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        Predicting ecosystem shift in a Salt Lake by using remote sensing indicators and spatial statistics methods (case study: Lake Urmia basin)

        Nadia Abbaszadeh Tehrani,Milad Janalipour 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.4

        The consequences of unsustainable human activities on the environment are often delayed, when it is too late to compensate. New approaches are based on the use of “spatial statistics” of leading indicators to measure the “critical slowing down” in a degraded ecosystem, when it is reaching to a tipping point. This research predicts the tipping points in the ecosystem of Lake Urmia Basin (LUB) based on spatial statistics. By Remote Sensing (RS) indicators, their effectiveness in assessing the state of the ecosystem was evaluated in a 16-years period (2002-2017). Seven spectral indicators (NDVI, NDWIv,NDWIw,NDSI,SRDI, NMDI and MVWR) were extracted from ten MODIS images. Ability of the indicators to identify critical point in time-series was investigated by five spatial statistic methods (Moran’s-I, Getis-Ord-Gi, Geary’s-C, variance, and skewness). The results showed that Moran’s-I is more successful in predicting the ecosystem tipping point(s) in comparison with other methods. In addition, the ability to predict ecosystem trends by the autocorrelation of MVWR is higher than other indicators. According to results, the tipping points of LUB occurred in the years of 2008 to 2010 and 2015. For further studies, it is recommended to use radar indicators for identifying tipping points of the similar vulnerable ecosystems.

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        Investigating effect of COVID‑19 on NO2 density using remote sensing products (case study: Tehran province)

        Nadia Abbaszadeh Tehrani,Farinaz Farhanj,Milad Janalipour 대한공간정보학회 2022 Spatial Information Research Vol.30 No.4

        The first case of COVID-19 was detected in Iran on February 19, 2020. From the beginning of the pandemic, some restrictions have been imposed to reduce the spread of the pandemic, which have led to the reduction or temporary closure of some industrial, construction, and transportation sectors. These sectors are typically some sources of pollutants induced to the atmosphere. The purpose of this study was to investigate the impact of the restrictions caused by the pandemic, on the concentration of nitrogen dioxide ( NO2) in the atmosphere of Tehran province. Average daily and monthly NO2 concentrations from the TROPOMI sensor of Sentinel-5P satellite before and after the pandemic (i.e., February 20 to August 19, 2020, and February 20 to August 19, 2019) were used. The results showed that the average NO2 concentration in the mentioned period in 2020 was equal to 168.09 μmol/m2, which compared to 2019 (195.11 μmol/ m2), had a decrease of 13.85%. Therefore, the imposed restrictions to reduce the prevalence of COVID-19 in Tehran province have an impact on the temporary decrease in NO2 concentration. It is recommended that after the end of the pandemic and the reconstruction of economic and industrial activities, measures will be taken to monitor the urban environmental loads and improve the air quality.

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