Wavelet-ANFIS hybrid model for MODIS NDVI prediction

Abstract

Urbanization at the expense of the natural environment has been increasing in Turkey in recent years. The toll it takes on the ecosystem has an adverse impact on local weather systems and natural resources. These rapid ecosystem changes are mostly observed in the western parts of Turkey. For a reliable prediction of sustainable development planning, the normalized difference vegetation index (NDVI) can be used as the main index for the description of both urbanization and land class. This study proposes the optimum adaptive neural-fuzzy inference systems (ANFIS) and hybrid Wavelet-ANFIS (WANFIS) models to estimate NDVI variation for certain seasonal (summer and winter) data in a grid area of 20 x 20 km(2) centered at the Kandilli region of Istanbul, Turkey (28 degrees 57' 53 '' E and 41 degrees 01' 07 '' N). The calculated NDVI values were obtained using the WANFIS model and compared with the Moderate Resolution Imaging Spectroradiometer Observations. The results reveal that the mean absolute percentage error of NDVI values are calculated as 1.5% and 0.7% for the winter and summer test datasets, respectively. The coefficient of determination (R-2) values of the winter and summer test datasets are 0.977 and 0.991, respectively. Further, when compared with ANFIS, the results demonstrate that the WANFIS model exhibits a better approximation for the estimation of NDVI variation in the summer than in the winter. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)