Object based interpretation of high spatial remote sensing images based on knowledge-based systems

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KIANI ABBAS; EBADI HAMID; khanlou Hekmat allah

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Journal: Iranian Journal of Remote Sensing & GIS Year:2019 | Volume:10 | Issue:4 Page(s): 00-00

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Title

Object based interpretation of high spatial remote sensing images based on knowledge-based systems

Author(s)

KIANI ABBAS | EBADI HAMID | khanlou Hekmat allah | Issue Writer Certificate

Keywords

classification –High spatial imageQ2

knowledge based systemQ1

Object based interpretationQ1

Abstract

Land cover classification in remote sensing imagery is one of the most widely used spatial information extraction methods, which can facilitate generating object imagery classes of the ground surface in order to automate and accelerate meeting the basic needs of management, organization, and exploitation of the environment. Due to the similar behavior of pixels, remote-sensing image classification using merely the spectral and textural information would lead to inefficiency in the classification. In fact, in classification process, objects are commonly identified using spectral properties of image pixels. If the spatial and conceptual properties are also considered, it causes to a better distinction between image classes and closes the machine process to human interpretation and adds to the system's performance. The present research is mainly focused on the use of interactive segmentation and interpretation processes with respect to the geometry of the image classes. The accuracy of the results have improved by introducing the knowledge-based rules to control and regulate the interactive process, taking into account the geometric properties of target classes. To evaluate the efficiency of the proposed method, the results were evaluated and compared with some of the other methods on IRS satellite images in an urban area. The results showed that geometric and conceptual features as a complementary information source, improve classification results in the urban area with heterogeneous spectral effects. Overall, the proposed hybrid technique improved overall accuracy and Kappa coefficient by %8 and 11. 18, respectively.

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APA: Copy

KIANI, ABBAS, EBADI, HAMID, & khanlou, Hekmat allah. (2019). Object based interpretation of high spatial remote sensing images based on knowledge-based systems. REMOTE SENSING & GIS, 10(4 ), 00-00. SID. https://sid.ir/paper/359583/en

Vancouver: Copy

KIANI ABBAS, EBADI HAMID, khanlou Hekmat allah. Object based interpretation of high spatial remote sensing images based on knowledge-based systems. REMOTE SENSING & GIS[Internet]. 2019;10(4 ):00-00. Available from: https://sid.ir/paper/359583/en

IEEE: Copy

ABBAS KIANI, HAMID EBADI, and Hekmat allah khanlou, “Object based interpretation of high spatial remote sensing images based on knowledge-based systems,” REMOTE SENSING & GIS, vol. 10, no. 4 , pp. 00–00, 2019, [Online]. Available: https://sid.ir/paper/359583/en

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