Detection and District Analysis of Urban Green Space Changes in The 22 Districts of Tehran

Document Type : Science - Research

Authors

1 Ph.D Student, Department of Geography and Urban Planning, Nour Branch, Islamic Azad University, Nour, Iran.

2 Assistant Professor, Department of Geography, Nour Branch, Islamic Azad University, Nour, Iran.

3 Associate Professor, Department of Geography, Nour Branch, Islamic Azad University, Nour, Iran.

4 Associate Professor, Department of Geography, Nour Branch, Islamic Azad University, Nour, Iran

Abstract

The main aim of this paper is to detect the ten-year changes in urban green spaces of Tehran metropolis, from 2010 to 2019, using the time series of Landsat 5, 7 and 8 images. The change detection was done in both annual and ten-year scale and the results are analyzed in two spatial scales; city level and municipal district-level. Detection of changes was done by a post-classification approach. The innovation of the study is efforts to reach the best results in the image classification step, for which in addition to optical and thermal bands' various features including some vegetation indices, water and built-up index, image texture components, and principal components were also used. Three classification methods including maximum likelihood, artificial neural network and support vector machine were implemented. The results indicated that the support vector machine has had the best result with 91.06% mean overall accuracy. The change detection showed a 10.58% decrease in the Tehran green spaces in the period under review. The greatest decrease, about 7.46 Km2, occurred in the period 1390-91 and the largest increase was 7.61 Km2 in the period 1394-95. Among the 22 municipal districts, regions 1 and 22 with 5.2 and 2.37 Km2, respectively, have had the highest decrease in urban green space, and regions 2 and 19 with 0.5 and 0.47 Km2, respectively, have had the highest increase.

Keywords

Main Subjects

References

  1.  

    1. اسماعیل­زاده، حسن و شفیعی ثابت، ناصر (1392)، بررسی تغییرات کاربری اراضی و ناپایداری در اکوسیستم شمال تهران (مطالعه موردی: حوضه آبخیز درکه-ولنجک)، پژوهش های دانش زمین، 15: 102-83.
    2. امیدوار, کمال؛ نارنگی­فرد، مهدی و عباسی, حجت اله (1394)، آشکارسازی تغییرات کاربری اراضی و پوشش گیاهی در شهر یاسوج با استفاده از سنجش از دور، جغرافیا و آمایش شهری منطقه‌ای، 5: 111-126.
    3. درگاه ملی آمار (1395)، نتایج سرشماری عمومی نفوس و مسکن، اطلاعات جمعیتی مناطق 22 گانه تهران.
    4. سرودی، منا و جوزی، سیدعلی (1395)، بررسی تغییرات کیفی فضای سبز شهر تهران از سال 1369 تا 1385 (مطالعه موردی: منطقه 5 شهرداری تهران)، فصلنامه علوم و تکنولوژی محیط زیست، 18: 335-344.
    5. مرصوصی، نفیسه و رشوند، صالح (1396)، تحلیل روند تغییرات دورهای فضای سبز شهری زنجان از 1385 تا 1390 و ارائه الگوی مکانیابی بهینه آن، دو فصلنامه علمی- پژوهشی پژوهش­های بوم­شناسی شهری، 16: 101-118.
    6. نظم­فر، حسین؛ جعفری، فیروز و فیضی­زاده، بختیار (1387)، کاربرد داده­های سنجش از دور در آشکارسازی تغییرات کاربری های اراضی شهری (مطالعه موردی فضای سبز شهر تبریز)، هنرهای زیبا، 34: 24-17.

    7. آرخی، صالح؛  نیازی، یعقوب و ارزانی، حسین (1390)، مقایسه تکنیک­های مختلف پایش تغییر کاربری اراضی / پوشش گیاهی با استفاده از GIS & RS(مطالعه موردی حوزه دره شهر- استان ایلام)، علوم محیطی، سال 8، شماره3، 81-96.    

