جستجوی مقالات مرتبط با کلیدواژه « تغییرات خط ساحل » در نشریات گروه « جغرافیا »

Coastal environments are one of the most sensitive environmental systems under the influence of dominant hydrodynamic processes. Coastal changes and evolution are occurring very fast. Coastal areas are now gradually becoming known as severe natural and man-made disturbances, including sea levels rising, coastal erosion and sedimentation, and over-exploitation of resources. A deep understanding of the regionchr('39')s coastline dynamics (erosion and sedimentation) is essential for the proper planning, land use, and conservation strategies to reduce potential losses. Development of the southern coast of Iran has not only destroying the geomorphological landforms but also led to a change in the process of erosion and sedimentation in coastal areas. Understanding the behavior of the coastline would assist the management and planning of coastal facilities construction and determining the margins of the coast. Today, remote sensing methods, while being economical and promoting high accuracy, make it possible to continuously observe and manage beaches. These benefits have led to the increasing use of satellite imagery to determine the accurate position of the coastline in the world. The goal of this research is the investigation of periodic change of the Oman sea coastline from 2000 to 2109 using the Landsat time-series dataset.

The study area in this article is related to the coastal line between Gwatr port and the Strait of Hormuz. The years of 2000, 2009, and 2019 were selected for the periodical coastal changes analysis in the last two decades. According to the time interval, the images of two Landsat 5 and 8 sensors were selected. The numbers of images that were mosaiced in each period are 15 scenes. Then, to discrete the water and land border, the modified normalized difference water index (MNDWI) in ENVI 5.3 software was used. This indicator is a combination of Green and Mid-Infrared bands. After applying the water and land boundary discrimination index, shoreline digitization in ArcGIS software has been done manually and with high accuracy. Thus shoreline from satellite images extracts by the Digital Shoreline Analysis System (DSAS). This method calculates the shoreline mobility and its changes based on satellite imagery. DSAS v4.3 is an extension developed by the US Geological Survey, which is adding to the ESRI ArcGIS 10.3 software. It is calculated the number of shoreline shifts from the past to the present. In this study, shoreline shifts are calculated using four data analysis methods (e.g., EPR, LRR, LMS, and NSM).

Identification of erosion and sedimentation transects indicates that the shoreline has been progressing ahead in most areas of coastline. During the last twenty years, 172.47 km of coastline length increased which is indicated by coastline sedimentation. These changes are apparent in most transects; 49% of transects were sediment, and 36% were erosive transects. The highest progress of coastlines observed in the Yekboni estuary (river mouth) area, western Jask Kohneh area which the sedimentation rate has reached 295.25 m/y. The sedimentation rate in the area of Chakha estuary, Gurdim, Gwadar port, and Bahu estuary has been above 100 meters per year. Also, the area between Brys to Pasabander and the upper area of Gashmi and Kartan estuaries has been high. The reasons for this can be attributed to the dock construction and the large volume of sediment in the estuaries by rivers. The highest amount of erosion rate in the nose of Jask port was 178.15 meters per year. The construction of stone walls in this area is the main cause of severe erosion. The length of the coastline in the year 2000, 2009, and 2019 were 1228.54, 1397.56 and 1394.08 km, respectively. The change of beach length is observed from 2000 to 2009; 169 km, from 2009 to 2019; 3.47 km, and from 2000 to 2019; 172.47 km.

The nature of coastlines is dynamic; therefore, the management of such sensitive ecological environments requires accurate time-series data. In this research, Landsat satellite imagery of TM and ETM sensors in the three periods of 2000, 2009, and 2019 have been used to detect shoreline changes. Coastal changes and spatial analysis are extracted by using the DSAS Extension in ArcGIS software. The length of the coastline in the year 2000, 2009, and 2019 were 1228.54, 1397.56, and 1394.08 km, respectively. Maximum sediment/erosion rates have been observed 290.25 and -178.15 m per year in the Yekboni estuary area and the cape of Jask port respectively along the coast of the Oman Sea. During twenty years, the eroded areas have experienced a recession, an average of 11.28 meters per year. The reasons are the rocky shores of the Oman Sea, desert landforms of some beaches and their exposure to severe wind erosion, dunes movement, and human activities. The areas of the coast where sedimentation was higher had an average of 9.74 meters per year. Human activities such as port construction and large volumes of sediment at the mouth of rivers have caused part of the coast to move toward the sea. In general, 36% of the study area has been eroded, and 49%  has been more sedimented. Remote sensing and geological techniques with DSAS will be useful methods for monitoring long-term coastal changes and provide a comprehensive view of coastal erosion and sedimentation patterns. Continuing the coastline monitoring is necessary to observe future changes and is economically significant.

