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Remote Sensing-Based Study of Plant Cover and Urbanization in Kunming from 2000 to 2022
- 1 College of the Environment, Beijing Jiaotong University, Weihai, 264401, China
* Author to whom correspondence should be addressed.
Abstract
Reduced vegetation cover due to accelerated urbanization can lead to many ecological problems, and whether ecological conservation measures can effectively mitigate this effect remains to be assessed. This paper explores the influence of urbanization on vegetation cover and the performance of related ecological protection measures in Kunming. This paper reveals the significant negative correlation between NDVI and NDBI data during the period of 2000-2022 through linear regression analysis and Pearson correlation analysis, and combines spatial analyses to demonstrate the changes of vegetation cover in Kunming during the urbanization process. The study results indicated that the NDVI in Kunming City as a whole had a slow increasing trend, with 0.0020 per year, and NDBI had a slow decreasing trend with 0.0014 per year. And they are significantly negatively correlated with a Pearson correlation coefficient of -0.6168. In addition, the vegetation cover in non-urban areas and the area around Dianchi Lake has increased considerably, indicating that the ecological protection measures in the region are effective, but the vegetation cover in urban areas has still declined. The study provides an important scientific basis for ecological protection policies and sustainable urban planning in similar cities, and promotes urban ecological protection and green development.
Keywords
NDVI, NDBI, Kunming
[1]. Salam, M., Islam, M. K., Jahan, I., & Chowdhury, M. A. (2024). Assessing the impacts of vegetation loss and land surface temperature on Surface Urban Heat Island (SUHI) in Gazipur District, Bangladesh. Computational Urban Science, 4, 24. https://doi.org/10.1007/s43762-024-00136-y
[2]. Ye, Q., Wang, X., Liang, L., Qiu, J.-W., & Tsim, S.-T. (2025). A Review on Landscape Factors for Biodiversity Performance Enhancement in Urban Parks. Diversity, 17(4), 262. https://doi.org/10.3390/d17040262
[3]. Resemini, R., Geroldi, C., Capotorti, G., De Toni, A., Parisi, F., De Sanctis, M., Cabai, T., Rossini, M., Vignali, L., Poli, M. U., Lo Piccolo, E., Mariotti, B., Arcidiacono, A., Biella, P., Alghisi, E., Bani, L., Bertini, M., Blasi, C., Buffi, F., ... Gentili, R. (2025). Building Greener Cities Together: Urban Afforestation Requires Multiple Skills to Address Social, Ecological, and Climate Challenges. Plants, 14(3), 404. https://doi.org/10.3390/plants14030404
[4]. Alademomi, A. S., Okolie, C. J., Daramola, O. E., Akinnusi, S. A., Adediran, E., Olanrewaju, H. O., Alabi, A. O., Salami, T. J., & Odumosu, J. (2022). The interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria. Applied Geomatics, 14(2), 299–314. https://doi.org/10.1007/s12518-022-00434-2
[5]. Kunming Municipal People's Government. (2025/4/10). Natural geography: Kunming overview. Retrieved from https://www.km.gov.cn/c/2025-03-03/4659502.shtml
[6]. Yang, H., Yu, J., Xu, W., Wu, Y., Lei, X., Ye, J., Geng, J., & Ding, Z. (2023). Long-time series ecological environment quality monitoring and cause analysis in the Dianchi Lake Basin, China. Ecological Indicators, 148, 110084. https://doi.org/10.1016/j.ecolind.2023.110084
[7]. Luo, C., Wang, X., Chen, Y., Luo, H., Dong, H., & He, S. (2025). Predictive Modeling of Cyanobacterial Blooms and Diurnal Variation Analysis Based on GOCI. Water, 17(5), 749. https://doi.org/10.3390/w17050749
[8]. Iglesia Martinez, A. de la, & Labib, S. M. (2023). Demystifying normalized difference vegetation index (NDVI) for greenness exposure assessments and policy interventions in urban greening. Environmental Research, 220, 115155. https://doi.org/10.1016/j.envres.2022.115155
[9]. Suparta, W., & Hartono, H. G. (2024). Application of the NDBI method for determining of built-up land: A case study for Surabaya City, Indonesia. International Research Journal of Engineering and Technology (IRJET), 11(07), 1321–1325.
[10]. Sharma, I., Tongkumchum, P., & Ueranantasun, A. (2021). Regression analysis of normalized difference vegetation index (NDVI) to compare seasonal patterns and 15 year trend of vegetation from east to west of Nepal. Nature Environment and Pollution Technology, 20(1), 267-273. https://doi.org/10.46488/NEPT.2021.v20i01.029
Cite this article
Wang,H. (2025). Remote Sensing-Based Study of Plant Cover and Urbanization in Kunming from 2000 to 2022. Theoretical and Natural Science,112,13-20.
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Volume title: Proceedings of ICEGEE 2025 Symposium: Sensor Technology and Multimodal Data Analysis
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