CHANGES IN VEGETATION COVERAGE AS AN INDICATOR OF SOIL CONDITION IN THE CARPATHIAN REGION AND ADJACENT TERRITORIES

Abstract

The monitoring of land resources is a critical component of sustainable development, particularly in regions with mixed agro-forestry landscapes that are sensitive to both climatic shifts and anthropogenic pressures. This study presents a comprehensive analysis of long-term vegetation dynamics within the Chernivtsi Raion. The primary objective was to assess spatio-temporal trends in vegetation productivity by utilizing the Normalized Difference Vegetation Index (NDVI) as a key indicator of vegetation health and soil condition. A core component of the methodology was a comparative analysis of results derived from two distinct satellite data sources - the moderate-resolution MODIS sensor and the high-resolution Landsat archive - to understand how sensor characteristics influence the interpretation of land degradation and improvement processes. The analysis was conducted using two independent, long-term satellite data archives. The first dataset comprised 16-day NDVI composites from the MODIS product MOD13Q1 at a 250-meter spatial resolution, covering the period from 2002 to 2024. The second dataset consisted of a harmonized time-series of Landsat 5, 7, 8, and 9 images at a 30-meter resolution for the years 2000 to 2024. For each year, a single representative image for the growing season (April–October) was generated. For MODIS, the annual metric was the mean NDVI of all composites within the season. For the more variable Landsat data, the median NDVI was calculated to create a robust annual composite resistant to outliers such as undetected clouds or sensor artifacts. A non-parametric, per-pixel trend analysis was performed on both time-series using the Kendall's Rank Correlation test to determine the direction and statistical significance of NDVI changes. Based on the Kendall's Tau (τ) coefficient and p-value (α = 0.05), pixels were classified into three categories: "greening" (statistically significant positive trend), "browning" (statistically significant negative trend), and "stable".  The comparative analysis revealed a significant and critical discrepancy between the trends identified by the two sensors. The MODIS data analysis indicated a predominant "browning" trend, with large, spatially contiguous areas of statistically significant NDVI decline observed throughout the study region. This suggested a widespread degradation of vegetation productivity. In stark contrast, the high-resolution Landsat analysis painted the opposite picture, showing a dominant "greening" trend. These positive changes were not uniformly distributed but were spatially concentrated in areas clearly corresponding to agricultural lands, forming a distinct mosaic of improvement. Despite this major conflict regarding the overall seasonal trend, both MODIS and Landsat data consistently showed a positive trend for the maximum July NDVI, indicating that peak summer vegetation productivity has been increasing across the region. It is concluded that the results derived from the Landsat archive are more representative of the actual on-the-ground biophysical changes. The discrepancy is primarily attributed to the difference in spatial resolution; the 30-meter Landsat data successfully captures field-level improvements in crop health or management intensity, whereas the coarse 250-meter MODIS pixels average these positive signals with non-vegetated or stable surfaces, masking the effect. Therefore, the primary conclusion of this study is that the Chernivtsi Raion has experienced a net "greening" over the past two decades, a process largely driven by the intensification of agricultural practices.