چکیده:
هدف این پژوهش بررسی تغییرات جنگلهای مانگرو و ارتباط این تغییرات با هیدرودینامیک دریا و مورفولوژی ساحلی در فاصله بین جزیره قشم و از رود مهران تا بندر پل طی بازه زمانی 47 ساله میباشد. با استفاده از تصاویر ماهوارهای و انجام پیش-پردازشها و طبقهبندی آنها به روشهای SVM، MLC و ANN و ارزیابی دقت نقشهها روش SVM با کسب بالاترین درصد دقت با ضریب کاپا 97/0 و صحت کلی 98، برای تهیه نقشه طبقهبندی تمام تصاویر انتخاب شد. نقشهها برای سالهای 1972، 1987، 2002 و 2019 با صحت کلی برابر با 40/92، 40/92، 62/96 و 98 و همچنین ضریب کاپا نیز به ترتیب 89/0، 90/0، 95/0 و 97/0 برآورد شدند. نتایج نشان می دهد که از سالهای 1972 تا 1987 این جنگل ها روند کاهشی داشته اما پس از این دوره گسترش آنها آغاز شده است. این مناطق شامل، جنگلهای مانگرو مردو، خور موریز دراز، خور هفت برم، جنگلهای مانگرو در جنوب بندر لافت، همچنین جنگلهای مانگرو بین اسکله طبل، ملکی و گورزین میشوند. با مقایسه نتایج حاصل از روند افزایشی و کاهشی جنگلهای مانگرو با منحنیهای منطبق با متوسط میزان جزر و مد و ویژگیهای مورفولوژیک منطقه این نتیجه به دست می آید که محدوده مورد مطالعه از بابت ویژگیهای هیدرودینامیک دریا، مانند متوسط دامنه جزرومد و گستردگی پهنه جزرو مدی، ارتفاع امواج و مورفولوژی ساحلی مانند شیب و دادههای رسوبی و آب ورودی رودخانه مهران، پتاسیل بالاتری برای توسعه هر چه بیشتر جنگلهای مانگرو دارد.
IntroductionFor thousands of years, mangrove forests have played a significant role in the economy and sustainable livelihoods of human societies. Therefore, identifying and measuring changes in the boundaries of mangroves over time can play an important role in planning and conducting effective protection measures and reducing the vulnerability of mangroves to natural and human hazards. The aim of this study was to investigate changes in mangrove forests and the relationship between these changes and marine hydrodynamics and coastal morphology in parts of the north and east of the Strait of Hormuz over a period of 47 years.MethodologyIn this study, Landsat satellite images, MSS, TM, ETM +, OLI sensors from 1972 to 2019 were used to monitoring mangrove forests changes in the west of the Hormuz strait. In the next step, the necessary preprocesses (radiometric and atmospheric corrections) were applied to the images in ENVI 5.3 software. And the classification of images was done by SVM, MLC and ANN methods, and considering that in order to finalize the land use map, all classification accuracy indicators should be adjusted with one or more valid statistical indicators. The kappa index and general accuracy are among the statistical methods used. Post-processing operations also included the integration of classes that were applied to make the land use map more eloquent and eliminate single pixels on different classes. In the next step, the Change Detection method was used to detect changes and tell the results of the classifications. The next step is to convert the classified image to polygon and transfer it to the Arc GIS environment to manage the classes. Of course, the class that is most important to us here is the Mangrove Forest class, which was examined in the period 1972-2019. After the changes in the mangrove forests were identified, with the help of 1: 25000 topographic maps, contours of 2 meters of the range was prepared and the slope map was prepared using DEM images of the area. Also, using the half-hour tide data, the minimum, maximum and average tide rates of Jask, Shahid Rajaee, Hormoz and Sirik stations were calculated and finally these data and maps were prepared to examine the development potential of mangrove forests, Was examined.ResultLand use maps were developed using Landsat images using three pixel-based classification algorithms (MLC, SVM, ANN) and the accuracy of the results