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.
GIS&RS
Jafar Jafarzadeh; Hashem Rostamzadeh; Mohammadreza Nikjoo; Esmaeil Asadi
Abstract
The study of changes in water resources in each region is essential to manage water resources and using them. In this study, the goal is to evaluate the available water resources in the plain of Ardebil in terms of surface and subsurface resources based on four criteria including natural, hydrological, ...
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The study of changes in water resources in each region is essential to manage water resources and using them. In this study, the goal is to evaluate the available water resources in the plain of Ardebil in terms of surface and subsurface resources based on four criteria including natural, hydrological, agricultural and humanitarian by using fuzzy network analysis. In order to assess better fuzzy network analysis evaluation, sub-criteria of population, industry condition, rainfall situation, the status of surface water (volume taken from the river) and groundwater (wells, springs and aqueducts status), the area under cultivation and the type of products in terms of water demand, slope and elevation are used. Dependencies among sub-criteria using DEMATEL fuzzy technique and according to experts are determined. Using the fuzzy network analysis all criteria and sub- criteria are weighed, and the maps for all sub-criteria, are generated in according to the weight obtained. Finally, the result map that is based on initial layers and weighted based on the fuzzy techniques is generated in GIS. The resulting map is identified the sensitivity of the study area in terms of potential water resources. The study area (Ardebil plain) is located in the northwest of Iran and is delimited by latitudes 38°05′ N and 38° 30′N and longitudes 48°15′ E and 48° 35′E. The average height is about 1360 meters from the sea level. It covers an area of about 820 km2 and is part of Qara Soo river basin. The low risk areas 11.13 % equivalent to 9200 hectares are located on the northern and a bit in west of the plain. The average risk areas 19.36 % equivalent to 15870 hectares are located in the north and west of plain. The high risk areas 21.3 % equivalent to 17510 hectares are located mostly in the central and upper parts of the plain. The vulnerable risk areas 31.9 % equivalent to 26220 hectares are located in the southern and central parts of the plain and finally the critical areas 16.1 % equivalent to 13250 hectares are scattered mostly in the south and east of the study area.
