry College, Fujian Agriculture and Forestry University, Fuzhou 350002, China

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Received Date: January 17, 2024
Revised Date: July 06, 2024

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Abstract

Abstract

This study utilized medium-resolution MOD13Q1 imagery to calculate the Normalized Difference Vegetation Index (NDVI). Using geographic information system (GIS) technology, NDVI data for Zhejiang Province from 2000 to 2019 was extracted. Trend analysis was then employed to investigate the spatiotemporal patterns, changing trends, and driving factors of NDVI in Zhejiang Province. The results show significant spatial differences in NDVI across Zhejiang Province from 2000 to 2019, with a fluctuating upward trend over time and an average growth rate of 0.022 per decade. Seasonally, the average NDVI ranked as follows: summer > autumn > spring > winter, exhibiting a single peak and single valley distribution, with the peak in July and the valley in February. Overall, NDVI improved with areas of improvement and significant improvement accounting for 15.81% and 55.85% of the province's total area, respectively, while degraded areas accounted for 22.02%. Results from a multiple linear regression model indicate that eight factors significantly influence NDVI: monthly maximum temperature, monthly average relative humidity, monthly cumulative precipitation, road density, river density, railway density, slope, and altitude. The model’s root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R²) were 0.050, 5.68%, and 0.572, respectively, indicating a certain level of reliability in estimating NDVI in Zhejiang Province. The study's findings reveal the spatiotemporal patterns and driving factors of NDVI in Zhejiang Province, providing a scientific basis for vegetation restoration in the region.
- Zhejiang,
- NDVI,
- Spatial and temporal patterns,
- trend analysis,
- driving factors

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References

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