References

Alberti, M. (2005). The effects of urban patterns on ecosystem function. International Regional Science Review, 28, 168-192.

Alberti, M., Booth, D., Hill, K., Coburn, B., Avolio, C., Coe, S., & Spirandelli, D. (2007). The impact of urban patterns on aquatic ecosystems: An empirical analysis in Puget lowland sub-basins. Landscape and Urban Planning, 80, 345-361.

Alberti, M., Marzluff, J.M., Shulenberger, E., Bradley, G., Ryan, C., & Zumbrunnen, C. (2003). Integrating humans into ecology: Opportunities and challenges for studying urban ecosystems. Bioscience, 53, 1169-1179.

Alder, G. (1995). Tackling Poverty in Nairobis Informal Settlements - Developing an Institutional Strategy. Environment and Urbanization, 7, 85-107.

Arnold, C.L., & Gibbons, C.J. (1996). Impervious surface coverage - The emergence of a key environmental indicator. Journal of the American Planning Association, 62, 243-258.

Baatz, M., & Schaepe, A. (2000). Multiresolution Segmentation: an optimization approach for high quality multi-scale image segmentation, In Strobl, J., Blaschke, T. & Griesebner, G. (Eds.), Angewandte Geographische Informationsverarbeitung XII. Beiträge zum AGIT-Symposium 1999 (pp. 12-23). Heidelberg: Herbert Wichmann Verlag.

Balder, H., Ehlebracht, K., & Mahler, E. (1997). Straßenbäume: Planen, Pflanzen, Pflegen am Beispiel Berlin [Street trees: Planning, planting, cultivating in the case of Berlin]. Berlin-Hannover: Patzer Verlag.

Baraldi, A., & Parmiggiani, F. (1995). An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters. IEEE Transactions on Geoscience and Remote Sensing, 33, 293-304.

Bazi, Y., & Melgani, F. (2006). Toward an optimal SVM classification system for hyperspectral remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 44, 3374-3385.

Beisl, U. (2001). Correction of bidirectional effects in imaging spectrometer data. Remote Sensing Series, 37. Zurich: University of Zurich.

Beisl, U., & Woodhouse, N. Correction of atmospheric and bidirectional effects in multispectral ADS40 images for mapping purposes. Proceedings of the 20th ISPRS Congress, 12-23 July, 2004. Istanbul, Turkey:

Ben-Dor, E., Levin, N., & Saaroni, H. (2001). A spectral based recognition of the urban environment using the visible and near-infrared spectral region (0.4-1.1 µm). A case study over Tel-Aviv, Israel. International Journal of Remote Sensing, 22, 2193-2218.

Benediktsson, J.A., Palmason, J.A., & Sveinsson, J.R. (2005). Classification of hyperspectral data from urban areas based on extended morphological profiles. IEEE Transactions on Geoscience and Remote Sensing, 43, 480-491.

Benediktsson, J.A., Swain, P.H., & Ersoy, O.K. (1990). Neural Network Approaches Versus Statistical-Methods in Classification of Multisource Remote-Sensing Data. IEEE Transactions on Geoscience and Remote Sensing, 28, 540-552.

Blair, R.B. (1996). Land use and avian species diversity along an urban gradient. Ecological Applications, 6, 506-519.

Boardman, J.W. Post-ATREM polishing of AVIRIS apparent reflectance data using EFFORT: A lesson in accuracy versus precision Summaries of the 7th JPL Airborne Earth Science Workshop, Pasadena, USA:

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 Proceedings URBAN/URS 2007 Joint Event, 11-13 April, 2007. Paris, France: CD-ROM,

Booth, D.B., Karr, J.R., Schauman, S., Konrad, C.P., Morley, S.A., Larson, M.G., & Burger, S.J. (2004). Reviving urban streams: Land use, hydrology, biology, and human behavior. Journal of the American Water Resources Association, 40, 1351-1364.

Bottyan, Z., Kircsi, A., Szegedi, S., & Unger, J. (2005). The relationship between built-up areas and the spatial development of the mean maximum urban heat island in Debrecen, Hungary. International Journal of Climatology, 25, 405-418.

Brabec, E., Schulte, S., & Richards, P.L. (2002). Impervious surfaces and water quality: A review of current literature and its implications for watershed planning. Journal of Planning Literature, 16, 499-514.

