Remote Sensing Image Fusion for Unsupervised Land Cover Classification

Chaâbane, F.

doi:10.5772/14221

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…In past the classification and planning organized in Almadinah city has been done based on traditional method of map digitizing of land cover classes and change detection were based in field survey [3,6,8]. This technique is useful for small area land cover classification but can't classify large area with many type of coverage classes and these methods are time consuming, it needs more effort and its low accuracy of land cover land use classification.…”

Section: Introductionmentioning

confidence: 99%

Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia

Daqamseh

2017

IJARSG

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In this study IKONOS images with high spatial resolution have been used for urban planning classification. This research explores approaches to improve urban planning and build up the data base for types of patterns area within the urban scheme in central of Almadinah Almunawarah using remote sensing based on Texture Analysis Applications and Geospatial Information System (GIS softwares). It has been compared with Traditional method (Field Survey) of urban planning classification in Almadinah Almunawarah. The activities of central Almadinah was divided into commercial area, investment area, industrial area, health services building, religious building, garden, infrastructure, government services building, and agricultural area. The results of this study showed the commercial and investments area was the largest area 6.5 km, and it is followed by religious services 3.2 km, while the third ring area the largest area was the agricultural housing area 16 km and then followed by commercial and investments area 5.3 km of the total area. This study recommends to use remote sensing data to classify the urban planning due to significantly improve land cover classification performance compare to traditional survey.

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Section: Introductionmentioning

confidence: 99%

Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia

Daqamseh

2017

IJARSG

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Application of innovative space technology approaches to the sustainability of agricultural systems in the developing world

Lamba

Rani²,

Kumar

2021

Remote Sensing Letters

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Pixel and region based temporal classification fusion for HR Satellite Image Time Series

Réjichi

Chaâbane

2012

2012 IEEE International Geoscience and Remote Sensing Symposium

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Satellite Image Time Series (SITS) are a very useful source of information for geoscientists especially for land cover monitoring. In this paper a new temporal classification approach for High Resolution (HR) SITS is proposed. It suggests a Bayesian combination between a pixel and a region, SVM (Support Vector Machine) based techniques where SVM is considered as a probabilistic classifier. RBF (Radial Basis Function) based SVM kernel is used to classify pixel evolution while a graph based SVM kernel is considered to analyze region temporal behavior.

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Remote Sensing Image Fusion for Unsupervised Land Cover Classification

Cited by 3 publications

References 21 publications

Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia

Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia

Application of innovative space technology approaches to the sustainability of agricultural systems in the developing world

Pixel and region based temporal classification fusion for HR Satellite Image Time Series

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