Urban structure type characterization using hyperspectral remote sensing and height information

Landscape and Urban Planning

Volumn 105, Issue 4, 2012, Pages 361-375

  Heiden, Uta ^a   Heldens, Wieke ^a   Roessner, Sigrid ^b   Segl, Karl ^b   Esch, Thomas ^a   Mueller, Andreas ^a  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

^b GFZ GERMAN RESEARCH CENTRE FOR GEOSCIENCES   (Germany)

Author keywords

HyMap; Hyperspectral; Indicator; Spectral reflectance; Surface material; Urban structure type

Indexed keywords

INDICATORS (INSTRUMENTS); MAPPING; SPECTROSCOPY; URBAN PLANNING;

HYMAP; HYPERSPECTRAL; SPECTRAL REFLECTANCES; SURFACE MATERIALS; URBAN STRUCTURE TYPES;

REMOTE SENSING;

AUTOMATION; CONSTRUCTION MATERIAL; HEIGHT; IMAGE ANALYSIS; LAND COVER; QUANTITATIVE ANALYSIS; REMOTE SENSING; SPATIAL ANALYSIS; SPECTRAL REFLECTANCE; URBAN MORPHOLOGY; URBAN PLANNING;

BAVARIA; GERMANY; MUNICH;

EID: 84858336613     PISSN: 01692046     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.landurbplan.2012.01.001     Document Type: Article

References (62)

