پایش تغییرات کاربری اراضی با استفاده از تصاویر ماهواره‌ای لندست (مورد مطالعه: دشت خانمیرزا)

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشجو

2 Dept. of Geographical Sciences and Planning, University of Isfahan, Hezarjerib St., Isfahan.

3 مرکز تحقیقات کشاورزی و منابع طبیعی

چکیده

اطلاعات دقیق و بهنگام در ارتباط با کاربری اراضی و تغییرات آن در تصمیم‌گیری‌های مدیریت شهری، پایش اکوسیستم و برنامه‌ریزی شهری بسیار حیاتی است. در دهه‌های اخیر تغییرات گسترده‌ای در کاربری اراضی در دشت خانمیرزا به‌عنوان یکی از زیرحوزه‌های آبخیز کارون شمالی رخ‌ داده است. هدف مطالعه حاضر، پایش تغییرات کاربری اراضی این دشت با استفاده از الگوریتم های مختلف می‌باشد. بدین منظور با استفاده از تصاویر ماهواره لندست 5، 7 و 8 و سنجنده‌های TM، ETM و OLI برای سه دوره 1996، 2006 و 2016 نقشه کاربری اراضی دشت خانمیرزا با استفاده از چهار الگوریتم حداکثر احتمال، شبکه عصبی مصنوعی، حداقل فاصله و فاصله ماهالانویی با استفاده از ضریب کاپا مورد ارزیابی قرار گرفت. نتایج حاصل از ارزیابی دقت این دو روش با استفاده از تعیین ضریب کاپا نشان داده است که الگوریتم شبکه‌ی عصبی مصنوعی نسبت به الگوریتم حداکثر احتمال از دقت بیشتری برخوردار است. همچنین بر اساس نتایج دو الگوریتم شبکه عصبی مصنوعی و حداکثر احتمال با دقت کلی 29/90 و 79/86 درصد، اراضی منطقه در شش کلاس کاربری (کشاورزی، مرتع، مسکونی، اراضی سنگی و لخت، باغ و اراضی پست نمدار) طبقه‌بندی شدند. تجزیه‌وتحلیل تغییرات کاربری‌ها نشان داد که اراضی کشاورزی و مسکونی، به ترتیب برابر با 5/62 و 5/3 درصد، روند افزایشی داشته‌ و از اراضی پست نمدار، مراتع و اراضی سنگی و لخت کاسته شده است. بیشترین تغییر کاربری‌ها، مربوط به تغییر اراضی سنگی و لخت (شامل اراضی بدون پوشش) به کاربری کشاورزی، به میزان 1673 هکتار از سال 2006 تا سال 2016 بوده است. از دیگر تغییر کاربری‌های مشهود در منطقه، تغییر کاربری 7/65 هکتار از اراضی سنگی و لخت و 8/40 هکتار از مراتع به اراضی مسکونی می‌باشد. به طور کلی نتایج نشان داد بهترین روش برای تهیه نقشه کاربری اراضی در منطقه مورد مطالعه، استفاده از شبکه عصبی مصنوعی است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Land Use Change Monitoring Using Landsat Satellite Image Data (Case study: Khan Mirza Plain)

نویسندگان [English]

  • taghi karimian 1
  • Abbas Amini 2
  • MOHSEN BAGHERI 3
  • HAMID GHAIUMI MOHAMMADI 3
1 student
2 Dept. of Geographical Sciences and Planning, University of Isfahan, Hezarjerib St., Isfahan.
3 Agricultural and Natural Resources Research Center
چکیده [English]

