علوم زیستی دریا
Davood Mafi-Gholami; Abolfazl Jaafari
Abstract
This study investigates changes in the integration status of mangroves of Hara Biosphere Reserve in the face of changes of rainfall and drought occurrences over a 31-year period (1986-2017). For this purpose, the 31-year time series of satellite images and precipitation data were used and the values ...
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This study investigates changes in the integration status of mangroves of Hara Biosphere Reserve in the face of changes of rainfall and drought occurrences over a 31-year period (1986-2017). For this purpose, the 31-year time series of satellite images and precipitation data were used and the values of the number of patches (NP) and the largest patch index (LPI) as well as the SPI valueswere obtained during the period. The results of the change in the number of patches and the largest patch index with the change in the pre1998 (wet period) and post-1998 (dry period) showed that with increasing SPI values (positive values) in the pre-1998 period (wet season), the number of patches and the index of largest patch decreased and in the post-1998 (drought period) the negative SPI values increased the number of patches and the index of the largest In fact, the results showed an increase in the size of the main cores and large vegetative patches (increased structural integrity) of the Reservoir during the wet season and its reverse trend during the drought period. According to the principles of landscape ecology, an increase in the number of patches and in the index value of the largest patch (due to a decrease in the total area of the habitat) in the post-1998 period indicates the destruction of this habitat in recent years. The results of this study are of value to assess the vulnerability of these habitats to the consequences of climate change.
علوم زیستی دریا
Mojdeh Miraki; Hormoz Sohrabi; Sima Sadeghi; Parviz Fatehi; Markus Immitzer
Abstract
Advances in remote sensing enable fast mangrove mapping the less need for intensive fieldwork, complex and heavy processing, and skill-based classification techniques. In this research, mangrove forest mapping was performed using Sentinel-2 satellite images in Google Earth Engine (GEE) in Hormozgan province ...
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Advances in remote sensing enable fast mangrove mapping the less need for intensive fieldwork, complex and heavy processing, and skill-based classification techniques. In this research, mangrove forest mapping was performed using Sentinel-2 satellite images in Google Earth Engine (GEE) in Hormozgan province in three ecosystems of Qeshm, Khamir, and Sirik. For this purpose, all steps of mapping these forests, including pre-processing and classification were performed in the GEE. The Modular Mangrove Recognition Index (MMRI) and classic spectral indices were also used to highlight the spectral differentiation of mangrove cover from the surroundings. To classify the image of the study area, three land cover classes were used: mangrove, non-mangrove, and sea (water). The classification was performed based on the random forest algorithm and accuracy assessment was evaluated in R software based on the K-fold validation method. The Qeshm site was demonstrated the highest accuracy among the three ecosystems with an overall accuracy of 98% and a kappa of 0.73. Khamir and Sirik sites were shown an overall accuracy of 97% and a kappa value of 0.71 and 0.70, respectively. The MMRI index was the most important variable in the RF classification in Qeshm and Khamir, while in Sirik, the SAVI index was the most important spectral index in mangrove map providing. The overall accuracy of over 95% at all three sites indicates that combining Sentinel-2 data using appropriate indices in the GEE is an effective approach to mangrove forest mapping
علوم غیرزیستی دریا
Yasaman Gandomi; Ahmad Savari; Babak Doustshenas; Saleh Arekhi
Abstract
The increasing application of remote sensing for mangrove mapping and monitoring is practical for sustainable management of the biological resources. The emergence of several vegetation indices (VIs) has certainly given significant impacts on mangrove and other forest mappings. In this study, four different ...
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The increasing application of remote sensing for mangrove mapping and monitoring is practical for sustainable management of the biological resources. The emergence of several vegetation indices (VIs) has certainly given significant impacts on mangrove and other forest mappings. In this study, four different vegetation indices including Normalized Different Vegetation Index (NDVI), Simple Ratio (SR), Soil Adjusted Vegetation Index (SAVI) and Triangular Vegetation Index (TVI) were compared to discover a suitable vegetation index for identifying mangrove area in Nayband bay, Boushehr, Iran and using landsat imagery with 30-m from 2012. Maximum Likelihood Classifier (MLC) was used to classify Mangrove and NonMangrove area. The results demonstrated that the best accuracy (96.85%) was from combination between 7 landsats spectral bands and some vegetation indices including NDVI and SAVI.
