TY  - JOUR
T1  - An integrated semiautomated and transferable data driven approach for urban texture mapping
AU  - Feizizadeh, Bakhtiar
AU  - Sanaei, Fatemeh
AU  - Naboureh, Amin
AU  - Yakar, Murat
PY  - 2025
DA  - October
Y2  - 2025
DO  - 10.26833/ijeg.1681173
JF  - International Journal of Engineering and Geosciences
JO  - IJEG
PB  - Murat YAKAR
WT  - DergiPark
SN  - 2548-0960
SP  - 183
EP  - 211
VL  - 11
IS  - 1
LA  - en
AB  - Urbanization has significantly increased over the past decades, making monitoring of urban growth and urban texture essential for urban planning and sustainable development. In this context, the classification of different urban textures has gained importance, leveraging advancemnts insatellite image processing and methods such as machine learning and object-based image analysis (OBIA), as well as their integration.  The present study aims to apply and evaluate different object-based methods to map urban texture in different part of Tabriz city in Iran. To this end, five area with distinct urban texture patterns were selected and analyzed  using OBIA’s spectral and spatial features. A semiautomated OBIA approach was developed and applied to map urban textures, and its robustness and efficiency was examinedOur analysis indicated that combining the average, shape, and gray level co-occurrence matrix methods enhances the ability to identify objects in urban environments. The results highlight  the high potential of OBIA algorithms and features  in detecting and classifying urban areas. This study provides valuable insights for urban planners, offering a useful tool for informed decision-making in future urban development.
KW  - Different patterns of urban texture
KW  - Worn-out texture
KW  - Object-based image analysis
KW  - Spectral and spatial algorithms
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UR  - https://doi.org/10.26833/ijeg.1681173
L1  - https://dergipark.org.tr/en/download/article-file/4795024
ER  -