1. Banzhaf E., Höfer R. Monitoring urban structure types as spatial indicators with CIR aerial photographs for a more effective urban environmental management. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 2008, 1(2):129-138.
2. Bassani C., Cavalli R.M., Cavalcante F., Cuomo V., Palombo A., Pascucci S., et al. Deterioration status of asbestos-cement roofing sheets assessed by analyzing hyperspectral data. Remote Sensing of Environment 2007, 109(3):361-378.
3. Ben-Dor E. Imaging spectrometry for urban applications. Imaging spectrometry. Basic principles and prospective applications 2001, Kluwer Academic Publishers, Dordrecht. F.D. Van der Meer, S.M. De Jong (Eds.).
4. Bochow M., Segl K., Kaufmann H. Automating the build-up process of feature-based fuzzy logic models for the identification of urban biotopes from hyperspectral remote sensing data 2007, Urban Remote Sensing Joint Event, Paris, France.
5. Bochow M., Küster [Peisker] T., Roessner S., Segl K., Kaufmann H. Towards an automated update of urban biotope maps using remote sensing data: What is possible?. Urban biodiversity and design 2010, 255-272. Wiley-Blackwell. N. Müller, P. Werner, J.G. Kelcey (Eds.).
6. Cavalli R.M., Fusilli L., Pascucci S., Pignatti S., Santini F. Hyperspectral sensor data capability for retrieving complex urban land cover in comparison with multispectral data: Venice City case study (Italy). Sensors 2008, 2008(8):3299-3320.
7. Clark R.N. Spectroscopy of rocks and minerals and principles of spectroscopy. Remote sensing for the earth sciences: Manual of remote sensing 1999, Vol. 3:3-52. John Wiley and Sons Inc. 3rd ed.
8. Cloutis E.A. Hyperspectral geological remote sensing: Evaluation of analytical techniques. International Journal of Remote Sensing 1996, 17(12):2215-2242.
9. Cocks T., Jenssen R., Stewart A., Wilson I., Shields T. The HyMapTM airborne hyperspectral sensor: The system, calibration and performance. Proceedings of the 1th EARSeL workshop in Zürich 1998, 37-42.
10. Duhme, F., & Pauleit, S. (1994). Strukturtypenkartierung als Instrument der räumlich integrativen Analyse und Bewertung der Umweltbedingungen in München (Mapping of urban structure types as a tool for spatially integrative analysis and evaluation of the environmental conditions in Munich). Report. Technische Universität München (in German).
11. Fina S. Planungsrelevanz: Potenziale und Herausforderungen neuer Geodatenstrukturen. Proceedings of 16th international conference on urban planning and regional development in the information society 2011, (in German).
12. Fischer H.S. Flächencharakterisierung der im Rahmen der Stadtbiotopkartierung erfassten Struktureinheiten 2002, Ifanos Landschaftsökologie, im Auftrag der Landeshauptstadt München, (in German).
13. Franke J., Roberts Dar A., Halligan K., Menz G. Hierarchical multiple endmember spectral mixture analysis (MESMA) of hyperspectral imagery for urban environments. Remote Sensing of Environment 2009, 113:1678-1690.
14. Goetz A.F.H., Vane G., Solomon J.E., Barrett N.R. Imaging spectrometry for earth remote sensing. Science 1985, 228(4704):1147-1153.
15. Habermeyer M., Marschalk U., Roth A. Digital elevation model database W42-A scalable system for spatial data. The international archives of the photogrammetry, remote sensing and spatial information sciences, ISPRS conference 2008 2008, International Society for Photogrammetry and Remote Sensing, Peking, China.
16. Heber, B., & Lehmann, I. (1993). Stadtstrukturelle Orientierungswerte für die Bodenversiegelung in Wohngebieten (Urban structural benchmarks for soil sealing in residential areas). Technical report 05-1993. Dresden, Germany: Institut für ökologische Raumentwicklung e.V (in German).
17. Heiden U., Roessner S., Segl K., Kaufmann H. Spectral analysis of urban surfaces using field measurements and hyperspectral HyMap data. Proceedings of IEEE/ISPRS joint workshop on remote sensing and data fusion over urban areas 2001, 173-177.
18. Heiden U., Segl K., Roessner S., Kaufmann H. Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data. Remote Sensing of Environment 2007, 111:537-552.
19. Heldens, W. (2010). Use of airborne hyperspectral data and height information to support urban micro climate characterisation. PhD thesis. Germany: Julius-Maximilians-Universitität Würzburg. (accessed on 19.08.11). http://opus.bibliothek.uni-wuerzburg.de/volltexte/2010/4893/.
