Abstract:
متغیّرهای اقلیمی و نوسانات آن بهطور چشمگیری روی اکوسیستمهای خشکی و تغییرات آنها اثرگذارند. در پژوهشهای بسیاری از شاخصهای گیاهی برای بررسی ارتباط بین تغییرات اکوسیستمها و پارامترهای اقلیمی استفاده شده است. در نوشتار پیش رو، از آنالیز مکانی و زمانی سیستم اطّلاعات جغرافیایی برای مدلسازی رابطة تغییرات پوشش گیاهی برپایة شاخص پوشش گیاهی بارزسازیشدة سنجندة مادیس و پاسخ آن به دمای سطح زمین و بارش در استان مازندران در بازة زمانی 2000 تا 2016 استفاده شد. پارامتر دمای سطح زمین از اطّلاعات ماهوارة مادیس و پارامتر بارش با استفاده از اطّلاعات ایستگاههای هواشناسی منطقه بهدست آمد. آنالیزهای همبستگی و رگرسیون خطّی برای بررسی رابطة زمانی - مکانی شاخص پوشش گیاهی و دو پارامتر اقلیمی انجام گرفت. نتایج بیانگر آن بود که طی دورة مورد بررسی، متوسّط شاخص سبزینگی استان روند افزایشی در طول داشته است؛ درحالی که عرصههای جنگلی استان روند کاهشی را طی دورة مورد پژوهش نشان دادهاند. نتایج بررسیهای میدانی این تناقض را با افزایش در شالیزارهای منطقه نشان میداد. نتایج تحلیل همبستگی نشان داد که همبستگی مکانی معنیداری بین دینامیک پوشش گیاهی با دمای سطح زمین وجود داشته که در ماههای زمستان، این ارتباط معنیدار و مستقیم و در تابستان معکوس بوده است. آنالیز تحلیل انطباقی نشان داد که درطول ماههای زمستان، توزیع مکانی پیکسلهای با بیشترین مقدار شاخص پوشش گیاهی با پیکسلهای با حداکثر دما (20 تا 27 درجة سانتیگراد) مطابقت داشته، درحالی که در طول ژوئن تا سپتامبر، حداکثر مقادیر پوشش گیاهی مربوط به مناطقی بود که دمای کمتر از 25 درجه داشته است؛ امّا همبستگی پوشش گیاهی با بارش بهصورت فضایی با تأخیری دوماهه در فصل بهار به پیک میرسد.
Climate variables and their fluctuations dramatically affect terrestrial ecosystems and their variations. Vegetation indices have been used in numerous studies to investigate the relationship between ecosystem changes and climate parameters. In this study, GIS based spatiotemporal analyses were applied to model the relationship between vegetation variations based on the EVI-MODIS and its response to land surface temperature (LST) and rainfall in Mazandaran province during the period of 2000-2016. The LST parameter was derived from the MODIS data and rainfall parameter was achieved via meteorological station data in the region. Correlation and linear regression analyses were used to study the relationship between spatiotemporal enhanced vegetation index (EVI) and two climatic parameters. The findings indicated that the EVI had a rising trend over the study period which was mostly due to the increase in paddy fields. There was also a significant spatial correlation between EVI and LST which was significant and direct in the winter months and reversed during summer. The tabulate area analysis showed that throughout the winter months the spatial distribution of the highest EVI pixels matched to the maximum temperature pixels (20 to 27 ° C), while during June to September, the maximum EVI values were related to the areas in which the LST was less than 25 °C. Although there was no significant relationship between EVI/MODIS and rainfall in studied area, they reached a peak with a lag time of 1/5 to 2/5 months in the spring. The final results showed that the temperature is the main EVI climate factor in region and MODIS products have high potential to reveal the spatiotemporal dynamics of vegetation, the impact of human factors and its relation with the climatic factors of temperature and rainfall in the region. Extended Abstract 1-Introduction Vegetation can be considered as a comprehensive index reflecting changes in its surroundings due to interactions with the climate of each region. Climate, as a controlling and dominant factor, not only plays a great role in controlling and distributing vegetation and its spatiotemporal variations, but also has interactive effects, which has been the subject of a majority of research in the world. Besides, the study of vegetation dynamics monitoring in recent decades has been widely considered based on the use of vegetation indices extracted