Linear and Non-Linear Vegetation Trend Analysis throughout Iran Using Two Decades of MODIS NDVI Imagery

Vegetation is the main component of terrestrial Earth, and it plays an imperative role in carbon cycle regulation surface water/energy exchange/balance. The coupled effects climate change anthropogenic forcing have undoubtfully impacted vegetation cover linear/non-linear manners. Considering essential benefits to environment, vital investigate dynamics through spatially temporally consistent workflows. In this regard, remote sensing, especially Normalized Difference Index (NDVI), has offered a reliable data source for monitoring trend analysis. paper, two decades (2000 2020) Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13Q1) were used analysis throughout Iran. First, per-pixel annual dataset was prepared using Google Earth Engine (GEE) by averaging all available values within growing season then fed into PolyTrend algorithm identification. total, nearly 14 million pixels (44% Iran) subjected analysis, results indicated higher rate greening than browning across country. Regarding types, linear dominant type with 14%, followed concealed (11%), cubic (8%), quadratic (2%), while 9% area remained stable (no trend). Both positive negative directions observed slope magnitudes ranging between −0.048 0.047 (NDVI units) per year. Later, precipitation land employed further dynamics. correlation coefficient (NDVI) 0.54 based on corresponding observations (n = 1785). comparison trends revealed matched 60% cases, suggesting potential impact covers. Further incorporation showed that grassland areas experienced significant highest proportion compared other types. Moreover, forest cropland had direction proportions. Finally, independent (from analysis) sources examine (greening/browning) from perspectives, confirming Iran’s process agreeing results. It believed could support achieving Sustainable Development Goals (SDGs) serving as initial stage study establishing conservation restoration practices.