علوم غیرزیستی دریا
Ataollah Abdollahi Kakroodi; Leila Amini; Mahdi Hasanlou
Abstract
In order to study in shallow coastal areas, free Landsat 8 image with relatively high radiometric resolution and the presence of two bands, coastal blue and blue is suitable. In this study, in addition to Landsat satellite imagery, hydrographic data has also been used. In order to increase the accuracy ...
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In order to study in shallow coastal areas, free Landsat 8 image with relatively high radiometric resolution and the presence of two bands, coastal blue and blue is suitable. In this study, in addition to Landsat satellite imagery, hydrographic data has also been used. In order to increase the accuracy and reduce the error, tried as much as possible the passing time of the Landsat 8 sensor close to the acquisition terrain date. The purpose of this study is bathymetry of the southeastern part of the Caspian Sea using the PCA algorithm on the pre-processed visible region. In this study, the FLAASH and Dark Object Subtract (DOS) atmospheric corrections were applied separately to visible bands. The obtained depth results by applying PCA transformation to these two types atmospheric correction is investigated. PCA algorithm is implemented in four different forms. Statistical parameters R^2, RMSE, and NRMSE are calculated between obtained data by PCA and hydrographic data in two types of atmospheric correction. The results show that in both of atmospheric correction, the accuracy of estimated depth by PCA is increased when four or three PCA components are introduced as algorithm inputs compared with only two or one PCA components are used. As well as, the use of four components, the accuracy of DOS in bathymetry with values of R2=0.91, RMSE=0.3,and NRMSE=0.05 has shown a better result in comparison to FLAASH correction's values R2=0.87, RMSE=0.38, and NRMSE=0.06.
علوم غیرزیستی دریا
Mohammad Akbarinasab; Hajar Karami; Taher Safarad
Abstract
For this study different time series of MODIS level-3 thermal IR SST data from 2013-2014 has been processed and thermal fronts the of Persian Gulf and the Oman Sea (47.6°E to 67.7°E and 18°N to 31°N) region mapped using the method, the Canny algorithm and Gaussian filter. Monthly thermal ...
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For this study different time series of MODIS level-3 thermal IR SST data from 2013-2014 has been processed and thermal fronts the of Persian Gulf and the Oman Sea (47.6°E to 67.7°E and 18°N to 31°N) region mapped using the method, the Canny algorithm and Gaussian filter. Monthly thermal front images of this region are mapped during the period of January 2013 to June 2014 are classified into Summer Monsoon (June, July, August, September), Winter Monsoon (October, November, December, January) and Pre Monsoon (February, March, April, May) periods and their characteristics are discussed here. The results show that high frequency of SST fronts were observed in the Oman Sea and Persian Gulf in October, November, December, January and May in 2013 year and January, November and December in 2014 year. The number of fronts increases since the beginning of winter to early spring and the beginning of fall, too. The remaining these fronts move with current toward the Arabian Sea and Indian Ocean at the beginning of the summer monsoon. Sustainable and cohesive front was seen near the Arvand River in the Persian Gulf that is presents in the cold months more. This front will disappear in the months of July, August and April 2013 and 2014. The other stable front is in the Oman Sea in southern Afghanistan. Most of the front are presenting in the warmer months of June, September, October in 2013 and in June, August and October in 2014.
مهندسی دریا
khosro fazelpoor
Abstract
In order to provide SST images, the sensor MODIS installed on Aqua Satellite EOS-1 was used. Applying lighting assessment out of images from Modis 21-Level 1B Calibrated Radiances -1km in Persian Gulf and the Bushehr sea station (Bouyeh) from global algorithm specified for above sensor was used to estimate ...
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In order to provide SST images, the sensor MODIS installed on Aqua Satellite EOS-1 was used. Applying lighting assessment out of images from Modis 21-Level 1B Calibrated Radiances -1km in Persian Gulf and the Bushehr sea station (Bouyeh) from global algorithm specified for above sensor was used to estimate the sea surface temperature. With function of Matlab software to extract data of satellite images, and GIS software to convert the matris obtained, the maps of sea surface temperature were used. Forty eight images taken in 2008, 2009, 2012, and 2013 were selected. Their correlation coefficient eventually was 0.75, 0.86, and 0.75 respectively. Likewise the special coefficient obtained as 0.86, 0.90, 0.94 and 0.86 respectively. Finally, taking the 31 band temperature into consideration for the years 2008, 2009, 2012 and temperature differences of bands 31 and 32 and the sensor angle as independent factors were used at Bouyeh temperature as an affiliated factor calibrated by SPSS software for global algorithm of Persian Gulf. In order to check the correctness the algorithm suggested, the sea surface temperature was re-examined with satellite images of the year 2013; the correlation coefficient 0.96 and 0.94 were obtained. The searching has shown that the depth with current sea and latitude have effect on sea surface temperature, and temperature balance specially in north and central latitude have contrary relation with depth.