Breiman, L. (2001). Random forests. Machine Learning, 45, 5-32.

Bruzzone, L., & Carlin, L. (2006). A multilevel context-based system for classification of very high spatial resolution images. IEEE Transactions on Geoscience and Remote Sensing, 44, 2587-2600.

Bruzzone, L., Chi, M.M., & Marconcini, M. (2006). A novel transductive SVM for semisupervised classification of remote-sensing images. IEEE Transactions on Geoscience and Remote Sensing, 44, 3363-3373.

Burges, C.J.C. (1998). A tutorial on Support Vector Machines for pattern recognition. Data Mining and Knowledge Discovery, 2, 121-167.

Cadenasso, M.L., Pickett, S.T.A., Burch, W.A., & Machlis, G.E. (2007). Human Ecosystems in the First Urban Century: Patch Dynamics Integrating Ecology and Social Science. New Haven: Yale University Press.

Cadenasso, M.L., Pickett, S.T.A., & Schwarz, K. (2007). Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Frontiers in Ecology and the Environment, 5, 80-88.

Carle, M.V., Halpin, P.N., & Stow, C.A. (2005). Patterns of watershed urbanization and impacts on water quality. Journal of the American Water Resources Association, 41, 693-708.

Carlson, T.N., & Arthur, S.T. (2000). The impact of land use - land cover changes due to urbanization on surface microclimate and hydrology: a satellite perspective. Global and Planetary Change, 25, 49-65.

Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N., & Smith, V.H. (1998). Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications, 8, 559-568.

Chen, C.C., & Lin, C.J. (2001). LIBSVM: a library for support vector machines [online]. Available from: [accessed September 2007].

Chopping, M.J. (2000). Testing a LiSK BRDF Model with in Situ Bidirectional Reflectance Factor Measurements over Semiarid Grasslands. Remote Sensing of Environment, 74, 287-312.

Chopping, M.J., Rango, A., & Ritchie, J.C. (2002). Improved semi-arid community type differentiation with the NOAA AVHRR via exploitation of the directional signal. IEEE Transactions on Geoscience and Remote Sensing, 40, 1132-1149.

Cocks, T., Jenssen, R., Stewart, I., Willson, I., & Shields, T. The HyMap(TM) airborne hyperspectral sensor: The system, calibration and preformance.. In Schaepman, M., Schlapfer, D. & Itten, K. (Eds.) (1998), Proceedings 1st EARSeL workshop on imaging spectroscopy, 6-8 October, 1998. Zürich, Switzerland: (pp. 37-42).

Collier, C.G. (2006). The impact of urban areas on weather. Quarterly Journal of the Royal Meteorological Society, 132, 1-25.

Congalton, R., & Green, K. (1999). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton: Lewis.

Damm, A., Hostert, P., & Schiefer, S. Investigating urban railway corridors with geometric high resolution satellite data. In Moeller, M. & Wentz, E. (Eds.) (2005), Proceedings 5th International Symposium Remote Sensing of Urban Areas (URS 2005), 14-16 March, 2005. Tempe, USA:

Deering, D.W. (1989). Field measurements of bidirectional reflectance, In Asrar, G. (Ed.) Theory and applications of optical remote sensing (pp. 14-65). New York: Wiley.

DeFries, R.S., Bounoua, L., & Collatz, G.J. (2002). Human modification of the landscape and surface climate in the next fifty years. Global Change Biology, 8, 438-458.

Dembrowski, H. (2004). The urban century. Editorial. Magazine for Development and Cooperation, 2004, 1.

Dennison, P.E. (2006). Fire detection in imaging spectrometer data using atmospheric carbon dioxide absorption. International Journal of Remote Sensing, 27, 3049-3055.

Diermayer, E., Hostert, P., Schiefer, S., & Damm, A. Comparing pixel- and object-based classification of imperviousness with HRSC-AX data. In Hostert, P., Schiefer, S. & Damm, A. (Eds.) (2006), Proceedings 1st Workshop of the EARSeL Special Intrest Group Urban Remote Sensing - "Challenges and Solutions", 2-3 March, 2006 . Berlin, Germany: CD-ROM,

Ehlers, M. (2007). New Developments and trends for Urban Remote Sensing, In Weng, Q. & Quattrochi, D. (Eds.), Urban Remote Sensing (pp. 357-376). Boca Raton: CRC Press.

