Sara Attarchi; Najmeh Poorakbar
Abstract
Extended Abstract
Introduction
Free access to the Landsat dataset and Sentinel 2 images has provided a great opportunity for long-term monitoring of resources. Landsat 8 was launched in 2013 to continue the mission of the previous Earth observation satellites. Landsat 8multi-spectral sensor, Operational ...
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Extended Abstract
Introduction
Free access to the Landsat dataset and Sentinel 2 images has provided a great opportunity for long-term monitoring of resources. Landsat 8 was launched in 2013 to continue the mission of the previous Earth observation satellites. Landsat 8multi-spectral sensor, Operational Land Imager (OLI), provides multi-spectral images with 30-meter resolution. Sentinel 2 was launched in 2015 with a multispectral sensor called MSI which captures images with different spatial resolutions (10m to 60m). The secret mission of Landsat satellites started in the 1970s and they have the longest archive of satellite images collected from the Earth. Sentinel 2 offers higher spatial, spectral and temporal resolutions and therefore it is important to compare the compatibility of Sentinel 2 and Landsat 8 images. OLI and MSI sensors both operate in the optical region, thus weather conditions can impose some limitations on their data acquisition. In such circumstances, data collected by a compatible and similar sensor can replace the cloud-covered images.
Generally, spectral features of new sensors are designed in such a way toconform to the corresponding bands of the previous sensors. The present study compares the corresponding bands of MSI and OLI sensors. The efficiency of both sensors in the classification of a heterogeneous and complex region has also been investigated.
Materials & Methods
Three near-simultaneous pairs of Landsat 8 and Sentinel-2 scenes were obtained to conduct a comparative study. Images were acquired in August 2017, November 2017, and July 2018.Minudasht - in northern Iran- was selected as the study area because of the presence of different land cover classes including rainfed agricultural lands, irrigated agricultural lands, forests, residential areas, and bare lands.Thescenes were processed for further analysis. First, the scenes were atmospherically corrected. In the next step, spatial resolution of MSI bands was resampled to 30 m, and each pair of mages were geometrically co-registered. To do so, 10 tie points were selected, and scenes were co-registered usingthe first-degree polynomial method. RMSE values were reported 2.5 m, 2.4 m, and 2.8 m for August 2017, November 2017, and July 2018, respectively. To investigate the similarities and differences of the sensors’ spectral content, the correlation between corresponding bands of the two sensors was estimated.
Then, images were classified using the support vector machine (SVM) algorithm. Five distinct land cover classes were found in the region including rainfed agricultural land, gardens and irrigated agricultural land, forests, residential areas, and bare lands. The training samples were selectedfromthe land use map and high-resolution Google Earth images. Approximately 300 training samples were selected for each land cover class. The accuracy of classification results was compared to verify the efficiency of two sensors in land cover mapping. Independent validation samples were selected for each class. Overall accuracy, commission error, and omission error were calculatedbased on the confusion matrices.
Results & Discussion
The reported correlation coefficientfor all corresponding bands was higher than 0.8. Results indicate a high level of similarity between the two sensors. Similar findings were reported by previous studies. Overall classification accuracy ofOLIimagescollected in August 2017, November 2017, and July 2018 was 91. 35 %, 89.60 %, and 93.12%, respectively. Overall classification accuracy ofMSI images collected inAugust 2017, November 2017, and July 2018 was 94.76 %, 95.55 %, and 94.07%, respectively. As it is obvious, Sentinel 2showed a higher performance in comparison to Landsat’s, because of its higher spatial resolution. A medium spatial resolution image collected from a complex landscape is often composed of mixed pixels, since different land cover types exist in one pixel. As the image’s spatial resolution improves, the dimensions of each pixeldecrease. Therefore, the number of mixed pixels will decrease and a higher classification accuracy will be expected.
Conclusion
Results confirm the similarity of two sensors in land cover classification. However, the findings could not be extended to other applications. MSI sensorslacka thermal bandand thus are not applicable when such a feature is needed (for an instance inthe retrieval of land surface temperature). In such applications, MSI cannot substitute OLI. For further studies, it is necessary to compare the performance of these sensors in different regions, since different land cover types may impactclassification results. Findings of the present study may raise attention to the differences between Landsat 8- OLI and Sentinel 2 MSI. Further studies can be conducted to investigate the differences between these two sensors. The possible similarities of othersimilar sensors can also be a topic for further investigations.
Seyed Saeid Nabavi; Hamidreza Moradi; Mohamad Shrifikia
Abstract
Extended Abstract Introduction There has been an increase in the occurrence of dust storms in the Middle East in recent years. The World Meteorological Organization has introduced dust storms as the result of atmospheric turbulence, which injects a large amount of dust into the atmosphere and makes the ...
