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 × 20 km2 centered at the Kandilli region of Istanbul, Turkey (28° 57′ 53″ E and 41° 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 (R2) 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.

中文翻译：

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MODIS NDVI预测的小波-ANFIS混合模型

近年来，土耳其以牺牲自然环境为代价的城市化进程不断加快。它对生态系统造成的损失对当地的天气系统和自然资源产生了不利影响。这些快速的生态系统变化主要在土耳其西部地区观察到。为了可靠地预测可持续发展规划，归一化差异植被指数（NDVI）可以作为描述城市化和土地类别的主要指标。本研究提出了最优自适应神经模糊推理系统 (ANFIS) 和混合小波-ANFIS (WANFIS) 模型来估计以 Kandilli 地区为中心的 20 × 20 km2 网格区域中某些季节（夏季和冬季）数据的 NDVI 变化土耳其伊斯坦布尔（东经 28 度 57 分 53 英寸和北纬 41 度 01 分 07 英寸）。计算的 NDVI 值是使用 WANFIS 模型获得的，并与中分辨率成像光谱仪观测值进行比较。结果表明，对于冬季和夏季测试数据集，NDVI 值的平均绝对百分比误差分别计算为 1.5% 和 0.7%。冬季和夏季测试数据集的决定系数 (R2) 值分别为 0.977 和 0.991。此外，与 ANFIS 相比，结果表明 WANFIS 模型对夏季 NDVI 变化的估计比冬季更好。冬季和夏季测试数据集的决定系数 (R2) 值分别为 0.977 和 0.991。此外，与 ANFIS 相比，结果表明 WANFIS 模型对夏季 NDVI 变化的估计比冬季更好。冬季和夏季测试数据集的决定系数 (R2) 值分别为 0.977 和 0.991。此外，与 ANFIS 相比，结果表明 WANFIS 模型对夏季 NDVI 变化的估计比冬季更好。