Classification of the wildland-urban interface: A comparison of pixel- and object-based classifications using high-resolution aerial photography

Computers, Environment and Urban Systems

Volumn 32, Issue 4, 2008, Pages 317-326

  Cleve, Casey ^a   Kelly, Maggi ^a   Kearns, Faith R ^a   Moritz, Max ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Classification; Image analysis; Object based methods; Remote sensing; Wildland urban interface

Indexed keywords

AERIAL PHOTOGRAPHY; COPYING; FORESTRY; IMAGE PROCESSING; IMAGING SYSTEMS; IMAGING TECHNIQUES; LAND USE; LANDFORMS; LAWS AND LEGISLATION; MAPS; OPTICAL DATA PROCESSING; OPTICAL PROJECTORS; PHOTOGRAPHY; PIXELS; REMOTE SENSING; SENSORS; SPACE OPTICS;

CLASSIFICATION; CLASSIFICATION APPROACH; CLASSIFICATION METHODS; DECISION-MAKERS; EFFICIENT METHODS; FIRE MANAGEMENT; GREATER ACCURACY; HIGH RESOLUTIONS; HIGH SPATIAL RESOLUTION IMAGERY; HIGH-SPATIAL RESOLUTION; IMAGE ANALYSIS; LAND USE AND LAND-COVER; OBJECT-BASED; OBJECT-BASED METHODS; REMOTE SENSING TECHNIQUES; RISK MITIGATION; STRUCTURAL DAMAGES; URBAN DEVELOPMENTS; WILDLAND AREAS; WILDLAND-URBAN INTERFACE;

CLASSIFICATION (OF INFORMATION);

AERIAL PHOTOGRAPHY; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE PROCESSING; PIXEL; REMOTE SENSING; SPATIAL RESOLUTION; URBAN DEVELOPMENT;

AIR CRAFT; CITIES; DATA PROCESSING; DECISION MAKING; DEVELOPMENT; FIRES; IMAGE ANALYSIS; INFORMATION RETRIEVAL; LAND USE; LEGISLATION; MAPPING; OPTICS; PHOTOGRAPHY; REMOTE SENSING; RESOLUTION; SENSORS;

EID: 49449103785     PISSN: 01989715     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compenvurbsys.2007.10.001     Document Type: Article

References (40)

