IEEE Geoscience and Remote Sensing Magazine - March 2015 - 33

[84] G. C. Iannelli, F. Dell'Acqua, and P. Gamba, "Comparing different textural approaches to extract human settlement from
CBERS-2B data," in Proc. Simpósio Brasileiro de Sensoriamento Remoto, Foz do Iguaçu, PR, Brasil, Apr. 2013.
[85] H. Xu, "Extraction of urban built-up land features from landsat imagery using a thematic oriented index combination technique," Photogramm. Eng. Remote Sens., vol. 73, no. 12, pp. 1381-
1391, Dec. 2007.
[86] M. E. Bauer, N. J. Heinert, J. Doyle, and F. Yuan, "Impervious
surface mapping and change monitoring using landsat remote
sensing," in Proc. ASPRS Annu. Conf., Denver, CO, May 2004.
[87] Q. Weng, "Remote sensing of impervious surfaces in the urban
areas: Requirements, methods, and trends," Remote Sens. Environ., vol. 117, pp. 34-39, Feb. 2012.
[88] M. C. Hung and M. K. Ridd, "A subpixel classifier for urban landcover mapping based on a maximum-likelihood approach and
expert system rules," Photogramm. Eng. Remote Sens., vol. 68, no.
11, pp. 1173-1180, Nov. 2002.
[89] S. Phinn, M. Stanford, P. Scarth, A. T. Murray, and P. T. Shyy,
"Monitoring the composition of urban environments based on
the vegetation-impervious surface-soil model by subpixel analysis techniques," Int. J. Remote Sens., vol. 23, no. 20, pp. 4131-
4153, Jan. 2002.
[90] M. Wieland, M. Pittore, S. Parolai, J. Zschau, B. Moldobekov,
and U. Begaliev, "Estimating building inventory for rapid seismic vulnerability assessment: Towards an integrated approach
based on multi-source imaging," Soil Dyn. Earthq. Eng., vol. 36,
pp. 70-83, May 2012.
[91] M. Herold, X. H. Liu, and K. C. Clarke, "Spatial metrics and image texture for mapping urban land use," Photogramm. Eng. Remote Sens., vol. 69, no. 9, pp. 991-1001, Sept. 2003.
[92] M. Dodge, R. Kitchin, C. Perkins, J. R. Jensen, and D. C. Cowen,
The Map Reader. Chichester, U.K.: Wiley, Apr. 2011.
[93] Q. Weng and D. Lu, "Landscape as a continuum: An examination of the urban landscape structures and dynamics of Indianapolis city, 1991-2000, by using satellite images," Int. J. Remote
Sens., vol. 30, no. 10, pp. 2547-2577, May 2009.
[94] A. Formisano, R. Landolfo, F. M. Mazzolani, and G. Florio, "A
quick methodology for seismic vulnerability assessment of
historical masonry aggregates," in Proc. COST C26 Final Conf.,
Naples, Italy, Sept. 2010.
[95] R. Vicente, S. Parodi, S. Lagomarsino, H. Varun, and J. A. R.
Mendes da Silva, "Seismic vulnerability assessment, damage
scenarios and loss estimation. Case study of the old city centre
of Coimbra, Portugal," in Proc. 14th World Conf. Earthquake Engineering, Beijing, China, Oct. 2008.
[96] P. M. Dare, "Shadow analysis in high-resolution satellite imagery
of urban areas," Photogramm. Eng. Remote Sens., vol. 71, no. 2, pp.
169-177, Feb. 2005.
[97] P. F. Hsieh, L. C. Lee, and N. Y. Chen, "Effect of spatial resolution on classification errors of pure and mixed pixels in remote
sensing," IEEE Trans. Geosci. Remote Sensing, vol. 39, no. 12, pp.
2657-2663, Dec. 2001.
[98] X. Tong, S. Liu, and Q. Weng, "Geometric processing of Quickbird stereo imagery for urban land use mapping-A case study in
Shanghai, China," IEEE J. Select. Topics Appl. Earth Observ. Remote
Sensing, vol. 2, no. 2, pp. 61-66, June 2009.
[99] H. Mayer, "Automatic object extraction from aerial imagery-A
survey focusing on building," Comput. Vis. Image Understanding,
vol. 74, no. 2, pp. 138-139, May 1999.
[100] R. Peteri and T. Ranchin, Remote Sensing of Impervious Surfaces.
New York: Taylor & Francis, 2007.
[101] J. Amini, M. R. Saradjian, J. A. R. Blais, C. Lucas, and A. Azizi,
"Automatic road-side extraction from large scale image maps,"
Int. J. Appl. Earth Observ. Geoinform., vol. 4, no. 2, pp. 95-107,
Nov. 2002.

