بــررسی تغیـیـرات پـوشـش گیــاهـی ایــران با استـفاده از ســری های زمـانی NDVI سنـجنـده NOAA-AVHRR و تجـزیـه وتحـلیـل هـارمـونیـک ســری های زمـانی (HANTS)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار گروه جغرافیا دانشگاه یزد، یزد، ایران

2 دانشجوی دکتری علوم و مهندسی مرتع، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران

10.22131/sepehr.2020.40476

چکیده

بررسی تغییرات پوششهایگیاهی میتواند اطلاعات ارزشمندی را در مورد گرمایش جهانی،چرخه کربن، چرخه آب و تبادل انرژی به همراه داشته باشد. استفاده از سریهای زمانی تصاویر ماهوارهای و روشهای سنجش از دور اطلاعات زیادی را در مورد تغییرات و پویاییهای پوششهای گیاهی به ما عرضه میدارند. هدف از پژوهش حاضر، تعیین تغییرات هر کدام از مؤلفههای سریهای فوریه پوششهای گیاهی ایران در طول سه دهه گذشته میباشد. بدین منظور در این مطالعه ازمحصول NDVI روزانه سنجنده AVHRRبا قدرت تفکیک مکانی 05/0 در 05/0 درجه با نام AVH13C1 استفاده شد. سپس با استفاده از الگوریتم HANTS اجزای هارمونیک چهار سری زمانی یکساله در زمان گذشته (1982، 1983، 1984 و 1985) و چهار سری زمانی یکساله در سالهای اخیر (2015، 2016، 2017 و 2018) تولید شد. در نهایت تغییرات اجزای هارمونیک یا همان تصاویر دامنه و فاز در سالهای اخیر نسبت به سالهای گذشته تعیین شد و اختلاف میانگین ارزشهای اجزای هارمونیک بین چهار سری زمانی یکساله در گذشته وحال با تجزیه واریانس یک طرفه بررسی شد و نقشههای معنیداری اختلاف بین میانگینها بدست آمد. با توجه به نتایج،در مناطق مرکزی، شرق و شمال شرق ایران دامنه صفر (میانگین پوشش گیاهی) در سطح احتمال 95 درصد (F-value< 0/05 ) کاهش یافته و در مناطق شمال و شمال غرب و غرب به ویژه ارتفاعات البرز و زاگرس دامنه صفر به طور معنیدار (F-value< 0/05) افزایش یافته است. اختلاف میانگین ارزش فازها در چهار سری زمانی در گذشته و سالهای اخیر در مناطق غرب و شمال غرب و همچنین شرق و شمال شرق ایران در سطح احتمال 95 درصد (F-value< 0/05) معنیدار میباشد. فازهای سالانه این مناطق به میزان 14 درجه کاهش یافته است که این موضوع نشان دهنده شروع زودتر فرآیندهای رشد و فنولوژی گیاهان این مناطق نسبت به سه دهه گذشته میباشد.

کلیدواژه‌ها


عنوان مقاله [English]

Investigating vegetation changes in Iran using NDVI time series of NOAA-AVHRR sensor and Harmonic ANalysis of Time Series (HANTS)

نویسندگان [English]

  • Hamid Reza Ghafarian Malamiri 1
  • Hadi Zare Khormizi 2
1 Assistant Professor Department of Geography, Yazd University, Yazd, Iran
2 PhD Student of Range Management, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
چکیده [English]

Introduction
 Investigation of vegetation changes can provide valuable information on global warming, the carbon cycle,water cycle and energy exchange. Satellite imagery timeseriesandremote sensing techniques offers a great deal of information on variations and dynamics of vegetation. Harmonic ANalysis of Time Series (HANTS) has been effectively used to eliminate missing and outliers in time series of vegetation indices and land surface temperature (LST). However, the algorithm has been less frequently used to detect changes in vegetation and phenology. HANTSalgorithm decomposes periodic phenomena into their components(different sines and cosineswith different amplitudes and phases). The value of phases and amplitudes contains valuable information that can be used to investigate variations and identify different characteristics of vegetation such as growth and phenology. The present study aims to determine changes in each componentof vegetation time series in Iranin the past (1982, 1983, 1984 and 1985) and in recent years (2015, 2016, 2017 and 2018).
 
Materials & Methods
 A daily NDVI product of AVHRR sensor, with a resolution of 0.05 at 0.05 ° (i.e. AVH13C1) was used in the present study. To obtain reliable harmonic components (amplitude and phase images), a reliable curve has to be fitted on the primary time series data. To do so, first,parameters of HANTS algorithm were determined and then Root Mean Square Error (RMSE) of the curves fitted on data related to four one-year time series in the past year’s category (1982, 1983, 1984 and 1985) and four one-year time series in recent year’s category (2015, 2016, 2017 and 2018) was estimated. This classification (i.e. four one-year time series in the past and recent years) was used for two reasons. First, extraction and comparison of harmonic components in a single time series in the past and recentyears’ categories cannot reflect real changes, as these changes may occur under the influence ofimpermanent dynamics of vegetation, such as dryor wet periods. Second, with four one-year time series in the past category (1982, 1983, 1984 and 1985), and four one-year time series (2015, 2016, 2017 and 2018) in recent years, statistical comparison of the harmonic components through one-way analysis of variance becomes possible. Following the production of reliable harmonic components, variations of the harmonic components in recent years were compared with their variations in the past using difference method, and mean difference ​​of the harmonic components’value in four one-year time seriesin the past and present categories wasdetermined using one-way analysis of variance. Finally, some maps were produced to exhibitthe significance of differenceinmeans.
 
Results & Discussion
According to the findings of the present study, mean RMSE of the fitted curves in the four one-year periods ofpresent and past time series were always less than 0.1 unit of NDVI. Moreover, mean RMSEof total area of Iranin the past and present time series were 0.037 and 0.039, respectively. This demonstrates high efficiency of the HANTS algorithm in elimination of missing and outlier data in the daily-NDVI time series ofNOAA-AVHRR. Results indicate thatrange of zero amplitude (the mean value of NDVI or the average vegetation coverage) decreasesin the central, eastern and northeastern regions of Iran atthe 95% probability level (F-value <0.05), whileit increases significantly (F-value <0.05)in the north, northwestern and western regions (especially, the Alborz and Zagros mountains). The meandifferenceof phases value in the four-time series of the past and recent years’categories wassignificant at the 95% probability level (F-value <0.05). Compared to the past time series, first harmonic phase average of total area of Iran in the new time series has decreased by almost 14 degrees. This decrease in the value of the annual and 6-month phases indicates a quicker growth phase and phenological processes of plants compared to past times.
 
Conclusion
 Results indicated that HANTS algorithm can effectively eliminateand reconstruct outliers in the NDVI time series. Zero harmonic (mean value) represents the overall level of vegetation cover and the firstharmonic phase in a one-year time series determines the starting time of growth in seasonal plants or thosewith agrowth period of6-month or less. Annual Phase indicates the angular starting position of the annual cycles and the 6-month phase inherently indicates the fluctuation and angular position of a half-year or 6-month curve. However, interpreting 6-month amplitude and phases are difficult. As most changes are controlled by the first harmonic phase, the first harmonic phase in a one-year time series contains important information about the beginning of growth and the phenological processes of plants. Therefore, harmonic components of a periodic time series canbeusedto identify and determine changes in vegetation coverage and phenological processes.

کلیدواژه‌ها [English]

  • HANTS
  • phase
  • Amplitude
  • Time Series
  • Phenology
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