Detection and monitoring of algal blooms in Persian Gulf using MODIS images

سال انتشار: 1390
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,809

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شناسه ملی سند علمی:

SASTECH05_061

تاریخ نمایه سازی: 22 مرداد 1391

چکیده مقاله:

Persian Gulf is susceptible to occurrence of Algal bloom phenomenon. As an example, the Red tide phenomenon occurred in the region from autumn 2008 to spring 2009. The aim of this research is to detect the Red tide phenomenon in the Persian Gulf waters and its monitoring during specific period of time using remote sensing data.Detection of Red tide phenomenon in waters of the region was accomplished using chlorophyll anomaly monitoring method. By using values of water leaving reflectance in visible and near infrared bands, regression analysis and also field measurements, an experimental bio-optical model was produced to estimate chlorophyll-a density of water using data gathered by MODIS sensor. This model explains %93 of the chlorophyll-a variation for chl-a ranging from 5 to 30and can be used to estimate chl-a density with a normalized root mean square error (RMSEN) of %9.8 and mean normalized bias (MNB) of %0.4.To determine areas where Red tide phenomenon is occurred in specific dates, values of chlorophyll-a density estimated at that date using the produced chlorophyll model is compared with the thresholds extracted from chlorophyll map of the same area related to a normal year (i.e. the previous year). Through this method, areas with intensive changes in chlorophyll-a density which are apt to bloom occurrence are determined. As the produced chlorophyll model does not provide the desirable accuracy in Case 1 waters, a filter is considered to omit the Case 1 waters from the final Red tide map. The obtained results show that the produced regional chlorophyll model is effectively capable of detecting bloom occurrence areas compared to OC3M model of MODIS sensor.

نویسندگان

Elham Tayebi

M.S Student, Photogrammetry Division, Surveying and Geomatics

Mohammad Reza Saradjian

Associate Professor, Remote Sensing Division, Surveying and Geomatics Engineering Dept., University of Tehran

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