Semi-automatic object-based model to produce the inventory map of gully erosion (Case study: Lighvan watershed)

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MOHAMMADI P.; AHMADI A.; FEIZIZADEH B.; JAFARZADEH A.A.; RAHMATI M.

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Journal: Journal of Water and Soil Conservation Year:2019 | Volume:26 | Issue:3 Page(s): 29-49

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Title

Semi-automatic object-based model to produce the inventory map of gully erosion (Case study: Lighvan watershed)

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ClassificationQ1

Object Oriented AlgorithmsQ1

Object-Oriented ProcessingQ1

SegmentationQ2

Abstract

Background and Objectives: Locating in arid and semi-arid region, Iran is always affected by sloping instability and erosion, especially gully erosion. This erosion pattern has occurred in different parts of Iran continuously over many years, and during erosion process and transferring the high amount of sediment has caused the destruction of roads, infrastructures, pasturelands, hillslopes, etc. which makes it necessary to identify high-risk areas and to develop sensitivity maps. In recent years, the processing of satellite images as an advanced method with the aim of increasing the accuracy and saving time and cost has been widely used by researchers. The object-oriented analysis of images is one of the most important methods for extracting information from satellite imagery, which is based on spectral, form and spatial characteristics and using expert knowledge to identify complications. Materials and Methods: In this research, the Lighwan watershed was studied as one of the most important sub-basins of Aji Chay in the East Azarbaijan Province. The images of Sentinel-2 (2016) with spatial resolution of 10, 20 and 60 meters were used for the processing and identification of gully erosion sites. The images were processed using the eCognition software and applied with different types of algorithms to design a semi-automatic model based on object-oriented analysis. Finally, in order to evaluate the accuracy of the model, the identified gully affected area were mapped out and calculated using ArcGIS software to match the ground truth map and to calculate the error matrix, manufacturer accuracy, user accuracy and kappa coefficient for each of the algorithms. Results: The results showed that the density and compactness algorithms had the highest and lowest accuracy of the manufacturer (manufacturer accuracies were 88 and 78), respectively. While based on Kappa coefficient, the asymmetry algorithm had the highest accuracy compared to other methods (kappa = 0. 91). Then, the shape index and density algorithms with kappa coefficient of 0. 89 and 0. 85 provided acceptable accuracy for the Classification and identification of the gully. Conclusion: In the present study, semi-automatic semi-automatic model for ditch identification was presented using spectral and geometric properties of Sentinel-2 satellite images and Object-Oriented Processing in eCognition software environment. The use of object-oriented methods due to the increased accuracy of classifying and identifying surface effects and phenomena can be used as a suitable solution for future soil studies and natural phenomena.

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APA: Copy

MOHAMMADI, P., AHMADI, A., FEIZIZADEH, B., JAFARZADEH, A.A., & RAHMATI, M.. (2019). Semi-automatic object-based model to produce the inventory map of gully erosion (Case study: Lighvan watershed). JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), 26(3 ), 29-49. SID. https://sid.ir/paper/156520/en

Vancouver: Copy

MOHAMMADI P., AHMADI A., FEIZIZADEH B., JAFARZADEH A.A., RAHMATI M.. Semi-automatic object-based model to produce the inventory map of gully erosion (Case study: Lighvan watershed). JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES)[Internet]. 2019;26(3 ):29-49. Available from: https://sid.ir/paper/156520/en

IEEE: Copy

P. MOHAMMADI, A. AHMADI, B. FEIZIZADEH, A.A. JAFARZADEH, and M. RAHMATI, “Semi-automatic object-based model to produce the inventory map of gully erosion (Case study: Lighvan watershed),” JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), vol. 26, no. 3 , pp. 29–49, 2019, [Online]. Available: https://sid.ir/paper/156520/en

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