Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Application of remote sensing data in detection of urban land use changes Case study: Shahr-e Kord

Document Type : Research Paper

Authors
Mohsen Shaterian 1
Seyed Hojjat Mousavi 2
Zahra Momenbeik 3
1 Associate Professor of geography and urban planning, Kashan university, Kashan, Iran
2 Assistant Professor of geography and ecotourism, Kashan university, Kashan, Iran
3 Master student of geography and urban planning, Kashan university, Kashan, Iran
10.22131/sepehr.2019.37522
Abstract
Extended Abstract
Introduction
Knowing type and percentage of each land use and land cover are considered to be a fundamental need for understanding and managing an area. Given the ever-increasing changes in land use, managers and experts need to be aware of past changes and developments. This is because, policy making and solving existing problems require detecting changes and determining the trend of changes over time. Satellite data is one of the quickest and least expensive methods available based on which researchers can produce different land use map. In this regard, Landsat Satellite imageries are one of the most important data sources used to study different types of land use and land cover changes, such as deforestation, agricultural expansion and urban growth. Extracting information from satellite imagery through classification is one of the most widely used methods. One of the most important applications of remote sensing data is for investigating and discovering changes in phenomena with a spatial-temporal nature (i.e. phenomena whose position and status changes over time). In fact, change detection is the process of identifying and determining the type and extent of land cover or land use in a given period of time based on remote sensing images. The present study seeks to monitor land use changes in Shahr-e Kord during the period of 1985 to 2017, and to prepare land use maps of the area using Landsat satellite imageries.
 
Materials & Methods
In the present study, satellite imageries received from TM, ETM+, and OLI sensors of Landsat satellites in 1985, 2000, 2015, and 2017 were extracted from the United States Geological Survey (www.usgs.gov) and analyzed using different remote sensing software and geographical information systems like ENVI 4.7 and ArcGIS 10.4. In order to produce land use changes map, error correction was first performed. Then, images were processed using supervised classification method and maximum likelihood algorithm, which based on previous studies have a higher accuracy compared to other algorithms. In order to classify land use/land covers, a training sample was produced for  each land use based on field observations, topographic maps (1:25000) produced by Iran National Cartographic Center, Google Earth imageries, and visual study of the imageries. Then, classification results were corrected using auxiliary data, visual interpretation, experiential knowledge, and GIS techniques. Prior familiarity with the region, visual study of imageries, previous experience and field operations revealed that following land uses exist in the region and are detachable on the images as well: a) urban, b) agricultural, c) industrial, d) meadow, e) airport, and c) other land uses (including pasture, rocky areas and areas without any specific land cover). Confusion or error matrix –including overall accuracy, producer’s accuracy, user accuracy and kappa coefficient- was also used to evaluate the accuracy of the classification. Also, urban land use changes were monitored using image differentiation functions.
 
Results & Discussion
After production of land use maps based on imageries received in 1985, 2000, 2015, and 2017, area of the six land cover classes was obtained. Results indicate that during these four periods (1985 to 2000), urban, industrial, agricultural and airport land uses have increased to 13, 111.7, 5.2 and 3.4 km2 (1.26, 10.16, 0.51 and 0.4 % increase) respectively, while meadows and other land uses have faced a decreasing trend. In other words, it can be concluded that most changes during this 15-year period occurred in meadows and other land uses. Since development of the airport have resulted in destruction of a large part of meadows, this land use have faced more severe changes. Land use changes from 1985 to 2017 indicate that 7.8 km2 of agricultural lands were transformed into urban land use, 1.4 km2 to industrial land use, 1.08 km2 to airport and 7.7 km2 to other land uses. Also, 20.5 km2 of other land uses were transformed into urban land use, 203.1 km2 to agricultural land use, 0.03 km2 to dried meadows, 0.17 km2 to airport and 14.5 km2 to industrial land use. 2.8 km2 of meadows were also transformed into agricultural land use, 0.05 km2 to industrial land use and 2.04 km2 to airport. During this period, urban and industrial land uses have remained unchanged.
 
