SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA
Keywords: Remote sensing, LANDSAT, Google Earth Engine, Grassland, Pasture, NDVI, Mann-Kendall test
Abstract. Proper management and monitoring of the ecological condition of natural feeders are crucial for both the economy and natural environments. Armenia is no exception, and addressing this issue requires comprehensive studies combining traditional methods with remote sensing technologies. Remote sensing in agriculture utilizes various sensors and technologies to collect data about crops, soil conditions, and agricultural parameters from a distance. This study focuses on the utilization of remote sensing, including satellite imagery, to assess the ecological state of grasslands and pastures in the Syunik administrative district of Armenia. Over a 22-year period (2000–2021), the study utilized Landsat series (5,7,8) multispectral optical images processed through Google Earth Engine (GEE) to analyze changes in the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation health. The results reveal favorable trends in vegetation health across the study regions, as indicated by consistently positive Z-values in the Seasonal Mann-Kendall test. While no significant trends were observed in some areas, others showed improvements in biomass conditions. This study provides valuable insights into the resilience and health of grasslands and pastures in the Sisian and Goris regions, offering a basis for targeted interventions and strategies to preserve these ecosystems for future generations.