Ehlers, M., Geehler, M., & Janowsky, R. (2006). Automated techniques for environmental monitoring and change analyses for ultra high resolution remote sensing data. Photogrammetric Engineering and Remote Sensing, 72, 835-844.

EPA [United States Environmental Protection Agency] (2001). Our built and natural environments, a technical review of the interaction between land use, transportation and environmental quality.Washington, DC: EPA.

Evans, C., Jones, R., Svalbe, I., & Berman, M. (2002). Segmenting multispectral landsat TM images into field units. IEEE Transactions on Geoscience and Remote Sensing, 40, 1054-1064.

Feingersh, T., Dorigo, W., Richter, R., & Ben-Dor, E. A new model-driven correction factor for BRDF effects in HRS data. In Zagajewski, B. & Sobczak, M. (Eds.) (2006), Proceedings 4th EARSeL workshop on Imaging Spectroscopy - "New Qualities in Environmental Studies", 27-29 April, 2005. Warsaw, Poland: (pp. 565-576).

Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Bonan, G., Carpenter, S.R., Chapin, F.S., Coe, M.T., Daily, G.C., Gibbs, H.K., Helkowski, J.H., Holloway, T., Howard, E.A., Kucharik, C.J., Monfreda, C., Patz, J.A., Prentice, I.C., Ramankutty, N., & Snyder, P.K. (2005). Global consequences of land use. Science, 309, 570-574.

Foody, G.M. (2004). Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy. Photogrammetric Engineering and Remote Sensing, 70, 627-633.

Foody, G.M., & Mathur, A. (2004). A relative evaluation of multiclass image classification by support vector machines. IEEE Transactions on Geoscience and Remote Sensing, 42, 1335-1343.

Foody, G.M., & Mathur, A. (2006). The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM. Remote Sensing of Environment, 103, 179-189.

Friedl, M.A., & Brodley, C.E. (1997). Decision tree classification of land cover from remotely sensed data. Remote Sensing of Environment, 61, 399-409.

Fu, K.S., Landgrebe, D.A., & Phillips, T.L. (1969). Information processing of remotely sensed agricultural data. Proceedings IEEE, 57, 639-653.

Gamba, P., & Dell'Acqua, F. (2007). Spectral resolution in the context of very high resolution urban remote sensing, In Weng, Q. & Quattrochi, D. (Eds.), Urban Remote Sensing (pp. 377-391). Boca Raton: CRC Press.

Gamba, P., & Houshmand, B. (2002). Joint analysis of SAR, LIDAR and aerial imagery for simultaneous extraction of land cover, DTM and 3D shape of buildings. International Journal of Remote Sensing, 23, 4439-4450.

Goel, N.S. (1988). Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sensing Reviews, 41, 553-564.

Goetz, A.F.H., Vane, G., Solomon, J.E., & Rock, B.N. (1985). Imaging Spectrometry for Earth Remote-Sensing. Science, 228, 1147-1153.

Goshtasby, A. (1988). Registration of Images with Geometric Distortions. IEEE Transactions on Geoscience and Remote Sensing, 26, 60-64.

Green, R.O., Eastwood, M.L., Sarture, C.M., Chrien, T.G., Aronsson, M., Chippendale, B.J., Faust, J.A., Pavri, B.E., Chovit, C.J., Solis, M.S., Olah, M.R., & Williams, O. (1998). Imaging spectroscopy and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 65, 227-248.

Gualtieri, J.A., & Cromp, R.F. Support vector machines for hyperspectral remote sensing classification. In Merisko, R.J. (Ed.) (1998), Proceedings SPIE-27th AIPRWorkshop Advances in Computer Assisted Recognition, vol. 3584, (pp. 221-232).

Guanter, L., Alonso, L., & Moreno, J. (2005). First results from the PROBA/CHRIS hyperspectral/multiangular satellite system over land and water targets. IEEE Geoscience and Remote Sensing Letters, 2, 250-254.

Harman, I.N., & Belcher, S.E. (2006). The surface energy balance and boundary layer over urban street canyons. Quarterly Journal of the Royal Meteorological Society, 132, 2749-2768.

Hatt, B.E., Fletcher, T.D., Walsh, C.J., & Taylor, S.L. (2004). The influence of urban density and drainage infrastructure on the concentrations and loads of pollutants in small streams. Environmental Management, 34, 112-124.

