| تعداد نشریات | 284 |
| تعداد نشریات سازمان | 82 |
| تعداد شماره‌ها | 3,036 |
| تعداد مقالات | 33,971 |
| تعداد مشاهده مقاله | 45,606,447 |
| تعداد دریافت فایل اصل مقاله | 74,763,821 |
پایش پوشش گیاهی با استفاده از تصاویر ماهواره‌ای در مراتع دماوند | ||
| تحقیقات مرتع و بیابان ایران | ||
| مقاله 14، دوره 28، شماره 1 - شماره پیاپی 82، فروردین 1400، صفحه 151-163 اصل مقاله (773.17 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijrdr.2021.121122.1704 | ||
| نویسندگان | ||
| بهنوش کریمی مفرح1؛ منصوره قوام* 2؛ عبدالنبی عبده کلاه چی3 | ||
| 1گروه مرتع وآبخیزداری، دانشکده منابع طبیعی وعلوم زمین دانشگاه کاشان | ||
| 2استادیار گروه مرتع و آبخیزداری، دانشکده منابع طبیعی وعلوم زمین دانشگاه کاشان | ||
| 3هیات علمی، پژوهشکده حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| چکیده | ||
| پایش تغییرات مراتع این امکان را فراهم می‌کند که در زمینه بهکارگیری برنامه‌های مدیریتی و حفاظتی با آگاهی تصمیم‌گیری شود. هدف از این پژوهش پایش تغییرات مراتع در بازه‌های پنج‌ساله در دوره زمانی 2000 تا 2015 با استفاده از سامانه‌های اطلاعات جغرافیایی و نرم‌افزار ENVI می‌باشد. در این راستا ابتدا تصاویر لندست در زمان‌های مورد نظر تهیه گردید. با استفاده از روشهای حداقل فاصله، ماهالانوبیس، حداکثر احتمال و درخت تصمیم و با اعمال سه شاخص NDVI، EVI و SAVI تصویر سال 2016 طبقه‌بندی شد. سپس با ارزیابی دقت توسط ضریب کاپا و صحت کلی، بهترین روش طبقه‌بندی استخراج گردید. در نتیجه سایر تصاویر برای سال‌های گذشته در بازه زمانی موردمطالعه با این روش طبقه‌بندی و پنج کلاس تحت عنوان مراتع کمتراکم، نیمهمتراکم، متراکم، فاقدپوشش و باغ‌ها و اراضی کشاورزی با توجه به موضوع موردمطالعه استخراج شد. همچنین نقاط تعلیمی به صورت برداشت زمین و از روی تصاویر به صورت ROI انتخاب شد. نتایج نشان داد که روش درخت تصمیم با اعمال شاخص SAVI، با دقت 73/94 بالاترین دقت را تولید کرد. بدینترتیب، با اینکه مساحت مراتع کمتراکم و نیمهمتراکم در سال 2005 و مراتع متراکم در سال 2010 افزایش پیدا کرده اما در مجموع در طی بازه زمانی 2000 تا 2015، هر سه کلاس مراتع کاهش، البته میزان کلاس فاقدپوشش به میزان قابل توجه و کلاس باغ‌ها و اراضی کشاورزی به میزان کم افزایش داشته‌اند. همچنین براساس یافته‌ها در دوره زمانی موردمطالعه، رفتار شاخص‌ها شبیه هم است. از سال 2000 تا 2010 شاخص‌ها دارای روندی افزایشی هستند اما در سال 2015 از میزان آنها کاسته می‌شود. ازاینرو می‌توان گفت طی اقدامات تخریب مراتع به‌ویژه در مراتع کمتراکم و نیمهمتراکم کاهش یافته و بر میزان مناطق فاقدپوشش افزوده شود. | ||
| کلیدواژه‌ها | ||
| Monitoring of vegetation using satellite images in Damavand rangelands | ||
| عنوان مقاله [English] | ||
| پایش پوشش گیاهی با استفاده از تصاویر ماهواره‌ای در مراتع دماوند | ||
| نویسندگان [English] | ||
| behnoosh karimi mofarah1؛ mansureh ghavam2؛ abdolnabi Abdeh Kolahchi3 | ||
| 1Department of Range and Watershed Management, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran. | ||
| 2Department of Range and Watershed Management, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran | ||
| 3Soil conservation and watershed management Research Institute (SCWMRI), AREEO, Tehran,Iran | ||
| چکیده [English] | ||
| Monitoring the changes in the rangelands makes it possible to make informed decisions about the application of management and protection plans. The purpose of this research is to monitor the changes from rangelands in the five-year period from 2000 to 2015 using geographic information systems and ENVI software. In this regard, Landsat images were first prepared at the specified times. By using the Minimum Distance, Mahalanobis, Maximum Likelihood, and Decision Tree, three NDVI, EVI, and SAVI indicators were modeled in 2016. Then, the best classification method was obtained by evaluating accuracy by Kappa coefficient and overall accuracy. As a result, other images for the past years were classified by this method and five classes were classified as low-density, semi-collimated, dense, non-covered, and gardens, and agricultural