was assessed using random points. The results showed that the highest overall accuracy and kappa coefficient were 99.44 and 0.99 for region A, and 98.41, 0.97, for region B, for SVM, respectively. Our study showed that SVM could be the most appropriate classification method for this study area. Therefore, SVM land use maps were prepared for the study area for 1972, 1987, 2002 and 2019. After preparing the land use change map, it was stated that mangrove forests in region A accounted for 55.84% and in region B for 36.18%, tidal areas in region A accounted for 27.63% and in Area B is 36.58 percent, Water Areas A is 3.04 percent, Area B is 1.78 percent, dry land is 15.37 percent and region B is 99.99. 7% have changed over the past 47 years. To explore the potential for the expansion of mangrove forests, we examined the slope of the region and its relationship with the average tide in the region. Comparing the results of the increasingand decreasing trend of mangrove forests with curves corresponding to the average tidal level and morphological features of the region, we conclude that the study area is about the hydrodynamic characteristics of the sea such as the average tidal area and extent. The catchment area, the height of the waves and the coastal morphology such as slope and sediments and the water entering the areas from the Hasanlangi River and the Gaz and Hivi rivers have a very high potential for further development of mangrove forests.Discussion and conclusionThe results show that in the northern part of the Strait of Hormuz, the area of mangrove forests has increased in all the years, but in the eastern part of the study, we have always faced a decreasing and increasing trend and We don't see this part significant development during these 47 years in mangroves.. However, according to the study of the geomorphic features of the region such as slope, topography and the presence of sabkha and Firth and sediments from the rivers of Hassan Langi, Gaz and Hivi, as well as the average tide of the region and the vast area it covers, The study has the potential to develop mangrove forests. The results of this study can provide significant information about the progress or regression of mangroves in different coastal areas, can significantly help to implement protection measures and rehabilitate Iranian mangroves.
خلاصه ماشینی:
همچنين اين رويشگاه در ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ 1- Saenger 2- De Lacerda 3 - Rodringuez & Feller 4 - Wells 5 - Ahmed & Abdel-Hamid 6 - Furukawal & Baba 7 - Duke 8 - Mcleod Rodney معرض برخي از تهديدات ديگر از جمله توسعه راه ها، استقرار نامناسب صنايع ، استفاده بدون ظرفيت يابي و طرح ريزي تفريحي (دانه کار، ۱۳۷۷)، توسعه استخرهاي برداشت نمک، تردد شناورهاي سنتي صيادي و تجاري ، آلودگي نفتي ، حضور گونه هاي بيگانه (اتنگاماکو و همکاران ۱ ۲۰۰۸).
ضروري است روند تغييرات سطح رويشگاه در زمان هاي مختلف با بررسي علت اين کاهش يا افزايش مورد بررسي قرار گيرد، تا با آشکار شدن نواحي که بيش تر در معرض تهديدات قرار دارند، روند کاهش تخريب آن ها در طول زمان آشکار ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ 1 - OtengAmoako 2 - Jensen 3 - Letchumy and MdSaid 4 - Gilman 5 - Paling 6 - Along 7 - Thom 8 - Maguire 9 - Danehkar 10 - Mehrabian شود.
به عبارتي اين تابع داده هاي آموزشي را ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ 1 - Dolan 2 - Ellison and Zouh 3 - Chavez 4- Gandini & Usunoff 5 - Roy 6 - Noori 7 -Maximum Likelihood classification 8 -Support Vector Machine classification 9 - Rao که به صورت غيرخطي در فضاي چند بعدي با استفاده از تابع کرنل طرح ريزي مي شود را در يک مجموعه داده به صورت خطي از هم جدا از هم جدا مي کند که نتيجه آن طبقه بندي خطي بين داده ها مي باشد (واپنيک ۱، ۱۹۹۹: ۱۳۱).