علوم زیستی دریا
m m
Abstract
Nowadays, because of bad urban, agriculture and industrial management many of water resources suffer quality issues. Remote Sensing play a key role in water quality assessment and management. Many of pollutions can be observed using remote sensing images, so it can be a very useful tool for water resources ...
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Nowadays, because of bad urban, agriculture and industrial management many of water resources suffer quality issues. Remote Sensing play a key role in water quality assessment and management. Many of pollutions can be observed using remote sensing images, so it can be a very useful tool for water resources management. Because of wide spreading of water bodies, field work cause to increase in time and cost of studies, so using satellite images can be an alternative. Quality monitoring such as salinity, water color, suspended sediment may measured using satellite images. For assessing Water Quality, some empirical relations should be found to relate water quality to one or some spectral bands. Water Quality parameters such as color, chlorophyll, Suspended Sediment and Salinity may be assessed using Remote Sensing techniques. Remote Sensing can be used for assessment and monitoring algal concentration in lakes and water resources. Increase in chlorophyll cause to reduction in Blue band reflectance and increase in Green band reflectance. For assessing Water Quality, some empirical relations should be found to relate water quality to one or some spectral bands. In this study, Chl-a, concentration of Tripton and Turbidity of a small part of the Persian Gulf was estimated applying a bio-optical model.
علوم زیستی دریا
a b; h m; a d; h e; s kh
Abstract
Atmospheric dust particles originating in the arid and semi arid regions of the world are known to be principal sources of mineral dust. The use of satellite remote sensing dust, the potential of this technique is created to provide valuable information to assist in the design of network measurement ...
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Atmospheric dust particles originating in the arid and semi arid regions of the world are known to be principal sources of mineral dust. The use of satellite remote sensing dust, the potential of this technique is created to provide valuable information to assist in the design of network measurement and estimation dust in marine environments. Dust deposited provides key nutrients such as iron to oceanic phytoplankton. Aerosol optical depth were reviewed in the study between March 2008 and December 2013 in the Persian Gulf. Aqua and Terra satellites for the MODIS sensor data as well as aerosol data (PM10) and Environmental stations and optical depth stations AERONET, used to evaluate the aerosol optical depth. The results showed that the data of MODIS AOD has acceptable accuracy and very high correlation between the values measured by MODIS and network AERONET, there (correlation coefficient: 90/0). Comparison between AOD values derived from measurements by satellites Aqua and Terra MODIS sensor and the amount of aerosol (PM10) estimated environmental stations in the Persian Gulf region also took place. The results showed that between these two values correlated to the Aqua and Terra satellites in the study area, and the correlation coefficient was greater in summer than winter. The results of this study showed that the optical depth data from the MODIS satellite images can provide accurate information dusts the Persian Gulf.
علوم غیرزیستی دریا
Hosein Farjami; Mohammad Taghi Zamanian,; Akbar Rashidi Ebrahim Hesari,; Seiied Ali Azarmsa,
Volume 11, Issue 1 , November 2012, , Pages 41-48
Abstract
Wind is a major factor which induces oceanic currents and many theories including the Ekman theory have considered the wind induces currents. In this paper a numerical process has been used for forecasting of oceanic currents based on this theory. The survey has been done in an artificial five layer ...
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Wind is a major factor which induces oceanic currents and many theories including the Ekman theory have considered the wind induces currents. In this paper a numerical process has been used for forecasting of oceanic currents based on this theory. The survey has been done in an artificial five layer oceanic basin with smooth bottom of 120 meters, considering the geographic position of Persian Gulf. Primitive equations were solved on earth’s spherical coordinates system with sigma as vertical coordinate by finite element method. Vertical profile of predicted current vectors showed the complete formation of Ekman Spiral in the basin. This experimental simulation is a new approach for confirmation of Ekman Theory.