from satellite imagery. One of the most important of these indices is EVI, which has a high sensitivity to structural variables of vegetation. On the basis, data from the MODIS satellite data and products by making time series of EVI were applied in the current study to determine the dynamics of this index relative to two main climate variables (land surface temperature and rainfall) over a period of time. 2-Materials and Methods In this study, spatiotemporal analysis of GIS was used to model the relationship between vegetation dynamics based on EVI from MODIS satellite. In fact, we tries to investigate the response of this index to two climate variables, including land surface temperature (LST) -as an auxiliary characteristic for temperature- and rainfall in Mazandaran province in northern Iran during the period 2000 to 2016. The LST was derived from the 17-year data from the MODIS satellite products. The rainfall information for this province was extracted from the Kriging interpolation based on the meteorological stations data available in the region. The EVI time series was also obtained from the MODIS products for the study period. Mapping was prepared based on the 17-yearly average monthly EVI and LST parameters extracted from the MODIS satellite. Three classes of EVI values (EVIEVI class, 0/23-Results and Discussion The EVI temporal pattern based on regression analysis showed that the overall trend of this index during the study period was linear which ascended with an average of 0.45. This trend has more fluctuations in the summer than in the spring. However, the spatial distribution pattern of the EVI based on the three vegetation classes showed that during 2010 and 2016, areas with 0/4 >EVI (forest zones) had a decreasing trend which is due to the fact that the area under cultivation of rice farms (0/44-Conclusion The results of this study showed that vegetation dynamics in Mazandaran Province responded to the land surface temperature fluctuations and this response was positive in the cold season. However, this relationship has not been seen in the case of rainfall. The increase in EVI in spring and summer is due to the beginning of the growing season and warming of the region, the highest in the Hyrcanian forests. The results also show the effects of human intervention on the dynamics of the spatiotemporal pattern of the region's land covers which was based on an increase in the EVI area of rice fields and a decrease in forest area floor levels despite EVI increases during the study period. The final results revealed that the temperature is the main climate factor of the EVI in region and MODIS products have high potential to reveal the spatiotemporal dynamics of vegetation, the impact of human factors and its relation with the climatic factors of temperature and rainfall in the region.
Machine summary:
از ايـن ميان ، سنجندٔە ماديس ناسا از ماهوارٔە ترا٢٠ و آکوآ٢١، با ٣٦ باند که باند ١ و ٢ آن با توان تفکيک مکاني ٢٥٠ متري، 1- Zhong 2- Richard & Poccard 3- Bao 4- Chuai 5- Xu 6- Luan 7- Xin 8- He 9- Leilei 10- Ding 11- Guo 12- Chang 13- Raynolds 14- Kaufmann 15- NOAA/AVHRR 16- LANDSAT 17- Halimi 18- Chen 19- Lu 20- Terra 21- AQUA باند ٣ تا ٧، با توان تفکيک ٥٠٠ متري و باند ٨ تا ٣٦ با توان تفکيک يک کيلومتر به طور وسيعي در پـژوهش هـاي اخير استفاده شده است (تستا١ و همکاران ، ٢٠١٨).
تجزيه و تحليل توزيع مکاني و زماني پوشش گياهي (شاخص تفاوت گياهي نرمال شدٔە ماهوارٔە ماديس )، دمـاي 1- Testa 2- Normalized Difference Vegetation Index (NDVI) 3- Enhanced Vegetation Index (EVI) 4- Soil Adjusted Vegetation Index (SAVI) 5- Chen 6- Hussein 7- Motlagh 8- Huete 9- Leaf Area Index (LAI) 10- Wang 11- Li 12- Zoungrana 13- Phompila 14- Dou سطح زمين ١ و بارندگي و روابط اين سه عامل در بازٔە زماني ٢٥ ساله در تبت ، نشان داد که ضريب همبستگي بين پوشش گياهي و دماي سطح زمين در ماه جولاي کمترين و بين پوشش گياهي و بارش در ماه سپتامبر بيشـترين بوده است (ليلي و همکاران ، ٢٠١٤).