پایش دمای سطح زمین با تکیه بر محصولات سنجنده مودیس و تکنیک‌های سنجش از دوری (مطالعۀ موردی: دشت کاشان) | ||
| کاوش های جغرافیایی مناطق بیابانی | ||
| دوره 11، شماره 1، تیر 1402، صفحه 161-178 اصل مقاله (3.16 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22034/grd.2023.19993.1575 | ||
| نویسندگان | ||
| مهدیه افشاری نیا1؛ عباسعلی ولی* 2؛ فاطمه پناهی3؛ حسین منشی4 | ||
| 1دانشجوی دکتری مدیریت و کنترل بیابان، گروه بیابان‌زدایی، دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، ایران | ||
| 2دانشیار دانشکده منابع طبیعی دانشگاه کاشان | ||
| 3دانشیار، گروه بیابان‌زدایی، دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، ایران | ||
| 4دانش‌آموخته کارشناسی ارشد مدیریت و کنترل بیابان، گروه بیابان‌زدایی، دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، ایران | ||
| چکیده | ||
| برآورد دمای سطح زمین برای طیف وسیعی از مطالعات کاربرد دارد. لذا پژوهش حاضر در نظر دارد؛ دمای سطح زمین دشت کاشان را با تکیه بر تصاویر ماهواره‌ای مودیس و پارامترهای فیزیکی حاصل از آن‌ها طی سال‌های 2020-2000 مورد بررسی قرار دهد. بدین‌ترتیب فرآورده‌های دمای سطح زمین(LST) با شناسۀ MOD11A1، شاخص تفاضل نرمال‌شدۀ پوشش گیاهی (NDVI) با شناسۀ MOD13Q1، تولید خالص اولیه (NPP)با شناسۀ MOD17A2H و آلبیدو (Albedo) با شناسۀ MOD43A1 با قدرت تفکیک مکانی 500 متر در بازۀ زمانی 8 روزه طی سال‌های 2020-2000 از پایگاه دادۀ ناسا استخراج شد. در ادامه نیز همبستگی پارامترهای فیزیکی با استفاده از ضریب همبستگی اسپیرمن بررسی گردید. نتایج نشان داد بین شاخص تفاضل نرمال‌شدۀ پوشش گیاهی و دمای سطح زمین، تولید خالص اولیه و دمای سطح زمین و آلبیدو و دمای سطح زمین ارتباط معنادار در سطح یک درصد وجود دارد. به‌گونه‌ای که همبستگی میان پوشش گیاهی و دما، تولید خالص اولیه و دما و آلبیدو و دما معکوس و به‌ترتیب برابر با 80/0-، 84/0- و 85/0- است. به‌طور کلی تغییرات پوشش زمین بالاخص پوشش گیاهی تأثیر بسزایی بر دمای سطح زمین دارد. نتایج پژوهش نشان می‌دهد که بخش وسیعی از افزایش دما در محدودۀ شرق و شمال شرق منطقۀ مورد مطالعه در اراضی بایر و نیز دریاچۀ نمک رخنمون داشته است که با گذشت سالیان متمادی افزایش دما قایل تأمل است. نتایج این پژوهش می‌تواند جهت کاربرد در بخش کشاورزی، منابع طبیعی و نیز محیط‌زیست دشت کاشان به‌منظور شناخت جزایر حرارتی و تصمیم‌گیری درخصوص بهبود شرایط پوشش‌گیاهی مورد توجه قرار گیرد. | ||
| کلیدواژه‌ها | ||
| سنجش از دور؛ محصولات مودیس؛ LST؛ NDVI؛ همبستگی | ||
| عنوان مقاله [English] | ||
| Monitoring the Earth surface temperature based on MODIS sensor products and remote sensing techniques (Case study: Kashan plain) | ||
| نویسندگان [English] | ||
| Mahdieh Afsharinia1؛ FATEMEH PANAHI3؛ HOSSEIN MANESHI4؛ | ||
| 1PhD student, Department of Desertification, Faculty of Natural Resources and Earth Sciences, Kashan | ||
| 3Associate Professor, Department of Desertification, Faculty of Natural Resources and Earth Sciences, Kashan University, Iran | ||
| 4Master's degree student, Department of Desertification, Faculty of Natural Resources and Earth Sciences, Kashan University, Iran | ||
| چکیده [English] | ||
| 1. Introduction Desertification manifests itself in its initial stages with less production in the ecosystem. In this situation, the balance of water and nutrients for the growth of plants becomes unfavorable compared to the past. In natural conditions, the ecosystem of dry areas is in a stable state in terms of water and energy conversion, but due to human intervention, this balance is subject to change. Obviously, when the vegetation is destroyed, the land becomes bare, its organic matter is destroyed and the structure of the soil is destroyed. In this situation, direct rain on the soil causes further destruction of the soil structure. The natural consequence of such conditions is the lack of rainwater storage and the drop in the level of underground water tables. Usually, severe reduction of vegetation, water and wind erosion, salinity, soil compaction, sedimentation and emptying of nutrients are considered as the main signs of desertification. According to the definition of the Convention to Combat Desertification (UNCED), desertification is the destruction of land in dry, semi-arid and dry and semi-humid areas due to human and climatic factors, which as a result reduces the productive power of the land. Water and soil are among the most valuable natural resources, and human societies, both farmers and ranchers, are active and dynamic agents of changing natural landscapes, and improper management, neglect, and excessive exploitation can lead to soil destruction, and as a result, human life is seriously threatened. be placed. 