Heiden, U., Segl, K., Roessner, S., & Kaufmann, H. (2007). Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data. Remote Sensing of Environment, 111, 537-552.

Herold, M., Gardner, M.E., & Roberts, D.A. (2003). Spectral resolution requirements for mapping urban areas. IEEE Transactions on Geoscience and Remote Sensing, 41, 1907-1919.

Herold, M., Roberts, D.A., Gardner, M.E., & Dennison, P.E. (2004). Spectrometry for urban area remote sensing - Development and analysis of a spectral library from 350 to 2400 nm. Remote Sensing of Environment, 91, 304-319.

Herold, M., Schiefer, S., Hostert, P., & Roberts, D.A. (2006). Applying Imaging Spectrometry in Urban Areas, In Quattrochi, D.A. & Weng, Q.H. (Eds.), Urban Remote Sensing (pp. 137-161). Boca Raton: CRC Press Inc.

Hill, J., & Mehl, W. (2003). Geo- und radiometrische Aufbereitung multi- und hyperspektraler Daten zur Erzeugung langjähriger kalibrierter Zeitreihen.. Photogrammetrie, Fernerkundung, Geoinformation, 2003, 7-14.

Hirano, Y., Yasuoka, Y., & Ichinose, T. (2004). Urban climate simulation by incorporating satellite-derived vegetation cover distribution into a mesoscale meteorological model. Theoretical and Applied Climatology, 79, 175-184.

Hodgson, M.E., Jensen, J.R., Tullis, J.A., Riordan, K.D., & Archer, C.M. (2003). Synergistic use of lidar and color aerial photography for mapping urban parcel imperviousness. Photogrammetric Engineering and Remote Sensing, 69, 973-980.

Hsu, C.W., & Lin, C.J. (2002). A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks, 13, 415-425.

Hu, B.X., Lucht, W., Li, X.W., & Strahler, A.H. (1997). Validation of kernel-drives semiempirical models for the surface bidirectional reflectance distribution function of land surfaces. Remote Sensing of Environment, 62, 201-214.

Huang, C., Davis, L.S., & Townshend, J.R.G. (2002). An assessment of support vector machines for land cover classification. International Journal of Remote Sensing, 23, 725-749.

Hughes, G.F. (1968). On the mean accuracy of statistical pattern recognizers. IEEE Transactions on Information Theory, 14, 55-63.

Imhoff, M.L., Bounoua, L., Ricketts, T., Loucks, C., Harriss, R., & Lawrence, W.T. (2004). Global patterns in human consumption of net primary production. Nature, 429, 870-873.

Itten, K., Meyer, P., Kellenberger, T., Leu, R., Sandmeier, S., Bitter, P., & Seidel, K. (1992). Correction of the Impact of Topography and Atmosphere on Landsat-TM Forest Mapping of Alpine Regions. Remote Sensing Series, 18. Zurich: University of Zurich.

Jacquemoud, S., Bacour, C., Poilve, H., & Frangi, J.P. (2000). Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode. Remote Sensing of Environment, 74, 471-481.

Jacquemoud, S., Baret, F., Andrieu, B., Danson, F.M., & Jaggard, K. (1995). Extraction of Vegetation Biophysical Parameters by Inversion of the Prospect Plus Sail Models on Sugar-Beet Canopy Reflectance Data - Application to TM and AVIRIS Sensors. Remote Sensing of Environment, 52, 163-172.

Janz, A., & van der Linden, S. (2007). imageSVM - Support Vector Machine Classification for Remote Sensing Image Data [online]. Available from: [accessed September 2007].

Janz, A., van der Linden, S., Waske, B., & Hostert, P. imageSVM - a user-oriented tool for advanced classification of hyperspectral data using support vector machines. In Reusen, I. & Cools, J. (Eds.) (2007), Proceedings 5th EARSeL Workshop on Imaging Spectroscopy - "Imaging Spectroscopy: Innovation in environmental research", 23-25 April, 2007. Bruges, Belgium: CD-ROM,

Jensen, J.R., & Cowen, D.C. (1999). Remote sensing of urban suburban infrastructure and socio-economic attributes. Photogrammetric Engineering and Remote Sensing, 65, 611-622.

