مدل‌سازی افرازی سطوح فرسایش و رسوب بر مبنای خصوصیات خاک سطحی با استفاده از داده‌های سنجش از دور (RS)

نوع مقاله : مقاله پژوهشی

نویسندگان

• میترا یاراحمدی ¹
• عطااله خادم الرسول ²
• هادی عامری خواه ³

¹ گروه خاکشناسی دانشکده کشاورزی دانشگاه شهید چمران اهواز

² دانشیار گروه خاکشناسی، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، ایران

³ مربی گروه خاکشناسی دانشکده کشاورزی دانشگاه شهید چمران اهواز

چکیده

کلیدواژه‌ها

• الگوریتمهای نظارت شده
• سطوح فرسایشی و رسوبی
• شاخصهای سنجش از دور
• طیف سنجی
• مدلسازی افرازی

موضوعات

• فرسایش و حفاظت خاک

عنوان مقاله [English]

Demarcation modeling of erosional and depositional surfaces with soil characteristics and remote sensing (RS)

نویسندگان [English]

• Mitra Yarahmadi ¹
• Ataallah Khademalrasoul ²
• Hadi Amerikhah ³

کلیدواژه‌ها [English]

• Demarcation modeling
• erosional and depositional surfaces
• remote sensing indicators
• spectrometry
• supervised algorithms

EXTENDED ABSTRACT

Introduction:

Soil erosion is the most common form of soil degradation all over the world. Soil erosion including on-site and off-site effects; the off-site effect of soil erosion is soil deposition. In order to assess the effects of soil erosion it is necessary to apply different methods and techniques. In this regard demarcation modeling based on remote sensing is the applicable technique which is usable for soil classification, ultimately precise soil erosion control at different scales. Therefore this study was conducted to evaluate the applicability of demarcation modeling to diagnostic soil erosional and depositional surfaces using remote sensing indices. 

Material and methods:

Regarding the importance of selection and implementation of conservational scenarios to manage the costs; necessarily has to concern on highlighting the erosional and depositional surfaces in the watersheds. Zahirieh area in Khuzestan Province with approximately 7100 ha and water erosion risks mainly gully and rill erosion types selected then using the filed survey and satellite images (Landsat 8 images from 2022) divided to erosional, depositional and stable areas. In this study 70 randomized sampling points using the Create Random Points tool in ArcGIS10.2 was created. Moreover, in the mentioned tool, the Constraining Feature Class for the polygon of the study area was set in order to limit the randomized points in the border of study area. Finally, 14 points as depositional and 12 points as erosional surfaces was highlighted and other randomized points was defined as Non-erosional surfaces. Based on soil erosional and depositional surfaces the soil sampling accomplished using the standard methods and soil samples as representative of whole area was analyzed. The physicochemical parameters of the soil consist of soil texture components (clay, silt and sand), bulk density, organic matter, phosphorus, lime, electrical conductivity, pH and soil gypsum were measured. Remote sensing indices including NDVI, SAVI, CI, BI, NDSI, NDMI and SI to assess the possibility of classification the erosional and depositional surfaces based on Landsat 8 images were calculated and mapped. In addition, supervised classification algorithms including Parallel levels, Mahalonobis distance, Maximum likelihood, Minimum distance, Neural network and Support vector machine (SVM) were used and evaluated using Kappa coefficient and overall accuracy. The statistical analyses with SPSS 26, supervised classification of remote sensing data in ENVI 4.7 and the separation of erosional and depositional surfaces in Google Earth Engine (GEE) were performed.          

Results:

The results of the average comparison test showed the significant difference between erosional and depositional surfaces for clay content and gypsum therefore, they can be used as parameters to separate surfaces, but for other parameters, no significant difference was observed. Indeed in the erosional surfaces the amount of clay was lower and amount of gypsum was higher than depositional surfaces. Furthermore the results depicted that there was a significant relation (R2:0.75) between elevation (m) and NDVI for depositional surfaces. The remote sensing (RS) indices including BI, SI and NDSI can be effectively applied to distinguish eroded surfaces from depositional surfaces in the study area.

Conclusion:

In general demarcation modeling is usable to separate the erosional and depositional surfaces in the watersheds therefore can be applied as a management tool to conserve the soils against erosive factors. Moreover, mapping the RS indices in the watersheds is a visual tool to recognize the critical areas.

Author Contributions

All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.

Data Availability Statement

If the study did not report any data, you might add “Not applicable” here.

Acknowledgements

The authors would like to thank all participants of the present study.

Ethical considerations

The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares no conflict of interest.