Accurate and real time information on land use and land cover and their changes is very important in urban management decisions, ecosystem monitoring and urban planning. In recent decades, widespread changes in land use of the Khan mirza plain as one of the northern Karun watersheds have occurred, that need to monitoring these changes.
In this study, Landsat 5, 7 and 8 satellite images and TM, ETM, and OLI sensors for the period of 1996, 2006, and 2016 were used to produce of land use and land cover map of Khan mirza plain by four methods: maximum likelihood, artificial neural network, minimum distance and Mahalanobis distance and theirs Kappa coefficient were evaluated.
The results of the evaluation of the accuracy of these two methods by using Kappa coefficients have shown that the artificial neural network algorithm is more accurate than the maximum likelihood algorithm. Also, by results of two algorithms of artificial neural network and maximum likelihood with an overall accuracy of 90.29 and 86.79, all of land cover maps were classified in six classes (agriculture, rangeland, residential area, rocky and bare lands, gardens and flatlands).
The analysis of the classifications showed that agricultural and residential classes had a rising trend, 62.5% and 3.5%, respectively, and rangeland, rocky and bare lands and flatlands were decreased.
The largest change is related to the conversion of rocky and bare lands class to the agricultural class, which 1673 hectares of rocky and bare lands in 2006 changes into agricultural lands in 2016. Another obvious land use change in this area, are change of rangelands into residential areas, which 40.8 ha of rangelands changed into residential area.
In overall, this research showed that the best way to produce of land use map in the study area is to use artificial neural network algorithm. According to the results, it is suggested using this method to produce of land use change map for this region.
Accurate and real time information on land use and land cover and their changes is very important in urban management decisions, ecosystem monitoring and urban planning. In recent decades, widespread changes in land use of the Khan mirza plain as one of the northern Karun watersheds have occurred, that need to monitoring these changes.
In this study, Landsat 5, 7 and 8 satellite images and TM, ETM, and OLI sensors for the period of 1996, 2006, and 2016 were used to produce of land use and land cover map of Khan mirza plain by four methods: maximum likelihood, artificial neural network, minimum distance and Mahalanobis distance and theirs Kappa coefficient were evaluated.
The results of the evaluation of the accuracy of these two methods by using Kappa coefficients have shown that the artificial neural network algorithm is more accurate than the maximum likelihood algorithm. Also, by results of two algorithms of artificial neural network and maximum likelihood with an overall accuracy of 90.29 and 86.79, all of land cover maps were classified in six classes (agriculture, rangeland, residential area, rocky and bare lands, gardens and flatlands).
The analysis of the classifications showed that agricultural and residential classes had a rising trend, 62.5% and 3.5%, respectively, and rangeland, rocky and bare lands and flatlands were decreased.
The largest change is related to the conversion of rocky and bare lands class to the agricultural class, which 1673 hectares of rocky and bare lands in 2006 changes into agricultural lands in 2016. Another obvious land use change in this area, are change of rangelands into residential areas, which 40.8 ha of rangelands changed into residential area.
In overall, this research showed that the best way to produce of land use map in the study area is to use artificial neural network algorithm. According to the results, it is suggested using this method to produce of land use change map for this region.
Accurate and real time information on land use and land cover and their changes is very important in urban management decisions, ecosystem monitoring and urban planning. In recent decades, widespread changes in land use of the Khan mirza plain as one of the northern Karun watersheds have occurred, that need to monitoring these changes.
In this study, Landsat 5, 7 and 8 satellite images and TM, ETM, and OLI sensors for the period of 1996, 2006, and 2016 were used to produce of land use and land cover map of Khan mirza plain by four methods: maximum likelihood, artificial neural network, minimum distance and Mahalanobis distance and theirs Kappa coefficient were evaluated.
The results of the evaluation of the accuracy of these two methods by using Kappa coefficients have shown that the artificial neural network algorithm is more accurate than the maximum likelihood algorithm. Also, by results of two algorithms of artificial neural network and maximum likelihood with an overall accuracy of 90.29 and 86.79, all of land cover maps were classified in six classes (agriculture, rangeland, residential area, rocky and bare lands, gardens and flatlands).
The analysis of the classifications showed that agricultural and residential classes had a rising trend, 62.5% and 3.5%, respectively, and rangeland, rocky and bare lands and flatlands were decreased.
The largest change is related to the conversion of rocky and bare lands class to the agricultural class, which 1673 hectares of rocky and bare lands in 2006 changes into agricultural lands in 2016. Another obvious land use change in this area, are change of rangelands into residential areas, which 40.8 ha of rangelands changed into residential area.
In overall, this research showed that the best way to produce of land use map in the study area is to use artificial neural network algorithm. According to the results, it is suggested using this method to produce of land use change map for this region.

کلیدواژه‌ها [English]

  • Khan Mirza Plain
  • Land Use Change
  • Landsat
  • Satellite images
  • monitoring

مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از تاریخ 05 آذر 1397
  • تاریخ دریافت: 30 تیر 1397
  • تاریخ بازنگری: 30 آبان 1397
  • تاریخ پذیرش: 05 آذر 1397