بررسی اثر تغییرات پوشش اراضی بر مراتع حوزه آبخیز قوری چای با تکنیک سنجش از دور
محورهای موضوعی :
آمایش سرزمین
مرضیه علی خواه اصل
1
,
داریوش ناصری
2
,
الهام فروتن
3
,
لیلا غیرتی آرانی
4
1 - استادیار، گروه کشاورزی و منابع طبیعی، دانشگاه پیام نور، تهران، ایران. *(مسوول مکاتبات)
2 - باشگاه پژوهشگران جوان و نخبگان، واحد اردبیل، دانشگاه آزاد اسلامی، اردبیل، ایران
3 - استادیار، گروه کشاورزی و منابع طبیعی، دانشگاه پیام نور، تهران، ایران.
4 - استادیار، گروه کشاورزی و منابع طبیعی، دانشگاه پیام نور، تهران، ایران.
تاریخ دریافت : 1395/02/31
تاریخ پذیرش : 1395/04/23
تاریخ انتشار : 1401/10/01
کلید واژه:
تغییرات پوشش اراضی,
NDVI,
تصاویر ماهواره ای,
حوزه آبخیز قوری چای,
چکیده مقاله :
زمینه و هدف: در حال حاضر، بیشتر تغییرات کاربری اراضی، بدون برنامه ریزی روشن و منطقی و توجه به اثرات زیست محیطی آنها صورت می گیرد و از آنجا که این تغییرات در سطوح وسیع و گسترده اتفاق می افتد، بنابراین تکنولوژی سنجش از دور ابزاری ضروری و ارزشمند جهت پایش تغییرات می باشد. هدف از تحقیق حاضر، بررسی تاثیر تغییرات پوشش اراضی بر مراتع حوزه آبخیز قوری چای در شمال استان اردبیل با تکنیک سنجش از دور می باشد.روش بررسی: ابتدا تصاویر ماهواره لندست مربوط به خرداد ماه سال های 1366 ، 1380 و 1394 تهیه و پس از پیش پردازش تصاویر، طبقه بندی تصاویر به روش نظارت شده با الگوریتم حداکثر احتمال انجام پذیرفت. سپس، تصاویر هر سال در چهار طبقه کشت دیم، مرتع، اراضی مسکونی (روستا) و اراضی بایر طبقه بندی شد. به منظور افزایش دقت طبقه بندی تصاویر نیز از رقومی سازی دستی، شاخص NDVI و لایه شیب استفاده شد و دقت طبقه بندی نیز با شاخص کاپا و صحت کلی بررسی شد.یافته ها: نتایج تحقیق نشان داد که در طی دوره زمانی مورد بررسی 5885 هکتار (7/49%) از سطح حوزه دچار تغییر کاربری شده است که بیشترین تغییر مربوط به کاهش شدید مراتع حوزه به میزان 2540 هکتار (4/21%) بر اثر تبدیل به اراضی کشت دیم و بایر می باشد.بحث و نتیجه گیری: بر اساس نتایج به دست آمده، استفاده از اطلاعات تکمیلی از جمله اطلاعات شیب و شاخص NDVI در کنار پردازش تصاویر ماهواره ای به روش نظارت شده برای تهیه نقشه های کاربری اراضی، موجب افزایش دقت طبقه بندی تصاویر می گردد.
چکیده انگلیسی:
Background and Objective: In the present time, land use changes are being conducted without clear and logical programming or regarding the environmental effects of the changes. Because land use changes occur in a large scale, remote sensing technique is a useful and valuable tool for monitoring the changes. The aim of this research is investigation of the effects of land cover changes on rangelands of Ghoorichay chatchment located in the north of Ardabil province using remote sensing technique.Material and Methodology: In this investigation, TM images for year 1987, ETM images for year 2001 and OLI-TIRS images for year 2015 were collected and analyzed. After image pre-processing enhancements and corrections, the images were classified using maximum likelihood supervised classification method. Then, considering study area features, the images were classified into four land cover classes: dry land, range land, bare land and village. Moreover, NDVI index and slope layer were used to increase classification accuracy. At last, land cover changes and their effects on the range lands were detected. Overall accuracies and kappa coefficient were evaluated.Findings: According to the results, during the studied period, 5885 hectare (49.7%) of study area had changed. The most land cover changes were related to range land with intensive decrease of 2540 hectares (21.4%) which was changed into bare land and dry land.Discussion and Conclusion: Additional information such as slope layer and NDVI index in assistant with supervised classification of satellite images can increase the accuracy of image classification to provide land cover maps.
