The role of spatial resolution in vegetation information extraction: a comparison of Jilin-1 and Sentinel-2 satellite data in the Grodnenskaya Pushcha biosphere reserve (Belarus)
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Abstract
High-resolution satellite remote sensing data provide new opportunities for analysing vegetation structure in forest ecosystems with complex spatial organization. This study examines the role of spatial resolution in vegetation information extraction using multispectral satellite imagery. The research was conducted in the potential biosphere reserve «Grodnenskaya Pushcha» in the Republic of Belarus, a protected area characterized by high forest cover and pronounced spatial heterogeneity of vegetation. Multispectral satellite images from Jilin-1 with a spatial resolution of 5 m and Sentinel-2 with spatial resolutions of 10–20 m were used for the analysis and were acquired during the peak vegetation growth period. Vegetation condition was assessed using the red-edge vegetation index NDVI705. The analysis included a comparison of spectral profiles, statistical characteristics of the NDVI705 index, and results of unsupervised clustering (K-means) obtained for identical regions of interest. The results showed that both satellite datasets exhibit similar spectral patterns in the red-edge and near-infrared regions of the spectrum, while differing in the level of spatial detail. The higher spatial resolution of Jilin-1 imagery enables the detection of internal heterogeneity of forest cover, including small forest openings, narrow riparian zones and fragmented vegetation patches. Sentinel-2 data provide a more generalized representation of landscape structure but remain effective for analysis at the regional scale. The results indicate that spatial resolution is an important factor in vegetation analysis within forest natural complexes and that the combined use of satellite data with different spatial characteristics can improve ecological monitoring in protected areas.
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References
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