Conclusion
Generally, results indicate that urban, industrial and agricultural land uses have developed over time, and these land uses have always had a positive increasing trend. While meadows and other land uses have had a decreasing and negative trend. This is due to the construction of Shahr-e Kord Airport, uncontrolled exploitations, digging wells and drought phenomena, which have led to a decrease in the level of water in aquifers and destruction of natural ecosystem in this region. In this way, previous meadows have turned into the source of intense dust generation in the city, which is a sign of desertification and ecosystem destruction. Due to drought and water scarcity in recent years, new deep wells have been dug with the aim of supplying water. This have occurred despite the critical condition of the meadows, and thus, have resulted in repeated protests by farmers and livestock farmers. Dramatic decrease in other land uses, including pastures, can also be attributed to recent droughts in Iran and intense dust generation. Increased population, increased human pressure on natural resources and also development of agricultural lands are among other causes of the present situation. Based on existing maps and satellite imageries, Shahr-e Kord is developing towards North and North West. In some areas, this development has occurred in pastures. Therefore, due to very high population density in the region which is still increasing, and also ongoing migration of villagers to the city, supplying appropriate accommodation and occupation for this population requires finding new suitable locations for urban and industrial development of the city. This development process should happen with correct management and according to the goals of sustainable development.
Keywords
Land use
Landsat
Shahr-e Kord
Remote Sensing
Change detection
1- آرخی، نیازی، ارزانی؛ صالح، یعقوب، حسین؛ 1390؛ مقایسه تکنیک‌های مختلف پایش تغییر کاربری اراضی/پوشش گیاهی با استفاده از RS و GIS (مطالعه موردی: حوزه دره شهر-استان ایلام)، مجله علوم محیطی، سال 8، شماره 3، صفحات 81-96.
2- ابطحی، پاک‌پرور؛ مرتضی، مجتبی؛ 1381؛ بررسی روند تغییرات کاربری اراضی در منطقه کاشان، مجله تحقیقات مرتع و بیابان ایران، جلد 6، صفحات 85 - 104.
3- اسلمی، قربانی، سبحانی، پناهنده؛ فرنوش، اردوان، بهروز، محسن؛ 1393؛ مقایسه روش های شبکه عصبی مصنوعی، ماشین بردار پشتیبانی و شیءگرا در استخراج کاربری و پوشش اراضی از تصاویر لندست 8.، مجله سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، سال 6، شماره 3، صفحات 1-14.
4- جعفری، حمزه، نصیری، رفیعی؛ حمیدرضا، محمد، حسین، یوسف؛ 1390؛ توسعه مدل مفهومی مبتنـی بـر الگوریتم Decision Tree  داده کاوی به منظور آشکارسازی تغییرات پوشش اراضی با استفاده از تصاویر سنجنده TM و داده های کمکـی (مطالعه موردی: بخش مرکزی شهرستان بویراحمد)، نشریه علوم محیطی، سال 8، شماره 3، صفحات 20-1.
5- حیدری زاده، محمدی؛ زهرا، عبدالرضا؛ 1395؛ پیش بینی تغییرات کاربری اراضی در دشت مهران با استفاده از مدل سلول های خودکار مارکوف، مجله مهندسی اکوسیستم بیابان، شماره 10، صفحات 57-68.
6- ربیعی، ضیائیان، علیمحمدی؛ حمیدرضا، پرویز، عباس؛ 1384؛ کشف و بازیابی تغییرات کاربری و پوشش اراضی شهر اصفهان به کمک سنجش از دور و سیستم اطلاعات جغرافیایی، فصلنامه مدرس علوم انسانی، دوره 9، شماره 4، صفحات 41-54.
7- رسولی، علی اکبر؛ 1387؛ مبانی سنجش از دور کاربردی با تأکید بر پردازش تصاویر ماهواره‌ای، انتشارات دانشگاه تبریز، چاپ اول، تبریز، 777 صفحه.
8- روستا، منوری، درویشی، فلاحتی؛ زهرا، سید مسعود، مهدی، فاطمه؛ 1391؛ کاربرد داده های سنجش از دور و سیستم اطلاعات جغرافیایی در استخراج نقشه های کاربری اراضی شهر شیراز، مجله آمایش سرزمین، شماره 6، صفحات 149-164.
9- زنگنه شهرکی، کاظم زاده، هاشمی دره بادامی؛ سعید، علی، سیروس؛ 1393؛ تحلیل زمانی- مکانی گسترش کالبدی شهر مشهد و پایش تغییرات کاربری اراضی اطراف، پژوهش‌های جغرافیای برنامه ریزی شهری، دورة 2. شمارة 4، صفحات 483-499.
10-  فاطمی، رضایی؛ سید باقر، یوسف؛ 1389؛ مبانی سنجش از دور، انتشارات آزاده، چاپ دوم، تهران، 288 صفحه.
11- فرج‌الهی، عسگری، اونق، محبوبی، سلمان ماهینی؛ اصغر، حمیدرضا، مجید، محمدرضا، عبدالرسول؛ 1394؛ پایش و پیش بینی روند تغییرات مکانی و زمانی کاربری/ پوشش اراضی (مطالعة موردی: منطقة مراوه‌تپه، گلستان)، نشریه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، دوره 6، شماره 4، صفحات 1-14.
12- فیضی‌زاده، جعفری، نظم‌فر؛ بختیار، فیروز، حسین؛ 1387؛ کاربرد داده‌های سنجش از دور در آشکارسـازی تغییـرات کـاربری‌هـای اراضی شهری (مطالعه موردی فضای سبز شهر تبریز، نشریه هنرهای زیبا، شماره 34، صفحات 24-17.
13- قرائتی جهرمی، ولی، موسوی، پناهی، خسروی؛ مجتبی، عباسعلی، سیدحجت، فاطمه، حسن؛ 1393؛ پایش تغییرات کاربری اراضی دشت کاشان با استفاده از داده‌های دور سنجی، مجله بین المللی علمی - تحقیقاتی زمین پویا، جلد 4، شماره 2، صفحات 129-137.
