Assessment of scots pine forest cover changes using NDVI and FCD indicators based on GIS and aerospace methods

Abstract

Abstract

Background and objective. The study aims to assess the changes in scots pine forest cover in the «Semey Ormany»state forest natural reserve from 2008 to 2023 using NDVI and FCD indices, GIS, and remote sensing methods. The key indicators are the Normalized Difference Vegetation Index (NDVI) and the Forest Canopy Density (FCD) index.

Materials and methods. Satellite data from Landsat 5 TM and Landsat 9 OLI were used. Google Earth Engine (GEE) and ArcGIS served as GIS platforms. Data preprocessing included atmospheric correction, cloud removal, radiometric and geometric corrections. NDVI and FCD methods were applied to assess forest cover.

Results. The NDVI method provides an overall view of vegetation conditions over large areas, enabling monitoring of forests and other vegetation types. However, it lacks precision in assessing tree canopy density, particularly in dense forests. In contrast, the FCD method offers more accurate forest density evaluation as it is specifically designed for forest cover analysis but does not account for other vegetation types.

Conclusion. The study results indicate significant forest recovery in the «Semey Ormany» reserve over the past 15 years. The proportion of deforested areas has significantly decreased, while dense forest cover has expanded. These changes are attributed to natural regeneration, forest restoration programs, and climatic factors. The combined use of NDVI and FCD methods enables a comprehensive assessment of forest ecosystem dynamics. The findings can be applied to other natural areas in Kazakhstan and serve as a basis for forest management strategies.

Key words: NDVI, FCD, GIS, remote sensing, Landsat, forest cover, Semey Ormany, forest degradation, natural regeneration.