پایش تغییرات کاربری اراضی با استفاده از تصاویر ماهواره‏ای لندست (مطالعه موردی: دشت خان‏ میرزا)

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری جغرافیا و برنامه ‏ریزی روستایی، دانشگاه اصفهان

2 دانشیار گروه جغرافیا و برنامه‏ ریزی روستایی، دانشکدة علوم جغرافیایی و برنامه‏ ریزی، دانشگاه اصفهان

3 عضو هیئت‏‏ علمی مؤسسة تحقیقات خاک و آبِ سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

4 عضو هیئت ‏علمی مؤسسة تحقیقات خاک و آبِ سازمان تحقیقات، آموزش و ترویج کشاورزی، اصفهان، ایران

چکیده

هدف اصلی از این تحقیق پایش تغییرات کاربری اراضی دشت خان‏میرزا با استفاده از الگوریتم‏های مختلف است که از تصاویر ماهوارة لندست 5، 7، و 8 و سنجنده‏های TM، ETM، و OLI برای سه دورة 1996، 2006، و 2016 استخراج شد و نقشة کاربری اراضی دشت با استفاده از چهار الگوریتم حداکثر احتمال، شبکة عصبی مصنوعی، حداقل فاصله، و فاصلة ماهالانویی با استفاده از ضریب کاپا ارزیابی شد. نتایج حاصل از ارزیابی دقت این دو روش با استفاده از تعیین ضریب کاپا نشان داد الگوریتم شبکة عصبی مصنوعی نسبت به الگوریتم حداکثر احتمال با ضریب از دقت بیشتری برخوردار است. همچنین، دو الگوریتم شبکة عصبی مصنوعی و حداکثر احتمال با دقت کلی 29/90 و 79/86 در شش کلاس کاربری (کشاورزی، مرتع، مسکونی، اراضی سنگی و لخت، باغ، و اراضی پست نم‏دار) طبقه‏بندی شد. تجزیه‏وتحلیل حاصل از تغییرات نشان داد کاربری‏های کشاورزی و مسکونی روند افزایشی داشته‏اند؛ به‏طوری‏که میزان این افزایش به‏ترتیب برابر با 5/62 و 5/3درصد بوده است و از اراضی پست نم‏دار، مراتع، و اراضی سنگی و لخت کاسته است. بیشترین تغییر کاربری‏ها مربوط به تبدیل کاربری اراضی سنگی و لخت به کاربری کشاورزی است که 1673 هکتار از اراضی سنگی و لخت در سال 2006 به اراضی کشاورزی در سال 2016 تبدیل‏ شده است. از دیگر تغییر کاربری‏های مشهود در منطقه تغییر کاربری اراضی سنگی و لخت و مراتع به اراضی مسکونی است؛ به‏طوری‏که 7/65 هکتار از اراضی سنگی و لخت و 8/40 هکتار از اراضی مرتع به کاربری مسکونی تبدیل ‏شده 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 4
1 student
2 Dept. of Geographical Sciences and Planning, University of Isfahan, Hezarjerib St., Isfahan.
3 Agricultural and Natural Resources Research Center
4 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
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