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Extended Abstract Introduction There has been an increase in the occurrence of dust storms in the Middle East in recent years. The World Meteorological Organization has introduced dust storms as the result of atmospheric turbulence, which injects a large amount of dust into the atmosphere and makes the horizontal visibility less than 1000 meters. Iran is involved in dust storms due to its geographical location and weather conditions. Long-term evaluation of statistical data, identifying the origin and routing dust storms can be effective in identifying the time and location of this event. Materials & Methods In this research, the temporal distribution of Khuzestan dust storms from 2000 to 2015 was investigated at five synoptic stations including Ahvaz, Abadan, Aghajari, Safi Abad and Mahshahr. Given the World Meteorological Organization’s codes on the dust storm incidents, and in order to minimize human error, the information related to the event was extracted using the Linux operating system. Furthermore, Mann-Kendall test and Pearson and Spearman correlation coefficients were used to evaluate the trend of the temporal changes of dust storms and the rate of the correlation of the effective factors with the frequency of dust storm occurrence, respectively. Regression models were used to determine the rate of the effectiveness and the prioritization of the factors affecting storms. The entire statistical analyses were performed using the SPSS 20 software. Results & Discussion According to the results obtained, out of 1507 recorded dust storms, the Ahvaz station with 509 (34%) and the Aghajari station with 156 (10%) recorded events, have had the highest and the lowest number of recorded dust storms, respectively. The temporal variations trend of dust events at the study stations was not significant at the 1 and 5% levels. However, the frequency of dusty days in the Ahvaz and Abadan stations was positively correlated with the frequency of days with the region’s prevailing wind speed and direction at the 99% confidence level (p<0.01). There was also no significant correlation between soil texture and type. The results of linear regression model showed that there is a positive relationship between the frequency of dusty days with the frequency of days with the region’s prevailing wind direction at all stations at the 99 and 95% levels. Based on the standardized regression coefficient, at most stations, the occurrence frequency of the prevailing wind at the study stations has the highest impact on the occurrence frequency of dust storms. Conclusion: About 65 percent of dust events have occurred in two cities of Ahvaz and Abadan, located in the center and southwest part of the Khuzestan province. This could be due to the further proximity of these two stations to the local and regional dust sources. Another reason could be the flow of atmospheric circulations in different regions of the province. In this regard, the northwest-southeast winds which carry dust, hit Ahvaz and Abadan more frequently. The highest number of dust storms were recorded during summer and spring. A downward trend of dust events has been observed at all studied stations since 2008. Nevertheless, the problems caused by this event have become more apparent and have affected the lives of people. For this reason, the general view is that the number of dust storm events has increased. The high concentration and the higher persistence of dust storm events could be the reason of such an idea as well. These possible causes could be addressed in future studies in analysis and control of dust storm events.
Hamed Eskandari Damaneh; Gholam Reza Zehtabian; Hassan Khosravi; Al Azareh
Abstract
Drought is a recurring and temporary natural event which leads to many damages to human life and natural ecosystems. In this study, the Standardized Precipitation Index (SPI) and Stream flow Drought Index (SDI) were used to assess droughts. For this purpose, monthly statistics of 72 rain-gauge stations ...
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Drought is a recurring and temporary natural event which leads to many damages to human life and natural ecosystems. In this study, the Standardized Precipitation Index (SPI) and Stream flow Drought Index (SDI) were used to assess droughts. For this purpose, monthly statistics of 72 rain-gauge stations and 42 hydrometric stations were used in Tehran province and drought indices of SPI and SDI were calculated in the matlab software. In the next stage, their zoning maps of these indices were prepared using ArcGIS software in different periods and the relationship between the two drought indices was obtained using the Pearson correlation coefficient. The results of this study showed that the drought trend has been increased over time in different parts of the province. Also, there was a significant relationship (at confidence level of 99%) between meteorological drought and hydrological drought in the area. The results show that the extent of drought has been increased over time and from north to south of the province. Based on rainfall and discharge data, the occurrence of meteorological drought, either as instantly or with a time delay of one month, has the highest impact on the hydrological drought. Also, the study of the spatial order showed that the highest correlation between meteorological drought and hydrological drought was found in Roudak station because of the small size of its upstream basin compared to position of its rain-gauge and hydrometric stations.
Hossein Asakereh; Soheila Maleki
Volume 20, Issue 78 , August 2011, , Pages 7-12
Abstract
Temperature and precipitation are two important climatic variables that have a significant effect on life and activities of individuals. These two elements are generally dependent on each other. In this research, the correlation between temperature and precipitation is determined using Pearson correlation ...
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Temperature and precipitation are two important climatic variables that have a significant effect on life and activities of individuals. These two elements are generally dependent on each other. In this research, the correlation between temperature and precipitation is determined using Pearson correlation coefficient. The existence or absence of a linear relationship between temperature and precipitation was also examined. Furthermore, the simultaneous effect of temperature and relative humidity on rainfall was calculated and the significance of regression was investigated. In this study, SPSS software was used for drawing graphs and multivariate regression analysis. Using the findings of this research, it was shown that there is a weak inverse relation between temperature and precipitation. The actual contribution of temperature changes in precipitation is 3.61% which is very low, and there is no linear relationship between temperature and precipitation. In the two-variable regression, the temperature had again no significant effect on rainfall, but relative humidity was an effective variable in precipitation of this station. In this study, the mean annual temperature and precipitation of Zanjan station, extracted from the meteorological website, have been used during the statistical period of 1956-2005. Zanjan is located on the northern 36o41’ and eastern 29o48’ in the northwest of Iran. The city’s altitude at the station is 1620 meters.
Mehrdad Hosseini; Reza Borhani; Maryam Khattar
Volume 15, Issue 58 , August 2006, , Pages 22-27
Abstract
In this research, in order to investigate the frosts occurred at Ekbatan station (Hamedan), the minimum daily temperatures of this station were studied. In general, the frosts were divided into three weak (mild), moderate, and severe categories. Next, the range of changes in the time of occurrence of ...
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In this research, in order to investigate the frosts occurred at Ekbatan station (Hamedan), the minimum daily temperatures of this station were studied. In general, the frosts were divided into three weak (mild), moderate, and severe categories. Next, the range of changes in the time of occurrence of these frosts was determined and the frequency of their occurrence was calculated. It was also attempted to obtain an experimental formula for the first autumn frost in a particular year based on the date of the last frosts of the spring of that year, and to determine the probability of occurrence of temperature thresholds between 0 and -15 ° C in different months of year by calculating different statistical parameters. In addition, it has been tried by dividing the the year into 36 distinct decades (ten days) to calculate the temperatures that are possible to occur with different percentages of probability.
