Statistical, structural, hybrid, and graph theoretical features to measure land development
IEEE Geoscience and Remote Sensing Letters, cilt.6, sa.1, ss.72-76, 2009 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 6 Sayı: 1
- Basım Tarihi: 2009
- Doi Numarası: 10.1109/lgrs.2008.2007753
- Dergi Adı: IEEE Geoscience and Remote Sensing Letters
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.72-76
- Anahtar Kelimeler: Fusion of features, Graph theoretical features, Hybrid features, Land development, Multispectral information, Structural features
- İstanbul Medipol Üniversitesi Adresli: Hayır
Özet
Extracting information on a developing region from its sequential satellite images has many benefits. Therefore, in a previous study, we introduced graph theoretical and conditional statistical features to measure land development in a predefined region. There, we only used the grayscale information from the satellite image at hand. Here, we extend that work by introducing novel statistical, hybrid, and graph theoretical features using multispectral information. We also introduce novel structural features based on three different structure extraction methods. We test our new features on a diverse data set and report their performances in measuring land development. © 2006 IEEE.