14- لیلسند، توماس م.، کیفر، رالف و.؛ 1387؛ سنجش از دور و تفسیر تصاویر ماهواره‌ای، ترجمه جعفر اولادی قـادیکلایی، انتشارات دانشگاه مازندران، چـاپ اول، بابلسر، 835 صفحه.
15- معاونت برنامه‌ریزی و پژوهش شهرداری شهرکرد؛ 1391؛ آمارنامه‌های سال 91 شهر شهرکرد، جلد اول، سرزمین و آب و هوا، شهرکرد، صفحات 11-25 .
16- میرزایی زاده، نیک نژاد، اولادی قادیکلایی؛ وحید، مریم، جعفر؛ 1394؛ ارزیابی الگوریتم های طبقه بندی نظارت شده غیرپارامتریک در تهیة نقشه پوشش زمین با استفاده از تصاویر لندست 8، نشریه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، دوره 6، شماره 3، صفحات 29-44.
17. Arulbalaji, P., Gurugnanam, B., 2014, Geospatial Science for 16 Years of Variation in Land Use/Land Cover Practice Assessment around Salem District, South India, Journal of Geosciences and Geomatics, 2(1), pp 17-20.
18. Baker, WL., 1989, A review of models of landscape change. Landscape Ecology, 2(2), pp 111-133.
19. Gao, J., Liu, Y., Chen, Y., 2006, Land cover changes during agrarian restructuring in Northeast China, Applied Geography, 26, pp 312–322.
20. Guan, D., Li, H., Inohae, T., Su, W., Nagaie, T., Hokao, K., 2011, Modeling urban land use change by the integration of cellular automaton and Markov model, Ecological Modelling, 222(20), pp 3761-3772.
21. Jensen, J.R., 2005, Introductory digital image processing: A remote sensing perspective (3rd Edn), Upper Saddle River, NJ: Prentice-Hall.
22. Lambin, E.F., 1997, Modelling and monitoring land-cover change processes in tropical regions, Progress in Physical Geography, 21(3), pp 375-393.
23. Li, Z., Li, X., Wang, Y., Ma, A., Wang, J., 2004, Land-use change analysis in Yulin prefecture, northwestern China using remote sensing and GIS, International Journal of Remote Sensing, 23(24), pp 5691-5703.
24. Lu, D., Mausel, P., Brondizio, E., Moran, E., 2004, Change detection techniques, International Journal of Remote Sensing, 25(12), pp 2365-2407.
25. Pal, M., Mather, P.M., 2005, Support vector machines for classification in remote sensing, International Journal of Remote Sensing 26 (5), pp 1007-1011.
26. Parker, D.C., Manson, S.M., Janssen, M.A., Hoffmann, M.J., Deadman, P., 2003, Multi-agent systems for the simulation of land-use and land-cover change: a review, Annals of the Association of American Geographers, 93(2), pp 314-337.
27. Ramamohana Rao, P., Hathiram, G., Bhakta Thukaram, G., Anand Kumar, S., 2015, Landuse and land cover analysis using remote sensing and GIS, a case study of Khammam District, Telengana State, India, International Journal of Recent Scientific Research Research, 6(7), pp 5465-5468.
28. Richard, A., 2003, Modelling of landuse change in Montana from 1860 to 2000, Applied Geography, 25, pp 47-63.
29. Richards, J.A., Jia, X., 1999, Remote Sensing Digital Image Analysis: An Introduction, Journal of Landscape and Urban Planning, 59(1), pp 43-57.
30. Ridd, M.K., Liu, J., 1998, A Comparison of Four Algorithms for Change Detection in an Urban Environment, Journal of Remote Sensing Environment, 63, pp 95-100.
31. Robert Pontius, 2013, Land use and Land cover changes in climate changes, The encyclopedia of Earth., Article 154143.
32. Shi, Z., Wang, R., Huang, MX., 2002, Detection of Coastal Saline Land Uses with Multi Temporal Landsat Images in Shangyu City China, Environmental Management, 30, pp 142-150.
33. Singh, A., 1989, Digital change detection techniques using remotely-sensed data, International Journal of Remote Sensing, 10 (6), pp 989-1003.
34. Stavros, K., Chrysostomos, D.S., 2013, Identification of land cover/land use changes in the greater area of the Preveza peninsula in Greece using Landsat satellite data, Applied Geography, 40, pp 150-160.
35. Stephenne, N., Lambin, E., 2001, A dynamic simulation model of land-use changes in Sudano-sahelian countries of Africa (SALU), Agriculture, Ecosystems & Environment, 85(1), pp 145-161.
36. Uma Maheswari, R., Rajkumar, R.OM., Surendran, A., Krishnamoorthy, B.S., 2015, Monitoring changes in land use/ land cover using multi temporal/sensor satellite data (a case study in palani). International Journal of Recent Scientific Research, 6(2), pp 2867- 2870.
37. Verburg, P.H., Schot, P.P., Dijst, M.J., Veldkamp, 2004, Land use change modeling: current practice and research priorities, Geo Journal, 61(4), pp 309-324.
38. Wakeel, A., Rao, K.S., Maikhuri, R.K., Saxena, K.G., 2005, Forest management and land use/cover changes in a typical micro watershed in the mid elevation zone of Central Himalaya, India, Forest Ecology and Management, 213, pp 229–242.