Object-oriented information extraction of high resolution imagery based on multi-classifier fuzzy integration

2011 ◽  
Author(s):  
Yu Zeng ◽  
Jixian Zhang ◽  
Guangliang Wang ◽  
J.L. van Genderen
Keyword(s):  
High Resolution ◽  
Information Extraction ◽  
Object Oriented ◽  
High Resolution Imagery

scholarly journals Assessing Riyadh’s Urban Change Utilizing High-Resolution Imagery

Land ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 193
Author(s):  
Ali Alghamdi ◽  
Anthony R. Cummings
Keyword(s):  
Maximum Likelihood ◽  
High Resolution ◽  
Accuracy Assessment ◽  
Middle Eastern ◽  
Object Oriented ◽  
Training Data ◽  
High Resolution Imagery ◽  
Significant Research ◽  
Desert Areas ◽  
Spot 5

The implications of change on local processes have attracted significant research interest in recent times. In urban settings, green spaces and forests have attracted much attention. Here, we present an assessment of change within the predominantly desert Middle Eastern city of Riyadh, an understudied setting. We utilized high-resolution SPOT 5 data and two classification techniques—maximum likelihood classification and object-oriented classification—to study the changes in Riyadh between 2004 and 2014. Imagery classification was completed with training data obtained from the SPOT 5 dataset, and an accuracy assessment was completed through a combination of field surveys and an application developed in ESRI Survey 123 tool. The Survey 123 tool allowed residents of Riyadh to present their views on land cover for the 2004 and 2014 imagery. Our analysis showed that soil or ‘desert’ areas were converted to roads and buildings to accommodate for Riyadh’s rapidly growing population. The object-oriented classifier provided higher overall accuracy than the maximum likelihood classifier (74.71% and 73.79% vs. 92.36% and 90.77% for 2004 and 2014). Our work provides insights into the changes within a desert environment and establishes a foundation for understanding change in this understudied setting.

Information Extraction of High-Resolution Remotely Sensed Imagery Based on Object-Oriented Method

2014 ◽  
Vol 513-517 ◽  
pp. 1527-1531
Author(s):  
Fu Lei Zhan ◽  
Guo Dong Yang ◽  
Xu Qing Zhang ◽  
Xue Feng Niu ◽  
Peng Shao ◽  
...  
Keyword(s):  
High Resolution ◽  
Information Extraction ◽  
World View ◽  
Object Oriented ◽  
Object Oriented Method ◽  
Thematic Map ◽  
Remotely Sensed Imagery ◽  
Rule Sets ◽  
High Resolution Satellite Imagery ◽  
Extract Information

In this study, on the basis of pixel-based classification, object-oriented classification method was used to extract information from high resolution satellite imagery. Select the Binhai New Area as the study area,World View-2 data was selected as data sources, the rule sets of information extraction developing were established firstly, then the parameters of imagery segmentation and classification were tested repeatedly to achieve building hierarchies and map elements. The results showed that object-oriented information extraction method was feasible, and the extracted information was used to produce thematic map on the ArcGIS platform.

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