منابع و مأخذ:
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Sanjari, S., Boroumand, N. 2013. Monitoring land use/cover changes in the last three decades using remote sensing technique (case study: Zarandestan region of Kerman). Application of Remote Sensing and GIS in Natural Resource Sciences. Vol. 4 (1), pp. 56-67. (In Persian)
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Kelarestaghi, A., Ahmadi, H., Jafari, M., Qudousi, J. 2017. Forecasting possible changes in forest use to dry farming using probabilistic modeling in the Frame Sahra watershed-Mazandaran province. Research and Construction, Vol 21 (3), pp.52-63. (In Persian)
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Soltanian, S., Rahimi, E., Sabz Qabaei, Gh., Rostami, K., Zeidi, A. 2013. Evaluation of the trend of land use changes in Oshtorankooh protected area between the years of 1989 and 2005 using Landsat images. Quarterly magazine of new technologies in environmental engineering and renewable resources, first year, Vol 1 (1), pp. 1-13. (In Persian)
Kazemi, M., Mahdavi, Y., Nohegar, A., Rezaei, P. 2018. Estimating changes in land cover and land use using geographic information systems (case study: Tange Bostank watershed, Shiraz). The application of remote sensing and GIS in natural resources sciences, Vol 2 (1), pp. 103-116. (In Persian)
Dong, , Wenting, ZH., 2014. A comparison of comparison of Markov model-based methods for predicting the ecosystem service value of land use in Wuhan, central China. EcosystemServices7, (2014), 57–65.
Edwards, P.J., May, R.M., Webb, N.R., 1994. Large Ale ecology and conservation biology. Environ, Natural Resources, 32 (1), 33–39.
Karagozlu, A., Nouri Kermani, A., Keshmiri, Z. 2018. Evaluation of physical changes and analysis of urban development using high-resolution satellite data and GIS/RS systems (Case study: District 5 of the Municipality Tehran). Environmental science and technology, Vol 11 (1), pp. 219-229. (In Persian)
Xian, G., Homer, C., Fry, , 2009. Updating the 2001 National Land Cover Data base land cover classification to 2006 by using Landsat imagery change detection methods. Remote Sensing of Environment, 113, 1133–1147.
Mohammady, M., Moradi, HR., Zeinivand, H., 2015. A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran. International Journal of Environment Science and technology, 12:1515–1526.
Chen, X., Vierling, L., Deering, D., 2005. A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98(1), 63-79.
Coops, N.C., Wulder, M.A., White, J.C., 2006. Identifying and describing forest disturbance and spatial pattern: data selection issues Understanding For Disturbance Spatial Pattern. Remote Sens, GIS Approaches, 31.
Chen, X., Vierling, L., Deering, D., 2005. A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98(1), 63-79.
Jensen, J.R and Cowen, D.C., 1999. Remote sensing of urban suburban infrastructure and socio-economic attributes. Photogram Engineering, Remote Sensing, 65, 611–622.
Hathout, S., 2002. The use of GIS for monitoring and predicting urban growth in East and West St Paul, Winnipeg, Manitoba, Canada. Journal of Environmental Management, 66, 229–238.