Introduction; Of important geomorphological characteristics of Uremia Lake is instability coastline. The salinity Phenomenon and Genesis crust of salt in the coastal lands is of the manifestations of this is the use, season. Monitoring the coastal areas and Extraction the water level changes in, different time, considered as fundamental research, because nature of coastline is dynamic and the management of such Sensitive ecological environments needs to earn detailed information in Different time intervals. For this purpose, Remote Sensing Technology has unique application uses information from these phenomena. Because multispectral satellite images have benefits and advantages that availability and this Digital interpretation is their most important. The overall objective of this study, was to evaluate the processes The governing on Dry environment and the hydrodynamic evaluate of lake in determining lake shoreline changes using the Landsat satellite images MSS, TM5, ETM 7 and OLI in period of 39 years (1976- 2015) and then is evaluate the effect these changes on amount of salt deposits around the lake.
In this study, to investigate the changes in Coastline and salt marsh Uremia Lake is used of Landsat satellite images (MSS-TM5-ETM -OIL) that have been downloaded of USGS. To prepare satellite images in during processing, have been done pre-processing steps down: geometric correction, atmospheric correction, mosaic and Resample. Considering the importance of accuracy geometric correction on accuracy of the results of detection of changes Because of pixel by pixel comparison of satellite images together, these images must have coincided perfectly geometrically. So images using the 1:25000 Topographic Maps With the image registration to map method in WGS84 coordinate system and projection UTM Zone 38 with RMSE errors less than 5.0 were corrected. Initially the digital value of each pixel (DN) was Conversion to the Spectral radiation in sensor (Radiance) and then obtained Radiance was Conversion to reflection on the sensor (reflectivity), for atmospheric correction has been used of FLAASH method. After performing these steps, because this area is not within a Landsat image, for coverage of the full study area were mosaic images of each year. Finally all of images were re-sampling with method nearest neighbor. In this study, is used of six Salinity Index (NDSI, SI1, SI2, SI3, SI9, SI14). In order to changes evaluate Water Levels Uremia Lake do this in the period of 1976 to 2015 the water level in each image extracted from each image individually. To, various indices including normalized indices water, the normalized index humidity, corrected water normalized index, the index water ratio, normalized vegetation index, is used the index automatic extraction of water. After applying of indices on images, accuracy of the results of the index using the samples point that Lifted from the Google Earth was assessed. Eventually has been selected Suitable index for extract the shoreline and salt marsh and in in order to the separate of shoreline and salt marsh desired using the Model Maker extension in the ERDAS software was binary by taking considering threshold. Then been done with convert raster to vector maps and analyzes of Intended changes in the GIS10.3 software.
Discussion & According to obtained results for the study area NDWI index is the strongest index for Water extraction, So that properly extracted 191 water sample point and of 218 sample points of salinity have put Only 7 samples in Water class. To extract Salt marsh strongest indicator, is the SI2 so that 214 sample points of salinity extracted correctly and of 195 samples points of water, only 12 samples out of put in salinity class and The weakest index, is NDSI indicator. According to the analysis of satellite images surface area of ​​Lake Uremia is reducing and the salt marsh is increase. So that the water level of the lake and salt marsh reached respectively of ​​5216.30 and 106.18 square kilometers in 1976 to 1519.12 and 3777.50 square kilometers in 2015. The results of surveys show that have area of water the negative trend and salt marsh have increased trend. So that the water level Declined 72.76 square kilometers between the years of 1976 to 1985 to 1262.03 square kilometers between the years of 2011 to 2015 but Area of salt marsh have increasing trend so that increased the 59.53 square kilometer between the years of 1976 to 1985 to 1247.82 square kilometers between years of 2011 to 2015. According to the extraction of shoreline using the satellite imaging greatest change has happened in the direction of East and Southeast (estuary of river Permanent and full water of Zarinehrood) lake.
the main objective of this research because of the importance and special Status Lake in Ecosystems, is detect of changes of shoreline and salt marsh Uremia Lake during the period of 39 years. Check fluctuations level of lake using the data of satellite Level gauge of 1992 to 2018 showed that level of the lake has about 8 meters dropped. Results of the accuracy of the Accuracy of various indices for extract the shores of Lake Uremia Revealed that The strongest and the weakest index respectively, NDWI and NDMI index and The strongest and the weakest index for extract of salt marsh is SI2 and NDSI index. Analysis of satellite images shows that area of ​​the lake water and salt marsh respectively reached from 5216.30 and 106.18 square kilometers in 1976 to 1519.12 and 3777.50 square kilometers in 2015. These results it shows reduction of 70.87 percent area of Water Lake and increase in 3457.63 percent of the land of salt marsh of ​​ the study area during the past 39 years. Most of changes of area are related to ​​salt marsh and shoreline respectively 1286.45 and 1310.97 square kilometers Related to the period 2006 to 2011. Comparison of changes the coastline and depth of the lake showed that greatest of changes in parts of southeast and south due to the shallow depth of these Regions happened.