Spatiotemporal Changes of Vegetation Growth and Its Influencing Factors in the Huojitu Mining Area from 1999 to 2023 Based on kNDVI
Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in the Shendong region, utilizing the kNDVI index calculated via the Google Earth Engine (GEE) cloud platform. The Mann–Kendall mutation test and linear regression analysis were employed to examine the spatiotemporal changes in vegetation growth over a 25-year period from 1999 to 2023. Through correlation analysis, geographic detector models, and land use map fusion, combined with climate, topography, soil, mining, and land use data, this study investigates the influencing factors of vegetation growth evolution. The key findings are as follows: (1) kNDVI is more suitable for analyzing vegetation growth in this study compared to NDVI. (2) Over the past 25 years, vegetation growth has exhibited an overall fluctuating upward trend, with an annual growth rate of 0.0041/a. The annual average kNDVI value in the mining area is 0.121. Specifically, kNDVI initially increased gradually, then rapidly increased, and subsequently declined rapidly. (3) Vegetation growth in the study area has significantly improved, with areas of improved vegetation accounting for 89.08% of the total mining area, while degraded areas account for 11.02%. (4) Precipitation and air temperature are the primary natural factors influencing vegetation growth fluctuations in the mining area, with precipitation being the dominant factor (r = 0.81, p < 0.01). The spatial heterogeneity of vegetation growth is influenced by land use, topography, soil nutrients, and mining activities, with land use having the greatest impact (q = 0.43). Major land use changes contribute 46.45% to vegetation improvement and 13.43% to vegetation degradation. The findings of this study provide a scientific basis for ecological planning and the development of the Huojitu mining area.
Authors
- Zhenyao Zhu
- Yi‐Qiang Cheng (ORCID: https://orcid.org/0000-0001-9336-2593)
- Zhichao Chen (ORCID: https://orcid.org/0000-0002-8431-6066)
- Xufei Zhang (ORCID: https://orcid.org/0000-0001-9666-5354)
- Hebing Zhang (ORCID: https://orcid.org/0009-0005-4799-8124)
- Shidong Wang (ORCID: https://orcid.org/0000-0003-3359-6130)
- Chengyuan Hao (ORCID: https://orcid.org/0000-0002-6002-3963)
- Youfeng Zou
Institutions
- Henan Polytechnic University (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-02-05
- DOI
- https://doi.org/10.3390/rs17030536
- Citations
- 2
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 2.60