20. Heldens W., Esch T., Heiden U., Müller A., Dech S. Exploring the demands on hyperspectral data products for urban planning: A case study in the Munich region. Proceedings of the 6th EARSeL SIG IS workshop 2009, E. Ben-Dor (Ed.).
21. Heldens W., Heiden U., Bachmann M., Esch T., Müller A., Dech S. Scaling issues in validation of abundance maps derived from HyMap data of an urban area. Proceedings of the 6th EARSeL SIG IS workshop 2009, E. Ben-Dor (Ed.).
22. Henry J.A., Dicks S.E. Association of urban temperature with land use and surface materials. Landscape and Urban Planning 1987, 14:21-29.
23. Hepner G.F., Chen J. Investigation of imaging spectroscopy for discriminating urban land covers and surface materials. AVIRIS earth science and applications workshop 2001.
24. Herold M., Gardner M.E., Roberts D.A. Spectral resolution requirements for mapping urban areas. IEEE Transactions on Geoscience and Remote Sensing 2003, 41(9):1907-1919.
25. Herold M., Liu X.H., Clarke K.C. Spatial metrics and image texture for mapping urban land use. Photogrammetric Engineering and Remote Sensing 2003, 69(9):991-1001.
26. Herold M., Roberts D.A., Gardner M.E., Dennison P.E. Spectrometry for urban area remote sensing-development and analysis of a spectral library from 350 to 2400nm. Remote Sensing of Environment 2004, 91:304-319.
27. Höfer R., Banzhaf E., Ebert A. Delineating urban structure types (UST) in a heterogeneous urban agglomeration with VHR and TerraSAR-X data. IEEE Joint Urban Remote Sensing Event JURSE 2009, 1-7.
28. Hoyano A., Iino A., Ono M., Tanighchi S. Analysis of the influence of urban form and materials on sensible heat flux-a case study of Japan's largest housing development 'Tama New Town'. Atmospheric Environment 1999, 33:3931-3939.
29. Kaufmann, H., Segl, K., Itzerott, S., Bach, H., Wagner, A., Hill, J., Oppermann, B., Heldens, W., Stein, E., Müller, A., van der Linden, S., Leitao, P.J., Rabe, A., & Hostert, P. (2008). Hyperspectral algorithms: Report in the frame of EnMAP preparation activities. Scientific technical report, 10/08, doi:10.2312/GFZ.b103-10089.
30. Kurz F., Müller R., Stephani M., Reinartz P., Schröder M. Calibration of a wide-angle digital camera system for near real time scenarios. Proc. ISPRS Hannover workshop 2007-high resolution earth imaging for geospatial information 2007.
31. Lacherade S., Miesch C., Briottet X., Le Men H. Spectral variability and bidirectional reflectance behaviour of urban materials at a 20cm spatial resolution in the visible and near-infrared wavelength. A case study over Toulouse (France). International Journal of Remote Sensing 2005, 26(17):3859-3866.
32. Lakes T., Kim H. The urban environmental indicator "Biotope Area Ratio": An enhanced approach to assess and manage the urban ecosystem services using high resolution remote-sensing. Ecological Indicators 2012, 13:93-103.
33. Lee S., Lathrop R.G. Sub-pixel estimation of urban land cover components with linear mixture model analysis and Landsat Thematic Mapper imagery. International Journal of Remote Sensing 2005, 26(22):4885-4905.
34. Li J., Song C., Cao L., Zhu F., Meng X., Wu J. Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China. Remote Sensing of Environment 2011, 115:3249-3263.
35. Müller R., Holzwarth S., Habermeyer M., Müller A. Ortho image production within an automatic processing chain for the hyperspectral airborne scanner ARES. Proceedings of the EARSeL workshop 3D remote sensing 2005.
36. Pauleit, S. (1998). Das Umweltwirkgefüge städtischer Siedlungsstrukturen: Darstellung des städtischen Ökosystems durch eine Strukturtypenkartierung zur Bestimmung von Umweltqualitätszielen für die Stadtplanung (The environmental effect arrangement of urban settlement structures: Presentation of the urban ecosystem by mapping structure types for determination of environmental quality targets for urban planning). Report. Technische Universität München (in German).
37. Pauleit S., Duhme F. Assessing the environmental performance of land cover types for urban planning. Landscape and Urban Planning 2000, 52:1-20.
38. Powell R.L., Matzke N., de Souza, Clark C., Numata M., Hess I., et al. Sources of error in accuracy assessment of thematic land-cover maps in the Brazilian Amazon. Remote Sensing of Environment 2004, 90:221-234.
39. Powell R.L., Roberts D.A., Dennison P.E., Hess L.L. Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil. Remote Sensing of Environment 2007, 106:253-267.
40. Pu R., Gong P., Michishita R., Sasagawa T. Spectral mixture analysis for mapping abundance of urban surface components from the Terra/ASTER data. Remote Sensing of Environment 2008, 112:939-954.