2. Methodology To achieve the goals of the research; Modis sensor images were obtained from the NASA database during the years 2000-2020. In order to calculate the land surface temperature (LST) from the MOD11A1 product, to extract the Normalized Difference Vegetation Index (NDVI), from the MOD13Q1 product, to extract the Net Primary Production (NPP) index, from the MOD17A2H product with a spatial resolution of 500 meters in a time frame of 8 The MOD43A1 product of the Terra satellite was used to extract the albedo index. After preparing the MODIS sensor images, the indices of land surface temperature, normalized difference of vegetation cover, net primary production and albedo were estimated from the images and their correlation was checked. 3. Results and Discussion Based on the results, LST is shown in three classes: low, medium and high. So, low to south moderate in the northwest and west and higher temperatures in the east of the study prevail. And based on the results, NDVI is classified into four areas with very poor, poor, moderate and dense coverage. Thus, the very weak layer is located in the north and northeast side, the weak layer is located in the northwest to south side, and the medium and dense layer is located in the northwest to southwest side. with increasing temperature; The normalized difference index of vegetation decreases and there is an inverse relationship between LST index and NDVI. with increasing temperature; Primary net production decreases and there is an inverse relationship between LST index and NPP. Based on the obtained results, it can be acknowledged that there is an inverse relationship between LST index and Albedo. 4. Conclusion Based on the results obtained from the fourth chapter; The LST index during 2000-2020 was divided into three classes of low temperature, medium temperature and high temperature. So that; The largest area of the studied area had an average temperature, which was observed in the south and southwest. In the eastern and northeastern regions, the temperature was higher than in other regions, which corresponds to Namak Lake and Qom. Also, areas with low temperature were covered only in small parts from the northwest to the southwest of the region, which corresponds to the uneven heights of Karks. The NDVI index during 2000-2020 was divided into four classes: very weak, weak, medium and dense. So that; The largest area of the studied area had weak to weak silt cover, which was observed in the northwest to east range, which corresponds to Namak Lake and Qom. Also, it covered areas with medium to dense coverage only in small parts from the northwest to the southwest of the region, which corresponds to the uneven heights of Karks. Based on the results of NPP index changes during 2000-2020, the highest amount of primary net production was observed in the northwest to southeast of the studied area. This shows that the amount of primary net production is higher in this range. Also, the minimum amount of primary net production in the range from northwest to south corresponds to the heights of Vulture to Tanam, which indicates low production. Based on the results of changes in the Albedo index during the years 2000-2020, the highest amount of albedo was observed in the northeast to the east, so that these areas correspond to the salt lake and areas with weak vegetation, low net primary production and high temperature, because albedo and surface temperature The earth is affected by the amount of vegetation and relatively small changes in the characteristics of the vegetation cause changes in the albedo and temperature of the earth's surface. Between the normalized difference index data of vegetation and land surface temperature, net primary production and land surface temperature and albedo and land surface temperature, there was a significant relationship at the one percent level so that the correlation between vegetation and temperature, net primary production and temperature and albedo and the temperature was reversed and equal to 0.80, -0.84 and -0.85 respectively. The results of the study made it possible to create a desertification program by presenting a practical program for the Syr Regressive Road Dam and took an effective step towards sustainable development. | ||
| کلیدواژه‌ها [English] | ||
| Remote Sensing, Modis products, LST, NDVI, Correlation | ||
| مراجع | ||