1. Alberti M., Weeks R., et al. Urban land cover change analysis in Central Puget Sound. Photogrammetric Engineering and Remote Sensing 70 9 (2004) 1043-1052
2. Baatz, M., Heynen, M., et al. (2000). eCognition User Guide. Munich, Definiens.
3. Barlow J., Franklin S., et al. High spatial resolution satellite imagery, DEM derivatives, and image segmentation for the detection of mass wasting processes. Photogrammetric Engineering and Remote Sensing 72 6 (2006) 687-692
4. + and DEM data in the northern Cascade Mountains, British Columbia. Canadian Journal of Remote Sensing 29 4 (2003) 510-517
5. Bauer T., and Steinnocher K. Per-parcel land use classification in urban areas using a rule-based technique. GeoBIT 6 (2001) 12-17
6. Benediktsson J.A., Pesaresi M., et al. Classification and feature extraction for remote sensing images from urban areas based on morphological transformations. IEEE Transactions on Geoscience and Remote Sensing 41 9 (2003) 1940-1949
7. Chubey M.S., Franklin S.E., et al. Object-based analysis of Ikonos-2 imagery for extraction of forest inventory parameters. Photogrammetric Engineering and Remote Sensing 72 4 (2006) 383-394
8. Cihlar J. Land cover mapping of large areas from satellites: status and research priorities. International Journal of Remote Sensing 21 6-7 (2000) 1093-1114
9. Cohen J.D. Preventing disaster: home ignitability in the wildland-urban interface. Journal of Forestry 98 3 (2000) 15-21
10. Congalton R.G., and Green K. Assessing the accuracy of remotely sensed data: principles and practices (1999), Lewis Publishers
11. Definiens (2005). eCognition Professional, Munich.
12. ESRI (2004). ArcGIS software. Environmental Systems Research Institute. Redlands, CA.
13. Ehlers M., Gähler M., et al. Automated analysis of ultra high resolution remote sensing data for biotope type mapping: new possibilities and challenges. ISPRS Journal of Photogrammetry and Remote Sensing 57 (2003) 315-326
14. Foody G.M. Status of land cover classification accuracy assessment. Remote Sensing of Environment 80 1 (2002) 185-201
15. Frontiera, P. L., Kearns, F. R. et al. (submitted for publication). A new approach to assessing parcel-level vulnerability to wildfire in the wildland-urban interface. Landscape and Urban Planning.
16. Harvey K.R., and Hill G.J.E. Vegetation mapping of a tropical freshwater swamp in the Northern Territory, Australia: A comparison of aerial photography, Landsat TM and SPOT satellite imagery. International Journal of Remote Sensing 22 15 (2001) 2911-2925
17. Hay G.J., Blaschke T., et al. A comparison of three image-object methods for the multiscale analysis of landscape structure. Journal of Photogrammetry and Remote Sensing 57 (2003) 327-345
18. Hay, G. J., Castilla, G. (2006). Object-based image analysis: Strengths, weaknesses, opportunities and threats (SWOT). OBIA, 2006: The international archives of the photogrammetry, remote sensing and spatial information sciences, Salzburg, Austria.
19. Hay G.J., Marceau D.J., et al. A multiscale framework for landscape analysis: object-specific analysis and upscaling. Landscape Ecology 16 (2001) 471-490
20. Herold M., Gardner M.E., et al. Spectral resolution requirements for mapping urban areas. IEEE Transactions on Geoscience and Remote Sensing 41 9 (2003) 1907-1919
21. Herold M., Liu X.H., et al. Spatial metrics and image texture for mapping urban land-use. Photogrammetric Engineering and Remote Sensing 69 9 (2003) 991-1001
22. Hollister J.W., Gonzalez M.L., et al. Assessing the accuracy of national land cover dataset area estimates at multiple spatial extents. Photogrammetric Engineering and Remote Sensing 70 4 (2004) 405-414
23. Jensen J.R. Introductory digital image processing: a remote sensing perspective (1996), Prentice Hall, Upper Saddle River, NJ
24. Jensen J.R., and Cowen D.C. Remote sensing of urban suburban infrastructure and socio-economic attributes. Photogrammetric Engineering and Remote Sensing 65 5 (1999) 611-622
25. Kalliola R., and Syrjänen K. To what extent are vegetation types visible in satellite imagery?. Annales Botanici Fennici 28 (1991) 45-57
26. Kelly M., Shaari D., et al. A comparison of standard and hybrid classifier methods for mapping hardwood mortality in areas affected by "sudden oak death". Photogrammetric Engineering and Remote Sensing 70 11 (2004) 1229-1239
27. Kettig R.L., and Landgrebe D.A. Classification of multispectral image data by extraction and classification of homogeneous objects. IEEE Transactions on Geoscience and Remote Sensing 14 1 (1976) 19-26
28. Laliberte A.S., Rango A., et al. Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico. Remote Sensing of Environment 93 1-2 (2004) 198-210
29. Leica (2004). Erdas Imagine 8.7 software.
30. Liu D., Kelly M., et al. A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery. Remote Sensing of Environment 101 2 (2006) 167-180
31. Murname R.J. Catastrophe risk models for wildfires in the wildland-urban interface: What insurers need. Natural Hazards Review 7 4 (2006) 150-156
32. Pyne S., Andrews P., et al. Introduction to wildland fire (1996), John Wiley and Sons, New York
33. Radeloff V.C., Hammer R.B., et al. The wildland-urban interface in the United States. Ecological Applications 15 3 (2005) 799-805
34. Thomas N., Hendrix C., et al. A comparison of urban mapping methods using high-resolution digital imagery. Photogrammetric Engineering and Remote Sensing 69 9 (2003) 963-972
35. Vogelmann J., Sohl T., et al. Regional characterization of land cover using multiple sources of data. Photogrammetric Engineering and Remote Sensing 64 1 (1998) 45-57
36. Vogelmann J.E., Howard S.M., et al. Completion of the 1990s National Land Cover Data Set for the conterminous United States from Landsat Thematic Mapper Data and ancillary datasources. Photogrammetric Engineering and Remote Sensing 67 (2001) 650-652
37. Walsh S.J., Crawford T.W., et al. A multiscale analysis of LULC and NDVI variation in Nang Rong district, northeast Thailand. Agriculture, Ecosystems and Environment 85 (2001) 47-64
38. Yuan, F., Bauer, M. E. (2006). Mapping impervious surface area using high resolution imagery: A comparison of object-based and per pixel classification. In American society for photogrammetry and remote sensing annual conference proceedings 2006, Reno, Nevada.
39. Yu Q., Gong P., et al. Object-based detailed vegetation classification with airborne high resolution remote sensing imagery. Photogrammetric Engineering and Remote Sensing 72 7 (2006) 799-811
40. Zhang Q., Pavlic G., et al. A semi-automatic segmentation procedure for feature extraction in remotely sensed imagery. Computers and Geosciences 31 3 (2005) 289-296