Modeling Vegetation Dynamics: Insights from Distributed Lag Model and Spatial Interpolation of Satellite Derived Environmental Data

The study proposes a method for modelling vegetation dynamics by combining time series analysis of the Normalised Difference Vegetation Index (NDVI) with spatial interpolation of environmental data. The goal is to provide a comprehensive understanding of how vegetation responds to changing environmental conditions by taking both temporal and spatial aspects into account. To investigate the temporal patterns of NDVI, advanced time series analysis techniques are used in the temporal domain. Distributed Lag Models, in particular, are utilised for modelling to discover the complex interactions between satellite derived NDVI and environmental factors such as Land Surface Temperature and precipitation. This method aids in assessing the delayed impacts of environmental influences on vegetation providing information on both short-term and long-term responses. Simultaneously, spatial interpolation methods are used in the spatial domain to build continuous maps of environmental variables across the study area. These spatial surfaces provide useful information on the geographic variation of environmental conditions. These findings have implications for ecosystem management, assessing climate change, and planning land use, providing a solid platform for informed decision-making in complex ecological systems.