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Belyani, Saeid, Modiri, Mehdi, Gadami, Fardin, Halimi, Mansour (2016), Investigating the surface temperature of the earth and the temperature taken from the thermometer to reveal the spatial structure of the thermal island of Tehran, the first international conference on climate change. [In Persian]. Denis, A., Carlos, A., Brine, D., Martha, C. and Mark, D. (2018). Use of remote sensing indicarors to assess effected of drouth in northeastern Brazil. Remote sensing of environment. 213 (2013). 129-143. Eskandari Doman, Hamed, Zahtabian, Gholamreza, Khosravi, Hassan, Azarnivand, Hossein, Barati, Ali Akbar (2022). Investigating the process of vegetation changes affected by drought in arid and semi-arid regions using remote sensing technique (case study: Hormozgan province), Desert Ecosystem Engineering, Volume 9, Number 28, p. 28. [In Persian]. Eskandari Domane, Hadi, Eskandari Domane, Hamed, Khosravi, Hassan, Chiraghi, Maitham, Adeli Sardoi, Mohsen (2022). Evaluation of land degradation using Landsat satellite remote sensing data in the period 1390-1400 (case study: Isfahan city), Remote Sensing and Geographical Information System in Natural Resources, Volume 14, Number 1, p. 86. [In Persian]. Feng, K., Wang, T., Liu, S., Kang, W., Chen, X., Guo, Z and Zhi, Y. (2022). Monitoring Desertification Using Machine-Learning Techniques with Multiple Indicators Derived from MODIS Images in Mu Us Sandy Land, China. Remote Sensing. 2022; 14(11):2663. https://doi.org/10.3390/rs14112663 Feng, Q., Ma, H., Jiang, X., Wang, X and Cao, S. (2019). What has caused desertification in China? Scientific reports, 5(1), 1-8. Ghafarian Malmiri, Hamidreza, Arabi Ali Abad, Fahima (2021). Estimation of land surface albedo in different land uses in Yazd-Ardakan Plain, Environmental Science Studies, Volume 5, Number 1, p. 2394. [In Persian]. Ghorbani Salkhurd, Rezvan, Mubasheri, Mohammadreza, Rahimzadegan, Majid (2010), Ability of MODIS sensor data in qualitative and quantitative analysis in urban areas. Climatology Research Journal, first year, third and fourth issue, p. 59. [In Persian]. Gitti, Alireza (2011), Desert, desertification and desertification, Tehran publication, Iranian Agricultural Science, p. 28. [In Persian]. Hashem Golugardi, Sara, Vali, Abbas Ali, Sharifi, Mohammad Reza, (2021), Investigating the process of desertification in the center of Khuzestan province using remote sensing time series data, Iran Water and Soil Research, Volume 52, Number 11, p. 2857. [In Persian]. Imson, A. (2012). Desertification, destruction and land sustainability. Land use planning. Springer. Jamali, Zahra, Ong, Majid, Salman Mahini, Abdul Rasool (2019), Investigating the relationship between land surface temperature and land use and the normalized vegetation difference index in Gorgan Plain, Spatial Planning and Planning, Volume 23, Number 3, p. 194. [In Persian]. Jamshidzadeh, Zahra (2020), Investigating the quality of the Kashan Plain aquifer using hydrogeochemical analyses, Hydrogeology, Volume 5, Number 1, p. 33. [In Persian]. Jiang, Zh., Xiliang, N. and Minfeng, X. (2023). A Study on Spatial and Temporal Dynamic Changes of Desertification in Northern China from 2000 to 2020. Remote Sensing 15, no. 5: 1368. https://doi.org/10.3390/rs15051368 Khosravi, Yunus, Heydari, Mohammad Ali, Tavakoli, Azadeh, Zamani, Abbas Ali (2017), Investigating the relationship between the temporal changes of the surface temperature and the spatial pattern of land use changes (case study: Zanjan city), Space Planning and Development, Volume 21, No. 3, p. 119. [In Persian]. Mahmoudi, Peyman, Amirjahanshahi, Seyed Mehdi, Firozi, Fatemeh, Salimpour, Hirsh (2021), Statistical modeling of the relationship between albedo and land surface temperature (LST) and normalized difference vegetation cover index (NDVI) in the Sistan plain in eastern Iran. The third national conference on environmental engineering and management. [In Persian]. Marboote, Bahareh, Ashrafzadeh, Afshin,Nezam Doost, Majid, Khaledian, Mohammadreza (2018), Comparison of real evaporation-transpiration of MOD16 product and simulated by SWAP model in Qazvin Province, Iran Water Resources Research, Year 14, Number 2, p. 65. [In Persian]. Ontel, I., Cheval, S., Irimescu, A., Boldeanu, G., Amihaesei, V., Mihailescu, D., Angearu, C., Nertan, A and Craciunescu, V. (2023). Assessing Recent Trends of Land Degradation and Desertification in Romania Using Remote Sensing Indicators. Available at SSRN: https://ssrn.com/abstract=4453641 or http://dx.doi.org/10.2139/ssrn.4453641 Panahi, Fatemeh, Ehteram, Mohammad, Gior, Alireza, Afsharinia, Mahdieh (2020), Desertification, Land Destruction and Sustainability, Kashan University, p. 128. [In Persian]. Qurbanniakhibri, Vajiheh, Mirsengari, Mirmehrdad, Liaqati, Homan, Armin, Mohsen (2017), Land surface temperature estimation of land use and land cover in Dana city using separate window algorithm and Landsat 8 satellite data, Environmental Sciences, Volume 15, Number 2, p. 55. [In Persian]. Rajai, I., Abbes, A., Farah, I. and Sattari, M. (2020). A riview of drought monitoring using sensing and data mining methods. International conference Advanced technologies.
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