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.

Dust is referred to sediments of less than 100 microns in size which are transmitted as suspended particles. Dust storms are events which naturally occur in arid and semi-arid areas, especially in subtropical latitudes. One of the most known sources of dust is the west of Asia, including Arabian Peninsula, Syria, Iraq, and Iran, especially Khuzestan Province. The purpose of this study is to investigate the frequency and trend of dust phenomena on hourly, monthly, seasonal and annual scale between 1995 and 2015 in Khuzestan Province. The method in this study is based on statistical computation of dust parameters and also the trend analysis of data based on Mann-Kendall test and spatial distribution maps of dust phenomena. The results suggests that 78.57 percent of dust event are occurred between 9.30 am to 15.30 pm local time, concurrent with peak of sun radiation and earth surface warming, dryness of soil and local pressure difference. The hourly trend analysis is increasing and significant in all hours and the highest increase occurred at 9.30 pm to 12.30 pm.49 percent of dusty days occurred in June, July and May and also 73 percent of them are in spring and summer as following from temperature increase and water and soil resources drying in the province. The seasonal and annual spatial distribution of dust indicates that most of dusty days in all seasons are located in west of province which suggests dominance of external sources as the main source of dust and the importance of topography factor in this area.The Z value spatial analysis suggests high increase of dust event in recent 20 years in southeast, south and central areas of the province and also on last hours of day which demonstrator development of internal sources activities in increasing trend of dust event in recent decades.

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.