Decline phenomenon is one of the most important reasons for the destruction and mortality of oak trees in Zagros forests due to the wide variety and diversity of the topography of its determination through track and field operations is not readily possible. Changes in an ecosystem are often gradual changes, but sometimes changes occur in an ecosystem in a short time. This change can cause a catastrophe in the ecosystem, which is difficult to identify. A proposed method for identifying a general change in time series is use the BFAST model, which, by analyzing the time series in the process, season, and residual components, identifies the changes in the time series and also repeatedly estimates the time and amount of the changes, and The path and amount of variation in this study, using this model and satellite images to monitor and evaluate the changes in coverage and decline of oak forests in Lorestan province during the statistical period (2000-2017). The results showed that more than 42804 hectares (1.5%) of the oak forests of the province were lost due to the decline phenomenon during the studied period. Also, according to the BFAST method, the trend diagram is a failover and their frequency variations are irregular. Comparison and study of different forest coverings also showed a decrease in NDVI, which indicates that the process of decreasing forest cover is inclusive. The study of autocorrelation and Kendal coefficient showed that there were significant changes and severity of failure (-0.7) in the area Study. The seasonal chart also has uneven and irregular variations due to changes in oak forests in the region. The results of this research can be used to study the changes in the coverage of oak forests in the area and management and the way to think about this phenomenon.

The purpose of this study is to determine and predict the effects of climate change on architecture using climate models. By clarifying the consequences of the impact of urban architecture on climate change while using the data of surrounding stations with library and field data methods. The climatic parameters of precipitation, temperature and relative humidity of the synoptic station of Miyaneh city during a full period of 32 years (2018-1987) and the possibility of climate change with the models in this city were examined and after obtaining the relevant data Climate change was predicted for the next 84 years through the GCM and SDSM microscale and the AR4 (2007) - HADCM3 (Run 1) - SR-A2 scenarios. In order to evaluate the effects of climate change on the comfort climate of the region, among the bioclimatic models used, the Tarjong model was considered for two periods of 16 and 42 years. In the next 84 years, compared to the last 32 years, the cold months of May, June, July and August will turn into pleasant heat, and in September, the heat will have a great impact on the skin, which indicates a warm climate in the next 84 years. Architectures must be considered.