تهیه نقشه کشت برنج براساس خصوصیات فنولوژیکی با استفاده از سری زمانی تصاویر سنتینل 1

محورهای موضوعی : کشاورزی، مرتع داری، آبخیزداری و جنگلداری

صیاد اصغری سراسکانرود ^{1 *} , حسین شریفی طولارود ² , بهروز سبحانی ³

1 - هیئت علمی دانشگاه محقق اردبیلی
2 - دانشجوی کارشناسی ارشد، دانشگاه محقق اردبیلی، اردبیل، ایران
3 - عضو هیات علمی دانشگاه محقق اردبیلی

تاریخ دریافت : 1401/02/10 تاریخ پذیرش : 1401/05/30 تاریخ انتشار : 1403/07/08

کلید واژه: ضریب بازپراکنش راداری, سنجش ازدور, پلاریزاسیون, شالیزار,

چکیده مقاله :

هدف از این پژوهش شناسایی اراضی شالیزار و تهیه نقشه کاربری براساس خصوصیات فنولوژیکی گیاه برنج با استفاده از بازپراکنش داده‌های راداری در سامانه گوگل ارث انجین است. به منظور افزایش دقت تغییرات شدت بازپراکنش، سری زمانی 2ساله انتخاب شد. سپس نسبت به شناسایی اولیه و طبقه‌بندی اراضی اقدام شد. ابتدا ارتباط بین روند بازپراکنش پلاریزاسیون VV و چرخه فنولوژیکی گیاه برنج بررسی شد. نتایج تجزیه و تحلیل روند نمودار بازپراکنش پلاریزاسیون VV نشان می‌دهد که در مرحله اول رشد گیاه برنج بدلیل وجود رطوبت، غرقابی بودن و عدم وجود سبزینگی کافی میزان بازپراکنش کمتر بوده است. در مرحله دوم رشد گیاه برنج بدلیل افزایش سبزینگی و پوشانده شدن سطح آب مقدار بازپراکنش بیشتر می‌باشد. درحالی که در مرحله سوم رشد گیاه برنج، بدلیل رسیدگی بذر گیاه برنج و همچنین خشک شدن سطح شالیزارها جهت برداشت محصول، میزان بازپراکنش کاهش پیدا می‌کند. در ادامه با مدیریت بازه‌های زمانی و استفاده از ترکیب رنگی نوع کاربری‌ها شناسایی شدند. بعد از شناسایی اولیه، جهت دستیابی به نتایج بهتر اقدام به تهیه نقشه کاربری بخش مرکزی تالش با روش طبقه‌بندی نظارت شده با استفاده از الگوریتم بیشترین شباهت شد. بعد از تهیه نقشه کاربری، صحت نقشه با استفاده از نمونه‌های زمینی ارزیابی شد. که دقت کلی و ضریب کاپای این الگوریتم به ترتیب برابر با 91.57 درصد و 0.75 می‌باشد. نتایج نشان داد که استفاده از سری زمانی بازپراکنش داده‌های راداری متناسب با فنولوژی در طبقه‌بندی‌ها باعث افزایش دقت طبقه‌بندی می‌شود. همچنین نتایج نشان می‌دهد که استفاده از تصاویر سنتینل1 به همراه سامانه گوگل ارث انجین کارایی بالایی در جهت نظارت بر اراضی شالیزار در مناطق شمالی بدلیل وجود ابر خواهند داشت.

چکیده انگلیسی:

The purpose of this study is to identify Paddy Rice field and prepare a land use map based on the phenological characteristics of rice plants using the backscatering of radar data in the Google Earth engine Platform. In order to increase the accuracy of backscatering intensity changes, a 2-year time series was selected. Then, initial identification and land classification were performed. First, the relationship between VV polarization backscatering process and phenological cycle of rice plant was investigated. The results of VV polarization backscatering diagram analysis show that in the first stage of rice plant growth due to moisture, flooding and lack of sufficient vegetation, the backscatering rate was lower. In the second stage of rice plant growth, the amount of backscatering is higher due to increased vegetation and water surface coverage. While in the third stage of rice plant growth, due to the ripening of rice plant seeds and also drying of the paddy fields to harvest, the backscatering rate decreases. Then, by managing time periods and using color combination, the types of uses were identified. After initial identification, in order to achieve better results, a user map of the central part of the effort was prepared using the supervised classification method using the most similar algorithm. After preparing the user map, the accuracy of the map was evaluated using ground samples. The overall accuracy and kappa coefficient of this algorithm are 91.57% and 0.75, respectively. The results showed that the use of phenological data reprocessing time series in accordance with phenology in classifications increases the accuracy of classification. The results also show that the use of Sentinel 1 images along with the Google Earth engine Platform will have a high efficiency in monitoring paddy lands in the northern regions due to the presence of clouds.

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