بررسی روند بیابان‌زایی در مرکز استان خوزستان با استفاده از داده‌های سری‌های زمانی سنجش از دور

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دوره دکتری گروه بیابان زایی دانشکده ی منابع طبیعی و علوم زمین دانشگاه کاشان

2 دانشیار دانشکده:دانشکده منابع طبیعی و علوم زمین گروه:بیابان زدائی، دانشگاه کاشان، کاشان، ایران

3 استادیار گروه هیرولوژی و منابع آب، دانشکده‌ی مهندسی آب و محیط زیست، دانشگاه شهید چمران اهواز، اهواز، ایران

چکیده

مناطق خشک اغلب تحت تأثیر فرسایش سریع خاک، تخریب زمین و بیابان‌زایی قرار می‌گیرند. داده‌های سنجش از دور با داشتن اطلاعات مکانی و زمانی، ابزار مناسبی جهت ارزیابی و بررسی این پدیده‌ها می‌باشند. در پژوهش حاضر از سری‌های زمانی شاخص‌های سنجش از دوری TGSI و آلبدو جهت پایش روند بیابان‌زایی در مرکز استان خوزستان استفاده شد. پس از محاسبه‌ی شاخص‌های ذکر شده با استفاده از تصویر سنجنده‌ی ETM+ برای سال‌های 2019-1999، مقادیر 411 نمونه‌ی تصادفی انتخاب شده روی تصاویر، برای ساخت مدل فضای ویژگی Albedo-TGSI در هر سال به کار رفت و همبستگی بین متغیر‌ها به میزان 83/0-48/0 در سال‌های مختلف محاسبه گردید. سپس معادله‌ی درجات بیابان‌زاییDDI  بر اساس شیب خط برازش داده شده به­دست آمد و مقدار شاخص بیابان­زایی برای هر نقطه در هر سال محاسبه شد. در مرحله‌ی بعد با اعمال طبقه‌بندی شکست طبیعی بر روی شاخص DDI، درجات مختلف بیابان‌زایی و همچنین مقادیر شکست و حدی درجات مختلف برای نمونه‌های تصادفی حاصل شد. سپس میانگین این حدود برای هر طبقه در هر سال محاسبه شد و به­عنوان نماینده‌ی آن طبقه در همان سال در سری زمانی قرار گرفت. به این ترتیب 5 سری زمانی از درجات بیابان‌زایی در سال های 2019-1999 به­دست آمد و در نهایت آزمون روند من کندال، برای هر سری زمانی در سطح معنی داری 10% و 5% انجام شد. نتایج نشان داد هیچ یک ازسری‌ها، به غیر از سری زمانی بیابان‌زایی زیاد، در سطح 5% روند معناداری از خود نشان ندادند. ولی دو طبقه‌ی بیابان‌زایی شدید و بیابان‌زایی زیاد به­ترتیب با مقادیر p-value، 90/0 و 50/0روند معناداری در سطح 10% از خود نشان دادند. همچنین نقشه‌ی توزیع مکانی میانگین تغییرات روند شاخص بیابان‌زایی در طبقات مختلف، نشان داد در مجموع، نزدیک 81% منطقه در طبقات بیابان‌زایی شدید و زیاد با روند افزایشی بیابان‌زایی معنادار قرار گرفت.

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of Desertification Trend in the Center of Khuzestan province Using Remote Sensing Time Series Data

نویسندگان [English]

  • Sareh Hashem Geloogerdi 1
  • Abbasali Vali 2
  • Mohammad Reza Sharifi 3
1 Ph.D. student desert management and control department. university of Kashan.Iran
2 Associate Professor: Combating Desertification: Faculty of Natural Resources and Earth Sciences: University of Kashan: Kashan: Iran
3 Assistant Professor, Department of Hydrology and water resourses: Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
چکیده [English]

Aired areas are often affected by rapid soil erosion, land degradation, and desertification. Therefore, continuous monitoring of land cover changes is required. Remote sensing data with spatial and temporal information are suitable for this purpose. In the present study, the time series of TGSI and Albedo remotely sensed indexes were used to monitor desertification in the center of Khuzestan province. After constructing the above-mentioned indexes for the period of 1999-2019 using ETM+ sensor images, the values of 411 randomly selected samples on the images were used to construct the Albedo-TGSI feature space model for each year and the correlation between the variables was calculated 0/48-0/83 in different years. The DDI (Desertification Degree Index) was then obtained based on the slope of the fitted line, and the value of DDI was calculated for each sample in each year. By applying a natural break classification on DDI, different levels of desertification and the break values were obtained and considered as the representative of the class in each year. Therefore, five time series of five desertification degrees were formed. Finally, a Man Kendall trend test was carried out with %95 and %90 confidence levels. The results showed that none of the series, except for the high desertification degree, showed a significant trend at the level of 5%. However, severe and high desertification degrees time series with p-value, 0.090 and 0.050 values showed a significant trend at the level of 10%, respectively. Also, the spatial distribution map of the average changes in the trend of desertification index in different classes, showed that in total, about 81% of the region was in severe and high desertification classes with a significant increasing trend of desertification.The results showed a high desertification degree at %5 significant level, and a sever desertification degree at %10 significant levels, showing increasing desertification trend. Furthermore, the spatial distribution of average DDI index indicated that about %81 of the study area was in severe and high desertification classes with a significant increasing trend.

کلیدواژه‌ها [English]

  • ETM+ image
  • DDI Index
  • Natural break classification
  • Man-Kendall trend test
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