    1. Ahmad, A., Aboobaider, B. M., Isa, M. S. a. M., Hashim, N. M., Rosul, M., Muhamad, S., & Man, S. (2014). Temporal changes in urban green space based on normalized difference vegetation index. Applied Mathematical Sciences, 8(55):2743-2751.
    2. Al-Dail, M. A. (1998). Change Detection in Urban Areas using Satellite Data. Journal of King Saud University. Engineering Sciences, 10(2): 217-227.
    3. Angelici, G., Bryant, N., Friedman, S. (1977). Techniques for land use change detection using Landsat imagery. Proceedings of the 43rd Annual Meeting of the American Society of Photogrammetry and Joint Symposium on Land Data Systems, Falls Church, VA, USA: 217–228.
    4. Byrne, G., Crapper, P., Mayo, K. (1980). Monitoring land-cover change by principal component analysis of multitemporal Landsat data. Remote sensing of environment, 10(3): 175-184.
    5. Deng, J., Huang, Y., Chen, B., Tong, C., Liu, P., Wang, H., & Hong, Y. (2019). A methodology to monitor urban expansion and green space change using a time series of multi-sensor SPOT and Sentinel-2A images. Remote Sensing, 11(10): 1230.
    6. Dong, L., Jiang, H., Yang, L. (2018). Spatio-Temporal Change of Vegetation Coverage and its Driving Forces Based on Landsat Images: a Case Study of Changchun City. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 3: 295–298.
    7. Ellefsen, R., Peruzzi, D. (1976). Land-use change detection from Landsat and Skylab satellites. In International Society for Photogrammetry, 13th. Int. Congress for Photogrammetry, 11-23.
    8. Foody, G. M., Mathur, A., Sanchez-Hernandez, C., Boyd, D. S. (2006). Training set size requirements for the classification of a specific class. Remote Sensing of Environment, 104(1): 1-14.
    9. Friedman, S. Z., Angelici, G. (1979). The detection of urban expansion from Landsat imagery. Remote Sensing Quarterly, 1: 58–79.
    10. Gordon, Steven I (1980). Utilizing Landsat imagery to monitor land-use change: A case study in Ohio. Remote Sensing of Environment, 9(3): 189-196.
    11. Kopecká, M., Szatmári, D., Rosina, K. (2017). Analysis of urban green spaces based on Sentinel-2A: Case studies from Slovakia. Land, 6(2), 25: 1-17.
    12. Nilkamal, P, M., Nikam, V., Banerjee, B. J. (2020). Machine learning on high performance computing for urban greenspace change detection: satellite image data fusion approach. International Journal of Image and Data Fusion, 1-15.
    13. Rafiee, R., Mahiny, A. S., Khorasani, N. J. (2009). Assessment of changes in urban green spaces of Mashhad city using satellite data. International Journal of Applied Earth Observation and Geoinformation, 11(6): 431-438.
    14. Rubec, C., Thie, J. (1978). Land use monitoring with Landsat digital data in southwestern Manitoba. Paper presented at the 5th Canadian Symp. Remote Sensing of Environment, 136–149.
    15. Shahabi, H., Zabihian, H., Shikhi, A. (2012). Application of satellite images and GIS in evaluation of green space destruction in urban area (Case study: Boukan City). International Journal of Eng., 1(7): 1–6.
    16. Singh, Ashbindu (1989). Review article digital change detection techniques using remotely-sensed data. International Journal of remote sensing, 10(6): 989-1003.
    17. Todd, William J (1977). Urban and regional land use change detected by using Landsat data. Journal of Research of the US Geological Survey, 5(5): 529-534.
    18. Toll, D., Royal, J., Davis, J. (1981). Urban area update procedures using Landsat data. American Society of Photogrammetry, Falls Church, RS-El-17.
    19. USGS website: /https://earthexplorer.usgs.gov.
    20. Van, T. T., Tran, N. D., Bao, H. D., Phuong, D. T., Hoa, P. K., Han, T. T (2017). Optical remote sensing method for detecting urban green space as indicator serving city sustainable development. In Multidisciplinary Digital Publishing Institute Proceedings,Vol. 2, No. 3, p. 140: 1-6.
    21. Wilson, J., Blackman, C., Spann, G. (1976). Land use change detection using Landsat data. Proceedings of the fifth annual remote sensing of earth resources conference, 79-91.
Journal of Urban Ecology Researches
Volume 12, Issue 25 - Serial Number 4
Winter
March 2022
Pages 37-58

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History

  • Receive Date: 08 October 2020
  • Revise Date: 28 November 2020
  • Accept Date: 29 December 2020

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