march 2015

ieee Geoscience and remote sensing magazine

[102] J. B. Mena, "State of the art on automatic road extraction for GIS
update: A novel classification," Pattern Recognit. Lett., vol. 24, no.
16, pp. 3037-3058, Dec. 2003.
[103] P. Gong and P. J. Howarth, "The use of structure information
for improving landcover classification accuracies at the rural-
urban fringe," Photogramm. Eng. Remote Sens., vol. 56, no. 1, pp.
67-73, Jan. 1999.
[104] H. Long and Z. Zhao, "Urban road extraction from high-resolution optical satellite images," Int. J. Remote Sens., vol. 26, no. 22,
pp. 4907-4921, Nov. 2005.
[105] W. Shi and C. Zhu, "The line segment match method for extracting road network from high-resolution satellite images,"
IEEE Trans. Geosci. Remote Sensing, vol. 40, no. 2, pp. 511-514,
Feb. 2002.
[106] J. Hu, A. Razdan, J. C. Femiani, M. Cui, and P. Wonka, "Road
network extraction and intersection detection from aerial images by tracking road footprints," IEEE Trans. Geosci. Remote Sensing,
vol. 45, no. 12, pp. 4144-4157, Dec. 2007.
[107] (2014, July). PAGER Inventory Database V2. [Online]. Available: http://pubs.usgs.gov/of/2008/1160/downloads/PAGER_database/
[108] (2014, Aug.). Global Earthquake Model, GEM Basic Building
Taxonomy V 1.0. [Online]. Available: http://www.globalquakemodel.org
[109] TOLOMEO Project. (2014, July). Tools for open multi risk assessment using earth observation data. [Online]. Available:
http://tolomeofp7.unipv.it/SoftwareTools/BREC
[110] B. Yu, H. Liu, J. Wu, Y. Hu, and L. Zhang, "Automated derivation
of urban building density information using airborne LiDAR
data and object-based method," Landscape Urban Planning, vol.
98, nos. 3-4, pp. 210-219, Dec. 2010.
[111] G. Miliaresis and N. Kokkas, "Segmentation and object-based
classification for the extraction of the building class from LiDAR DEMs," Comput. Geosci., vol. 33, no. 8, pp. 1076-1087,
Aug. 2007.
[112] F. Samadzadegan, M. Hahn, and B. Bigdeli, "Automatic road
extraction from LIDAR data based on classifier fusion in urban
area," in Proc. IEEE Joint Urban Remote Sensing Event, Shanghai,
China, May 2009, pp. 1-6.
[113] J. Jung, C. Armenakis, and G. Sohn, "Data-driven alignment
of 3 D building models and digital aerial images," in Proc. ISPRS
Technical Commission VII Symp., Vienna, Austria, July 2010.
[114] H. Miller and H. Jiawei, Geographic Data Mining and Knowledge
Discovery. Boca Raton, FL: CRC Press (Taylor & Francis Group),
2009.
[115] D. Alexander, Confronting Catastrophe New Perspective on Natural
Disasters. New York: Oxford Univ. Press, 2000.
[116] FEMA 329. (2014, June). Demolition debris and waste source
volume calculations. [Online]. Available: http://www.fema.gov/
pdf/government/grant/pa/fema_329_debris_estimating.pdf
[117] SENSUM Project. (2014, Aug.). SENSUM Source code repository, GitHub repository for the SENSUM tools source code. [Online]. Available: https://github.com/SENSUM-project/sensum_rs
[118] SENSUM Project. (2014, Aug.). SENSUM QGIS plugin repository. [Online]. Available: https://github.com/SENSUM-project/
sensum_rs_qgis
[119] SENSUM Project. (2014, Aug.). Source code documentation.
[Online]. Available: http://lhotse21.gfz-potsdam.de/sensum/
sensum_rs_doc/index.html
[120] RASOR Project. (2014, Aug.). Rapid analysis and spatialisation
of risk. [Online]. Available: http://www.rasor-project.eu
[121] SENSUM Project. (2014, Aug.). Approved QGIS plugin SENSUM earth observation tools 1.0. [Online]. Available: http://plugins.qgis.org/plugins/sensum_eo_tools/
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http://pubs.usgs.gov/of/2008/1160/downloads/PAGER_da http://www.globalquake http://www.model.org http://tolomeofp7.unipv.it/SoftwareTools/BREC http://www.fema.gov/ https://www.github.com/SENSUM-project/sensum_rs https://www.github.com/SENSUM-project/ http://lhotse21.gfz-potsdam.de/sensum/ http://www.rasor-project.eu http://pl http://ugins.qgis.org/plugins/sensum_eo_tools/
Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - March 2015
