بررسی روند‌ تغییرات سرسبزی پوشش گیاهی ( Greening و Browning ) با استفاده از سری زمانی MODIS-NDVI در استان مازندران

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

1 دانشجوی دکتری ، گروه جنگلداری و اقتصاد جنگل، دانشکده منابع طبیعی دانشگاه تهران، کرج، ایران.

2 استاد، گروه جنگلداری و اقتصاد جنگل، دانشکده منابع طبیعی دانشگاه تهران، کرج، ایران.

چکیده

سابقه و هدف: پوشش گیاهی یکی از اجزاء اصلی بیوسفر و یک عنصر حیاتی در سیستم اقلیمی است که آگاهی از تغییرات و روند فعالیت آن، می‌تواند به بهره‌وری بهینه از زمین‌های کشاورزی، اکوسیستم‌های طبیعی، تغییرات اقلیمی و تنوع زیستی تاثیر گذارد. شاخص‌های گیاهی حاصل از داده‌های ماهواره‌ای، ابزار قدرتمندی برای نظارت و بررسی پویایی پوشش گیاهی در مقیاس‌های زمانی و مکانی بزرگ را فراهم کرده است. هدف پژوهش حاضر بررسی روند بلندمدت پوشش گیاهی به صورت پیکسل به پیکسل در استان مازندران با استفاده از سری زمانی NDVI سنجنده MODIS ماهواره‌های Terra و Aqua است.
مواد و روش‌ها: پژوهش حاضر در کل استان مازندران که 53 درصد از جنگل‌های هیرکانی و 12050 کیلومتر مربع از مراتع را در بر می‌گیرد، انجام شد. در این مطالعه محصولات شاخص پوشش گیاهی سنجنده MODIS با تفکیک مکانی 250 متر و فاصله زمانی 16 روزه به نام‌های MOD13Q1 و MYD13Q1 مورد استفاده قرار گرفته است. تصاویر شاخص NDVI موجود در این دو محصول با هم ترکیب و یک سری زمانی 828 تصویری با فاصله 8 روزه و تفکیک مکانی 250 متر از شاخص NDVI برای دوره زمانی 2003 تا 2021 ایجاد شد. به منظور افزایش کیفیت و حذف داده‌های پرت سری زمانی، پیکسل‌های متاثر از ابر، برف و یخ در هر تصویر از سری زمانی بر‌اساس اطلاعات تضمین کیفیت MODIS و مؤلفة فصلی درون سری‌های زمانی که ممکن است بررسی روند بلند مدت را با مشکل مواجه کند، با استفاده از فرمول Anomaly حذف شد. سپس سری زمانی با استفاده از روش‌ پارامتریک حداقل مربعات معمولی(OLS)و روش‌های ناپارامتریک تیل‌سن، من-کندال و معنی‌داری من-کندال در محیط گوگل ارث انجین (GEE) مورد تجزیه و تحلیل قرار گرفت.
یافته‌ها: نتایج این مطالعه نشان داد که خروجی روش‌های OLS، تیل‌سن و من-کندال به هم نزدیک بوده و روند‌های افزایشی (Greening) و کاهشی (Browning) به ترتیب در حدود 87 و 13 درصد از سطح استان رخ داده است. همچنین معنی‌داری روندهای من-کندال نشان می‌دهد که 21/77 درصد از روند‌های منطقه شامل 65/70 درصد از روند‌های مثبت (Greening) و 56/6 درصد از روند منفی (Browning) در سطح 1 درصد و 48/6 و 95/2 درصد از روندها به ترتیب سطوح 5 و 10 معنی‌دار هستند. پراکنش مکانی روند‌‌های پوشش‌های گیاهی نیز نشان داد که بخش وسیعی از روند‌های Browning در مناطق جلگه‌ای شمال استان و بیشتر روند‌ Greening در اراضی جنگلی و پوشش‌های مرتعی رخ داده است.
نتیجه‌گیری: به طور کلی مطالعه حاضرنشان داد که Greening در سطح وسیعی بخصوص در پوشش‌های گیاهی طبیعی شامل جنگل‌ها و مراتع رخ داد است‌. تغییرات پوشش‌ها گیاهی طبیعی متاثر از تغییرات اقلیمی است، چرا که فعالیت‌های انسانی در آن‌ها محدود می‌باشد. بنابراین روند گرمایش زمین می‌تواند مهمترین عامل Greening در استان مازندران باشند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigating the trend of vegetation changes (greening and browning) using MODIS-NDVI time series in Mazandaran province

نویسندگان [English]

  • Ahmad Abbasnezhad Alchin 1
  • Ali Aasghar Darvishsefat 2
1 PhD. Student, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran.
2 Professor, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
چکیده [English]

Background and objectives: Vegetation is one of the main components of the biosphere and a vital element in the climate system, and knowing its changes and activity trends can affect the optimal productivity of agricultural land, natural ecosystems, climate change, and biodiversity. Vegetation indices derived from satellite data have provided a powerful tool for monitoring and investigating vegetation dynamics in large temporal and spatial scales. The aim of this study is to investigate the long-term trend of vegetation in pixels to pixels in Mazandaran province using the NDVI time series of MODIS sensor.
Materials and methods: The current research was conducted in the province of Mazandaran, which includes 53% of Hyrcanian forests and 12050 square kilometers of rangeland. In this study, the vegetation index products of the MODIS sensor with a spatial resolution of 250 meters and an interval of 16 days, named MOD13Q1 and MYD13Q1, have been used. The NDVI index images available in these two products were combined and a time series of 828 images with an 8-day interval and a spatial resolution of 250 meters was created from the NDVI index for the period from 2003 to 2021.In order to increase the quality of the time series, the pixels affected by clouds, snow and ice in each image of the time series based on MODIS quality assurance information and the seasonal component within the time series that may make long-term trend investigation difficult, using the Anomaly method were removed. Then the time series was analyzed using parametric ordinary least squares (OLS) regression and non-parametric Theil-Sen and Mann-Kendall in Google Earth Engine (GEE).
Results: The results of this study showed that the output of OLS, Theil-Sen and Mann-Kendall methods were close to each other and Greening and Browning occurred in about 87% and 13% of the province, respectively. Also, the significance of Man-Kendall trends shows that 77.21% of trends in the province, include 70.65% of positive trends (Greening) and 6.56% of negative trends (Browning) at ρ < 0.01, 6.48% and 2.95% of trends at ρ < 0.05 and ρ < 0.10 are significant, respectively. The spatial distribution of the trends also showed that a large part of the Browning trends occurred in the plains of the north of the province and most of the Greening trends occurred in forest lands and rangeland.
Conclusion: In general, this study showed that greening occurred on a large scale, especially in natural vegetation including forests and rangeland. Changes in natural vegetation are affected by climate change, because human activities are limited in them. Therefore, the process of global warming can be the most important factor of Greening in Mazandaran province.

کلیدواژه‌ها [English]

  • Long-term trend
  • Google Earth Engine
  • Mann-Kendall
  • Theil-Sen
  • MODIS-NDVI

مراجع

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پژوهش‌های علوم و فناوری چوب و جنگل
دوره 30، شماره 1
فروردین 1402
صفحه 125-140

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