An Object-Oriented Pattern Recognition Approach for Urban Classification

Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment

Volumn , Issue , 2011, Pages 129-140

  Myint, Soe W ^a   Stow, Douglas ^b  

^a ARIZONA STATE UNIVERSITY   (United States)

^b SAN DIEGO STATE UNIVERSITY   (United States)

Author keywords

Applicability and effectiveness of two different classification approaches within object oriented image analysis paradigm, a Quickbird multispectral data; Nearest neighbor classifier extracting urban land covers; Object based approaches, to semi automated LULC mapping remote sensing and image processing research; Object oriented approach, additional selection or modification of new training samples; Object oriented classification mapping urban LULC classes, Definiens software known as eCognition to achieve OBIA; Object oriented pattern recognition approach for urban classification; Remotely sensed image data for identification and mapping of land use and landcover (LULC) classes for urban environments; Rule set classifier, time consuming with difficulty in implementation than identifying classes using a nearest neighbor classifier; Rule based detection of swimming pools one's expert knowledge, rule set for extracting a LULC class; Segmented objects, organized into image object levels known as scale levels

Indexed keywords

CLASSIFICATION (OF INFORMATION); IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; LAND USE; MAPPING; MEMBERSHIP FUNCTIONS; PIXELS; REMOTE SENSING; SAMPLING;

DEFINIENS; EXPERT KNOWLEDGE; IMAGE OBJECTS; LAND USE AND LAND COVER; NEAREST NEIGHBOR CLASSIFIER; OBJECT-ORIENTED IMAGE ANALYSIS; SEMI-AUTOMATED; TRAINING SAMPLE; URBAN CLASSIFICATION; URBAN LAND COVER;

OBJECT ORIENTED PROGRAMMING;

EID: 84875631954     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470979563.ch9     Document Type: Chapter

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