A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Object-based approaches for land use-land cover classification using high resolution quick bird satellite imagery (a case study: Kerbela, Iraq)
Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that use of textural data during the object image classification approach can considerably enhance land use classification performance. Moreover, the results showed higher overall accuracy (86.02%) in the o object based method than pixel based (79.06%) in urban extractions. The object based performed much more capabilities than pixel based.
Object-based approaches for land use-land cover classification using high resolution quick bird satellite imagery (a case study: Kerbela, Iraq)
Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that use of textural data during the object image classification approach can considerably enhance land use classification performance. Moreover, the results showed higher overall accuracy (86.02%) in the o object based method than pixel based (79.06%) in urban extractions. The object based performed much more capabilities than pixel based.
Object-based approaches for land use-land cover classification using high resolution quick bird satellite imagery (a case study: Kerbela, Iraq)
Jaber, Hussein Sabah (author) / Shareef, Muntadher Aidi (author) / Merzah, Zainab Fahkri (author)
2022-06-29
doi:10.3846/gac.2022.14453
Geodesy and Cartography; Vol 48 No 2 (2022); 85–91 ; 2029-7009 ; 2029-6991
Article (Journal)
Electronic Resource
English
DDC:
710
Hybrid Object-based Approach for Land Use /Land Cover Mapping using High Resolution Imagery
| BASE | 2011
Land Use and Land Cover Mapping Using Rule-Based Classification in Karbala City, Iraq
| Springer Verlag | 2018