lands according to the subject. Educational points were also selected for both land surveying and ROI. The results showed that the tree of decision-making with the SAVI index yielded the highest accuracy with a precision of 94.73. Thus, although the area of low density and semi-dense pastures in 2005 and dense pastures in 2010 has increased, overall, during the period 2000 to 2015, all three classes of rangelands decreased. The attention and the class of gardens and agricultural lands have increased at a low level. Based on the findings of the study period, the behavior of the indicators is similar. From 2000 to 2010, the indicators were incremental, but in 2015, they decreased. Hence, it can be said | ||
| کلیدواژه‌ها [English] | ||
| Remote sensing, Damavand County, monitoring of changes, vegetation, SAVI Index | ||
| مراجع | ||
|
- Abate, T. and Angassa, A., 2016. Conversion of savanna rangelands to bush dominated landscape in Borana, Southern Ethiopia. Ecological Processes, 5(6): 1-18. - Abdolalizadeh, Z. and Ebrahimi, A., 2016. Change detection of land cover in recent three decades using RS and GIS in Sabzkouh protected area. Journal of Range and Watershed Managment, 69(3): 621-631. - Ahmadpour, A., Solaimani, K., Shokri, M. and Ghorbani, J., 2014. Comparison of three common methods in supervised classification of satellite data for vegetation studies. Journal of RS and GIS for Natural Resources, 5(3): 77-89. - Akbari, A. and Shakibari, A., 2014. Processing and extracting information from satellite data using ENVI with applied examples in geoscience, geography, geography and environment. Satellite Publishing, Tehran, 240 p. - Al-Ahmadi, F.S. and Hames, A.S., 2009. Comparison of four classification methods to extract land use and land cover from raw satellite images for some remote arid areas, Kingdom of Saudi Arabia. Journal of King Abdulaziz University, Earth Science, 20 (1): 167-191. - Arzani, H., 1994. Some aspects of estimating short and long term rangeland carrying capacity in the Western Division of New South Wales. Ph.D.Thesis, University of New South Wales. Australia. - Arzani, H. and Abedi, M., 2015. Evaluation of Range: Measurement of Vegetation, Volume II, University of Tehran Press, Tehran, 305 p. - Darwish, T. and Faour, G., 2008. Rangeland degradation in two watersheds of Lebnon. Lebanese Science Journal, 9(1): 71-80. - Eshghizadeh, M. and Esmaeilian, Y., 2020. Evaluation possibility of rangelands biomass estimation using Landsat 8 satellite data. Iranian Journal of Range and Desert Research, 27(1), 159-176. - Gandhi, M., Parthiban, S., Thummalu, N. and Christy, A., 2015. NDVI: Vegetation change detection using RS and GIS- A case study of Vellore District. Procedia computer science (ICRTC), 57: 1199-1210. - Hagen, S., Heilman, P., Marsett, R., Torbick, N., Salas, W., Ravensway, J. and Qi, J., 2012. Mapping Total Vegetation Cover Across Western Rangelands with Moderate Resolution Imaging Spectroradiometer Data. Rangeland Ecology and Management, 65(5): 456-467. - Hosinitsousel, M., Arzani, H., Farajzadeh Asl, M., Jafari, M., Babayikfaki, S. and Kohandel A., 2015. Monitoring of vegetation changes in rangelands during growing season using satellite imagery and its relationship with climatic factors. Case study: Alborz Province. Journal of Surreal and Desert Research, 22(4): 627 -618. - Kazemi, M. and Kamani Maskooni, E., 2018. Watershed Sustainability Assessment Based on HELP Model (Case Study: Lost Paradise Watershed, Fars Province). Extension and Development of Watershed Management, 6(22): 7-18. - Khaninzadeh, A., 2006. Investigate the possibility of preparing a cover map In TM vegetation using Landsat satellite data Nair-Yazd area. MSc thesis, Faculty of Natural Resources, Isfahan University of Technology, Iran. - Kumar Joshi, P.K. and Roy, P.S., 2006. Vegetation cover mapping in India using multi-temporal IRS wide field Sensor (WiFS) data. International Journal of Remote Sensing. 