41. Richter R. ATCOR 4 user guide 2009, DLR - German Aerospace Centre, Remote Sensing Data Centre, Oberpfaffenhofen, Germany.
42. Roessner S., Segl K., Heiden U. Comparison of automated methods for identification of urban surfaces using airborne hyperspectral data of reflective and thermal wavelength ranges. Second EARSeL workshop on imaging spectroscopy 2000.
43. Roessner S., Segl K., Heiden U., Kaufmann H. Automated differentiation of urban surfaces based on airborne hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing 2001, 39:1525-1532.
44. Roessner S., Segl K., Bochow M., Heiden U., Heldens W., Kaufmann H. Potential of hyperspectral remote sensing for analyzing the urban environment. Urban remote sensing: Monitoring, synthesis and modeling in the urban environment 2011, 49-62. John Wiley and Sons Ltd., Oxford. Xiaojun Yang (Ed.).
45. Schaepman M.E., Ustin S.L., Plaza A.J. Earth system science related imaging spectroscopy-An assessment. Session on the state of science of environmental applications of imaging spectroscopy held in honor of Alexander FH Goetz, Vol. 113 2009, S123-S137.
46. Scholten F., Gwinner K., Tauch R., Boulgakova O. HRSC-AX-High-resolution orthoimages and digital surface models for urban regions. Proceedings of the 2nd GRSS/ISPRS joint workshop on remote sensing and data fusion over urban areas (URBAN 2003) 2003, 225-229.
47. Segl K., Roessner S., Heiden U., Kaufmann H. Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data. ISPRS Journal of Photogrammetry and Remote Sensing 2003, 58(1-2):99-112.
48. Segl K., Bochow M., Roessner S., Kaufmann H., Heiden U. Feature-based identification of urban endmember spectra using hyperspectral HyMap data. eProceedings of the 1st workshop of the EARSeL special interest group urban remote sensing 2006, P. Hostert, S. Schiefer, A. Damm (Eds.).
49. Siedentop S., Fina S. Monitoring urban sprawl in Germany. Towards a GIS-based measurement and assessment approach. Journal of Land Use Science 2010, 5(2):73-104.
50. Silvan-Cardenas J., Wang L. Sub-pixel confusion-uncertainty matrix for assessing soft classifications. Remote Sensing of Environment 2008, 112(3):1081-1095.
51. Small C. High spatial resolution spectral mixture analysis of urban reflectance. Remote Sensing of Environment 2003, 88:170-186.
52. Song C. Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporated endmember variability. Remote Sensing of Environment 2005, 106:253-267.
53. Sukopp H., Blume H.P., Eikmann T., Fritsche U., Gebhard U., Hampicke U., et al. Die ökologische Gliederung der Stadt. Stadtökologie 1998, Gustav Fischer Verlag, pp. 316-372 (in German).
54. Tang, Y. (2007). An integrated GIS-spatial analysis of Atlanta's urban structure and urban space. PhD thesis. University of Georgia, USA. (accessed on 23.08.11). http://ugakr.libs.uga.edu/bitstream/handle/10724/10039/tangyanbing%20200 708%20phd.pdf.
55. Taubenböck H., Esch T., Wurm M., Roth A., Dech S. Object-based feature extraction using high spatial resolution satellite data of urban areas. Journal of Spatial Science 2010, 55(1):117-132.
56. Van der Linden S., Hostert P. The influence of urban structures on impervious surface maps from airborne hyperspectral data. Remote Sensing of Environment 2009, 11(113):2298-2305. 41.
57. Van der Linden S., Janz A., Waske B., Eiden M., Hostert P. Classifying segmented hyperspectral data from a heterogeneous urban environment using support vector machines. Journal of Applied Remote Sensing 2007, 1.
58. Weng Q., Hu X., Lu D. Extracting impervious surfaces from medium spatial resolution multispectral and hyperspectral imagery: A comparison. International Journal of Remote Sensing 2008, 29(11):3209-3232.
59. Wickop, E., Böhm, P., Eitner, K., & Breuste, J. (1998). Qualitätszielkonzept für Stadtstrukturtypen am Beispiel der Stadt Leipzig (Benchmark concept for urban structure types-A case study of the city of Leipzig). UFZ technical report 14.
60. Wu C., Murray A.T. Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment 2003, 84(4):493-505.
61. Wurm M., Taubenböck H., Roth A., Dech S. Urban structuring using multisensoral remote sensing data-By the example of German cities-Cologne and Dresden. Urban Remote Sensing Joint Event 2009.
62. Yoshida H., Omae M. An approach for analysis of urban morphology: Methods to derive morphological properties of city blocks by using an urban landscape model and their interpretations. Computers Environment and Urban Systems 2005, 29:223-247.