Yousefi, S., Moradi, H., Hosseini, S. H., Mirzaei, S. 2018. Monitoring land use changes in Marivan using TM and ETM+ sensors of Landsat satellite. Journal of Remote Sensing and GIS Application in Natural Resources Sciences. Vol 2 (3), pp. 104 -97. (In Persian)
Nazari Samani, A. A., Ghorbani, M., Kohbanani, H. 2009. Evaluation of the trend of land use changes in the Taleghan watershed in the period 1987 to 2001. Rangeland, Vol. 4 (3), pp. 451 -442. (In Persian)
, Gao, X., 2015. Land cover changed object detection in remote sensing data withmedium spatial resolution. International Journal of Applied Earth Observation and Geoinformation, Vol. 38, pp.129–137.
Hong, Y., 2013. Characterizing land use changes in 1990-2010 in the coastal zone of Nantong, Jiangsu province, Chin. Ocean & Coastal Management, 71, (2013), 108-115.
Shalaby, A., Tateishi, R., 2007. Remote sensing and GIS for mapping and monitoring land cover and land use changes in the northwestern coastal zone of Egyp. Applied Geography 27, (2007), pp. 28-41.
Tavallaee, S., Haji Nowrozi, N. 2016. Pakdasht land use preparation using RS and GIS. Journal of Geographical Sciences, Vol. 5, No. 6 and 7: 27-40. (In Persian)
Rasouli, A. A. and Mahmudzadeh, H. 2018, Fundamentals of Remote Sensing Basic Knowledge. first edition, Alimaran Publications. (In Persian)
Yuan, F.K.E., Sawaya, C., Loeffelholz, M. E., 2005. Land cover classification and change analysis of the Twin (Minnesota) Metropolitan Area by multi temporal Landsat remote sensing. Remote sensing of Environment, 95: 317-328.
Richards, J., Xiuping, J., 2006. Remote Sensing Digital Image Analysis: An Introduction. 4th Edition, Springer.
Soroudi, M., Jozi, S. A. 2013. .Remote sensing and implementation of Markov model to investigate the changes of urban green space (Case study: District 1 of Tehran municipality). Environology. Vol. 39 (10), pp. 113-122. (In Persian)
Lee, T., H.,Yeh., 2009. Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities, Taiwan. Ecological Engineering, 487-496.
Yousefi, S., Tazeh, M., Mirzaei, S., Moradi, H., Tavanger, Sh. 2013. Comparison of different classification algorithms of satellite images in the preparation of land use map (case study: Noor city). Application of Remote and GIS in Natural Resources Sciences. Vol. 2, pp. 15-25. (In Persian)
Ghorbani, R., Taghipour, A. A., Mahmoudzadeh, Ha. 2017. Evaluation and analysis of land use changes in the Ala-Gol, Alma-Gol and Aji-Gol international wetlands of the Turkmen Sahra using multi-temporal satellite images. Geography and Environmental Planning. Vol. 23 (4), pp. 168-186. (In Persian)
Rusta, Z., Manouri, S. M., Darvish, M., Falahati, F. 2013. The application of remote sensing and geographic information system in extracting the land use map of Shiraz outskirts. Town and Country Planning. Vol. 4 (6), pp. 163- 149. (In Persian)
Sanjari, S., Boroumand, N. 2013. Monitoring land use/cover changes in the last three decades using remote sensing technique (case study: Zarandestan region of Kerman). Application of Remote Sensing and GIS in Natural Resource Sciences. Vol. 4 (1), pp. 56-67. (In Persian)
Elcavy, O., Rod, J., Ismail, H., Suliman, A., 2011. Land use and land cover changes detections in the western Nile delta of Egypt using remote sensing data. Applied geography, 31(2011), pp. 483-494.
General Department of Meteorology of Ardabil Province, Department of Statistics and Information, access date 2014. (In Persian)
Kelarestaghi, A., Ahmadi, H., Jafari, M., Qudousi, J. 2017. Forecasting possible changes in forest use to dry farming using probabilistic modeling in the Frame Sahra watershed-Mazandaran province. Research and Construction, Vol 21 (3), pp.52-63. (In Persian)
Rajesh, B., Yuji, M., 2006. Land use change analysis using remote sensing and GIS: A Case Study of Kathmandu Metropolitan, Nepal. Research Abstracts on Spatial Information Science CSIS DAYS: 1.