103(2): 190-202. - Matinfar, H., Sarmadian, F., Alavi panah, S. and Heck, R., 2007. Characterizing Land use/land cover types by Landsat7 data based upon Object oriented approach in Kashan region. Iranian Journal of Range and Desert Research, 14(4): 589-602. - Mirbaghri, V., Baradaran Nasiri, M. and Zare Arnani M., 2008. Investigating the possibility of monitoring the changes of vegetation in the Ardakan plain of Yazd using Landsat satellite images between 1976 and 2002, Geomatics conference, National Mapping Organization Tehran: 1-10. - Mirzayizadeh, N., Niknejad, M. and Mahdavi, A., 2014. Comparison of two methods for categorizing maximum probability and geometric distance in forest plot preparation (Case study: Biureh-Ilam province). Fourth International Conference on Environmental Challenges and Tree Chronology. Caspian Ecosystem Institute. University of Agricultural Sciences and Natural Resources. Sari: 212-222. - Mohamadi, S., 2016. Determination of best supervised classification algorithm for land use maps using satellite images (Case Study: Baft, Kerman Province, Iran). Journal of Rangeland Science, 6(4): 297-308. - Mohammadyari, F., Pourkhabaz, H., Tavakoli, M. and Aghdar, H., 2015. MappingVegetation and monitoring its Changes using Remote Sensing and GIS Techniques (Case study: Behbahancity). Scientific- Research Quarterly of Geographical Data (SEPEHR), 23(92), 23-34. - Rahdari, V., Soffianian, A., Khajaldin, S. andMaleki Najfabdai, S., 2014. Identification of satellite image ability for vegetation cover crown percentage mapping in arid and semi Arid region (Case study: Mouteh wild life sanctuary). Journal of Environmental Science and Technology, 15(4): 43-54. - Raati Shovazi, M., Karam, A., Ghafarian Malmiri, H.R. and Sepehr, A., 2018. Comparison the performance of some classification algorithms in study of desert landforms changes in Yazd-Ardakan plain. Quantitative Geomorphological Research, 6(1): 57-73. - Sanaeinejad, H., Astaraie, A., Mirhosseini, P., Agriculture, A. and Ghaemi, M., 2010, Using Satellite Images for Vegetation Studies (Comparison of Different Vegetation Indices - A Case Study of Neishabur Area), Fifth National Congress on Agricultural Machinery and Mechanization, Ferdowsi University of Mashhad: 1-10. - Shafei, H. and Hosseini, S., 2011. A study of vegetation in Sistan region through satellite data. Journal of Plant Ecophysiology, 3(9): 91-104. - Tim, H., William, S. and Graham, T., 1996. Modelling NDVI from decadal data in the North East Arid Zone of Nigeria. Journal Of Envirnomental Management, 48: 249-261. - Vanderpost, C., Ringrose, S., Matheson, W. and Arntzen, J., 2011. Satellite based long-term assessment of rangeland condition in semi-arid areas: An example from Botswana. Journal of Arid Environment, 75(4): 383-389. - Veisi, V., Ghavam, M. and bazrafshan, O., 2019. Drought Impacts on vegetation cover an emphasis on remote sensing (Case Study: Salafchegan – Neizar Watershed). Iranian Journal of Range and Desert Research, 26(3): 704-716. - Wylie, B.K., Meyer, D., Tieszen, L. and Mannel, S., 2002. Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands: A case study. Remote Sensing of environment. 79: 266-278. - Zebiri, M. and Majd, A., 2009. Introduction to remote sensing technology and application in natural resources, University of Tehran Press, Tehran, 317 p. - Zha, Y., Gao, J., Ni, S., Liu, Y., Jiang, J. and Wei, Y., 2003. A spectral reflectance-based approach to quantification of grassland cover from Landsat TM imagery. Remote Sensing of Environment. 87(3): 371-375.. | ||
|
آمار تعداد مشاهده مقاله: 687 تعداد دریافت فایل اصل مقاله: 379 |
||