Land use mapping of Kaftareh Watershed of Ardabil using visual and digital processing of ETM+ image

Subject Areas : forest

ardavan  ghorbani ¹ (استادیار دانشکده فناوری کشاورزی و منابع طبیعی گروه مرتع و آبخیزداری دانشگاه محقق اردبیلی)
farnoosh  aslami ² (دانشجوی کارشناسی ارشد سنجش از دور و سیستم اطلاعات جغرافیایی)
saeed  ahmadabadi ³ (دانش آموخته کارشناسی ارشد سنجش از دور و سیستم اطلاعات جغرافیایی)
sahar  ghaffari ⁴ (دانشجوی دکترای علوم مرتع دانشگاه محقق اردبیلی)

Received: 2015-01-02 Accepted : 2015-08-05 Published : 2016-02-20

Keywords: land use, Supervised classification, Accuracy assessment, Land cover, Visual interpretation, objected-based image analysis, Ardabil province,

Abstract :

Abstract The availability of land use information permits decision-makers to develop plans in short to long-term period for the conservation, sustainable use and development of natural resources and watersheds. In this study, ETM+ image (2006), GPS and GIS were used for image interpretation, field data collection and land use mapping. Preprocessing and required correction have conducted. Initially, field visit have been conducted and different land uses have been defined. In the second step, image was visually interpreted and then training area has selected and using the maximum likelihood algorithm image was classified. According to the lack of the capability for detecting river beds and residential areas in digital image processing, integration of visual and digital interpretation (supervised classification) and object-based image analysis were used. Results show that, in visual interpretation, there is almost no capability to discriminate rangeland from dry farming land uses; however garden, residential areas and riverbeds are discriminated. Results of supervised classification show that there are problems to detect and discriminate different land uses; however, by integration of digital and visual interpretation, it is possible to use Landsat data to discriminate different land uses in the areas such as Kaftareh watersheds and Arshagh region of Ardabil province. The results of the evaluation of object-based classification accuracy showed the highest overall accuracy, because the method parameters such as scale, shape, tone and texture, in addition to using pixel values ​​were used in classification, hence with appropriate segment creation, there is the possibility of precise discrimination of land uses such as residential areas from dryland farming. In the future studies, according to the importance of land use map in the studies such as natural resources, watershed managements and agriculture, it is better to use high spatial imagery and object-based methods.     

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