SPATIO-TEMPORAL CHANGE MODELING OF LULC: A SEMANTIC KRIGING APPROACH

摘要: Spatio-temporal land-use/ land-cover ( LULC ) change modeling is important to forecast the future distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal in trend often exhibits non-linear behavior, due various dynamic factors, such as, human intervention (e.g., urbanization), environmental Hence, proper forecasting of distribution should involve study and historical data. Existing literatures have reported that meteorological attributes NDVI , LST MSI ), are semantically related terrain. Being influenced by terrestrial dynamics, temporal changes these depend on properties. incorporating knowledge into prediction process help developing an accurate model. This work attempts inter-annual pattern different a region Kolkata (a metropolitan city India) during years 2000-2010 spread using semantic kriging SemK approach. A new variant time-series proposed, namely Rev-SemK ts capture multivariate associations between attributes. From empirical analysis, it be observed augmentation more precise pattern.