The Comparison of Pixel and Object-based Classification for Land Use/Land Cover Mapping

Year 2018, Volume: 15 Issue: 2, 43 - 49, 31.12.2018

Derya Gülçin

https://doi.org/10.25308/aduziraat.423782

Abstract

The classification of high resolution satellite images enable planners and researchers to classify land use/land cover (LULC), which are important in terms of carrying out the planning applications both at city and landscape scale. For conducting different landscape analysis, LULC plays a significant role for numerous applications, such as urban growth analysis, deforestation, etc. Urban atlases provided by European initiatives, Coordination of Information on the Environment (CORINE) and various thematic maps are based on the classification of high resolution satellite images. As a current method, object-based classification is also used effectively in remote sensing researches. The materials of this study are Worldview ortoready pansharpened satellite image with a local resolution of 0.5 m environs the urban settlement of Aydin dated 2013, and the satellite images belong to the same year acquired from Google Earth Pro software. The research area representing urban green space, barren land, road, building, agricultural field, and shadow was chosen to classify urban LULC by supervised classification and object based classification in a comparative way. The results of the accuracy analysis demonstrate that the object-based classifier achieved a high overall accuracy (92.52%), whereas the most commonly used decision rule, namely maximum likelihood classifier, produced a lower overall accuracy (82.79%). This research shows that the object-based classifier is a significantly better approach than the classical pixel classifiers.

Keywords

supervised classification, object based classification, land use/land cover

Arazi Kullanımlarının Sınıflandırılmasında Piksel ve Obje Tabanlı Sınıflandırmanın Karşılaştırılması

Abstract

Yüksek çözünürlüklü uydu görüntülerinin sınıflandırılmasıyla oluşturulan arazi örtüsü-arazi kullanımı (AÖ/AK)
envanterleri, hem kent ölçeğinde hem de peyzaj ölçeğindeki planlama uygulamalarının yürütülmesi açısından önem
taşımaktadır. Avrupa'da alan kullanım planlaması kapsamında hazırlanan kent atlasları, peyzaj ölçeğindeki Natura 2000 ve
CORINE veri setlerine dayanan haritalar, uydu görüntülerinin yüksek doğrulukla sınıflandırılması ile oluşturulmaktadır.
Sınıflandırma tekniklerinden kontrollü ve kontrolsüz sınıflandırmanın yanı sıra, güncel bir yöntem olan obje tabanlı sınıflama
da etkin olarak kullanılmaktadır. Bu çalışmanın materyali olarak, 2013 yılına ait Aydın kentsel yerleşim merkezi sınırındaki 0.5
m yersel çözünürlüğe sahip Worldview Ortoready Pansharpened uydu görüntüsü ve görüntünün yorumlanmasında Google
Earth Pro yazılımının geçmiş görüntüleri arasında aynı yılı kapsayan hava fotoğrafları kullanılmıştır. Kentsel alan kullanımlarını
örnekleyecek düzeyde seçilen çalışma alanı, kontrollü ve obje tabanlı sınıflandırma tekniği ile sınıflandırılarak, sınıflandırma
sonuçları karşılaştırmalı olarak değerlendirilmiştir. Doğruluk analizi sonuçlarına göre, kontrollü sınıflandırma için hesaplanan
ortalama doğruluk değeri %82.79, obje tabanlı sınıflandırma için hesaplanan ortalama doğruluk değeri %92.52 olarak elde
edilmiştir.

Keywords

piksel tabanlı sınıflandırma, obje tabanlı sınıflandırma, kentsel alan kullanımları

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