A comparison of object-based with pixel-based land cover change detection in the baltimore metropolitan area using multitemporal high resolution remote sensing data

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 4, Issue 1, 2008, Pages

  Zhoua, Weiqi ^a   Troya, Austin ^a   Grove, Morgan ^b  

^a UNIVERSITY OF VERMONT   (United States)

^b USDA FOREST SERVICE   (United States)

Author keywords

Baltimore; High spatial resolution image; LTER; Object based image analysis; Postclassification change detection; Urban area

Indexed keywords

BALTIMORE; HIGH-SPATIAL RESOLUTION IMAGE; LTER; OBJECT-BASED IMAGE ANALYSIS; POSTCLASSIFICATION CHANGE DETECTION; URBAN AREA;

AERIAL PHOTOGRAPHY; IMAGE ANALYSIS; IMAGE RESOLUTION; LANDFORMS; PIXELS; REMOTE SENSING; SIGNAL DETECTION;

OBJECT RECOGNITION;

EID: 67649793203     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2008.4779814     Document Type: Conference Paper

References (6)

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4. Zhou, W. and A. Troy., in press. An Object -oriented Approach for Analyzing and Characterizing Urban Landscape at the Parcel Level. International Journal of Remote Sensing.
5. Zhou, W., A. Troy, and J.M. Grove. 2008. Object -based land cover classification and change analysis in the Baltimore Metropolitan Area using multi-temporal high resolution remote sensing data. Sensors. 8: 1613-1636.
6. Blaschke, T., 2005, A framework for change detection based on image objects, In Göttinger Geographische Abhandlungen, S. Erasmi, B. Cyffka and M. Kappas (Eds), 113, pp. 1-9. Available online at http://www.definiens.com/ binary-secure/213-140.pdf?binary-id=213&l og-id=10463&session-id= 63e0a3f4d2bb30984e35e709eb54e658 (accessed 21 December 2007).