Geomorphology
musa abedini; shahram roostaei; Mohammad Hossein Fathi
Volume 22, Issue 66 , January 2019, , Pages 187-205
Abstract
Diagnosis and classification of landslides is a critical need in the risk analysis before and after the disaster. And primarily through land surveying or traditional interpretation of images was done. In this paper to identify and classify types of object-oriented approach landslide has been paid. The ...
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Diagnosis and classification of landslides is a critical need in the risk analysis before and after the disaster. And primarily through land surveying or traditional interpretation of images was done. In this paper to identify and classify types of object-oriented approach landslide has been paid. The data used in this study consisted of false color images obtained from satellite data Resourcesat-1 with spatial resolution of 5.8 meters and digital elevation models with 2.5-meter resolution satellite image of 10 meters of Cartosat-1 was used. This method was used for the North West basin and then used without further reforms in the eastern part of the basin. A total of three sliding using this method accurately identified 71.11% and 91.4% classification accuracy has been detected. In this way, the landslide early detection of high accuracy and speed, hence has great potential to assist in risk analysis, disaster management and decision making process after the earthquake or heavy rainfall, can be used related entities, including crisis management headquarters, natural resources and watershed institutions.
GIS&RS
bakhtiar feizizadeh; seyed mohammad hassanitabar; Jafar Jafarzadeh
Volume 22, Issue 65 , November 2018, , Pages 223-241
Abstract
Segmentation is one of the basic method of the information extraction within the object-based image analysis (OBIA) approach. This process separates initial and main objects which are basis for OBIA. According to this, generating appropriate segments plays an important role for performing high accurate ...
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Segmentation is one of the basic method of the information extraction within the object-based image analysis (OBIA) approach. This process separates initial and main objects which are basis for OBIA. According to this, generating appropriate segments plays an important role for performing high accurate object-based classification. Within this research, we aimed to employ multi spectral and spatial satellite images including: IRS, Quick Bird and Spot5, for the purpose of image fusion and optimizing the scale of segmentation. For this to happen, Multi-resolution segmentation approach was performed based on various satellite images with different spatial resolution. As that, spatial information of Quick Bird and panchromatic band of IRS and Spot5 images, alongside spectral resolution of Spot5 (red band, especially) and Quick Bird, have a significant impact in increasing the contrast of image and improve the quality of segmentation, subsequently. The results of this research, indicate the importance of applying spatial information for optimizing the scale of segmentation. In addition, results confirmed that object based image fusion techniques can be employed for integrating different spatial resolution of satellite images. It also turned out that integrating lower spatial resolution with high spatial resolution is an efficient procedure for improving segmentation quality. The results of research, are great of importance for identifying different segmentation approach of object-based classification. The achieved results are also important for executive departments such as Natural resource, agriculture, etc. in light of presentation appropriate approach for rapid extraction of information from satellite image.
