Ecosystem productivity, biome distribution, and forest carbon stocks are likely to be changed by the climate change. These ecosystems changes can be identified using Satellite based normalized difference vegetation index (NDVI). In this study, global inventory modeling and mapping studies (GIMMS) NDVI data acquired by the advanced very highresolution radiometer (AVHRR) was used for analyzing the trend over Turkey for the period 1982-2015. The acquired data has bi-monthly nature, and the maximum value of composite method was used for finding monthly NVDI. The obtained NDVI was then clipped to the study area, and then the trend was estimated using Annual aggregated time series (AAT) and seasonal adjusted time series (SAT) methods. In AAT method the annual averages were calculated and then the trend was estimated. In SAT, the seasonal component removed from the time series and the seasonal adjusted time series used for estimating the trend. The gradient latitudinal and longitudinal trend was also implemented to investigate the spatial trend. The gradient was calculated as the trend of the blocks of a specific latitude of longitude over the whole Turkey to have better interpretation of the spatial trend from south to north and east to west. The results showed that throughout Turkey the NDVI has an increasing and decreasing trend, but the increasing trend is dominant as 89.9% and 79.1% of the total area using AAT and SAT respectively are significant increasing trend. One the other hand, only 0.45% and 0.36% of the total area has significant decreasing trend using AAT and SAT respectively and the rest of the area has no significant trend. The seasonal adjusted method showed most of the no trend areas is distributed through the eastern part and the far western part of Turkey. The Annual aggregated trend showed similar pattern with largest no trend area centered in the far eastern part of Turkey. The gradient analysis showed decreasing in the magnitude of the positive NDVI trend when moving from the west to the east, and no specific pattern in the south north direction.