جستجوی مقالات مرتبط با کلیدواژه "pearson correlation" در نشریات گروه "اکولوژی"

Dust storms are natural phenomena but with serious and destructive effects on the environment and human societies. The southeast region of Iran is one of the most active sources of dust storms in Asia, dust storms occur in this region almost all year round, but their frequency is higher in summer and spring. This study aims to investigate the dust storm anomaly in the southeast of Iran during a period of 21 years (2000-2020) and its relationship with vegetation anomaly changes. The DSIA was used to examine the spatial and temporal changes of dust storms, and the NDVIA was used to examine the changes in vegetation anomalies in the region. The correlation between DSIA and NDVIA was determined by using Pearson's coefficient. The temporal trends of DSIA show that from 2000 to 2012, it had a positive and increasing trend in most of the years of the study, and the highest value of DSIA occurred in 2012, which is equal to 96%. Then, from 2012 to 2020, this trend has been decreasing, and the lowest value of DSIA equal to -67% was observed in 2020. Also, moving from east to west of the studied area, the value of the DSIA decreased. The temporal trends of the NDVIA show that from 2000 to 2012, the trend of changes is downward, but from 2012 to 2020, the trend of changes is upward. In terms of time, the highest value of the NDVIA index is related to 2014, and in general, since 2012, this index has had positive and increasing changes. Pearson correlation results showed that the DSIA index is significantly correlated with the NDVI index, this correlation is negative (p-value<0.05 r=0.52) due to the negative and significant correlation between the NDVIA index and the DSIA index. Since 2012, with the increase of the NDVIA index and the improvement of vegetation conditions, the DSIA index has decreased. The effect of this correlation was also observed spatially, as moving from east to west of the region, with the increase of the NDVIA index, the amount of DSIA decreases. These results can be useful for decision-makers to assess the risks of dust storm impacts and reduce its negative consequences in the southeast parts of Iran.

Chlorophyll-a concentration is among the most important parameters used to investigate the primary production in marine ecosystems. Chlorophyll-a concentration is influenced by climatic/environmental factors, including Sea Surface Temperature (SST). Satellite sensors are able to provide reliable products of chlorophyll-a concentration and SST data with an adequate spatiotemporal resolution. In this study, level 3 (resolution 4 km) MODIS monthly products of chlorophyll-a concentration and SST  from year 2003 to 2018 of the Persian Gulf and the Oman Sea were used. The data were transformed into a raster format and the values of each pixel were extracted. Several gaps were observed in MODIS products of chlorophyll-a concentration. The Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm was used to reconstruct these gaps. Pearson correlation procedure was applied to analyze the correlation between chlorophyll-a concentration and SST. Results showed that during the study period, the correlation between the two parameters was negative (-0.44 to -0.67) and significant in the most part of the study area. The correlation coefficients in December were negative (-0.67 to -0.05) and significant in the Oman Sea and the most areas of the Persian Gulf, while in July those relationships were mostly positive (0.13 to 0.64) and significant.