Johnson, L.F., Hlavka, C.A., & Peterson, D.L. (1994). Multivariate-Analysis of Aviris Data for Canopy Biochemical Estimation Along the Oregon Transect. Remote Sensing of Environment, 47, 216-230.

Kareiva, P., Watts, S., McDonald, R., & Boucher, T. (2007). Domesticated nature: Shaping landscapes and ecosystems for human welfare. Science, 316, 1866-1869.

Kaufmann, H., Segl, K., Chabrillat, S., Müller, A., Richter, R., Schreier, G., Hofer, S., Stuffler, T., Haydn, R., Bach, H., & Benz, U. ENMAP - an advanced hyperspectral mission. In Zagajewski, B. & Sobczak, M. (Eds.) (2006), Proceedings 4th EARSeL workshop on Imaging Spectroscopy - "New Qualities in Environmental Studies", 27-29 April, 2005. Warsaw, Poland: (pp. 55-59).

Kennedy, R.E., Cohen, W.B., & Takao, G. (1997). Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery. Remote Sensing of Environment, 62, 277-291.

Kimes, D.S. (1983). Dynamics of Directional Reflectance Factor Distributions for Vegetation Canopies. Applied Optics, 22, 1364-1372.

Kimes, D.S., Knyazikhin, Y., Privette, J.L., Abuelgasim, A.A., & Gao, F. (2000). Inversion methods for physically-based models. Remote Sensing Reviews, 18, 381-439.

Kittler, J. (1998). Combining classifiers: A theoretical framework. Pattern Analysis and Applications, 1, 18-27.

Koetz, B., Morsdorf, F., van der Linden, S., Curt, T., & Allgöwer, B. (2008). Multi-source land cover classification for forest fire management based on imaging spectrometry and LiDAR data. Forest Ecology and Management, in press.

Kötz, B., Schaepman, M., Morsdorf, F., Bowyer, P., Itten, K., & Allgower, B. (2004). Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties. Remote Sensing of Environment, 92, 332-344.

Kruse, F.A., Lefkoff, A.B., Boardman, J.W., Heidebrecht, K.B., Shapiro, A.T., Barloon, P.J., & Goetz, A.F.H. (1993). The Spectral Image-Processing System (Sips) - Interactive Visualization and Analysis of Imaging Spectrometer Data. Remote Sensing of Environment, 44, 145-163.

Kruse, F.A., Lefkoff, A.B., & Dietz, J.B. (1993). Expert System-Based Mineral Mapping in Northern Death-Valley, California Nevada, Using the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 44, 309-336.

Kuemmerle, T., Hostert, P., Radeloff, V., van der Linden, S., Perzanowski, K., & Kruhlov, I. (2008). Cross-border comparison of post-socialist farmland abandonment. Ecosystems, in press.

Kuo, B.-C., & Landgrebe, D.A. (2004). Nonparametric weighted feature extraction for classification. IEEE Transactions on Geoscience and Remote Sensing, 42, 1096-1105.

Lacherade, S., Miesch, C., Briottet, X., & Le Men, H. (2005). Spectral variability and bidirectional reflectance behaviour of urban materials at a 20 cm spatial resolution in the visible and near-infrared wavelengths. A case study over Toulouse (France). International Journal of Remote Sensing (Letter), 26, 3859-3866.

Langhans, M., van der Linden, S., Damm, A., & Hostert, P. The influence of bidirectional reflectance in airborne hyperspectral data on spectral angle mapping and linear spectral mixture analysis. In Reusen, I. & Cools, J. (Eds.) (2007), Proceedings 5th EARSeL Workshop on Imaging Spectroscopy - "Imaging Spectroscopy: Innovation in environmental research", April 23-25, 2007. Bruges, Belgium: CD-ROM,

Leroy, M., & Roujean, J.L. (1994). Sun and View Angle Corrections on Reflectances Derived from Noaa Avhrr Data. IEEE Transactions on Geoscience and Remote Sensing, 32, 684-697.

Li, X.W., & Strahler, A.H. (1986). Geometric-Optical Bidirectional Reflectance Modeling of a Conifer Forest Canopy. IEEE Transactions on Geoscience and Remote Sensing, 24, 906-919.

Liu, J.G., Dietz, T., Carpenter, S.R., Alberti, M., Folke, C., Moran, E., Pell, A.N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C.L., Schneider, S.H., & Taylor, W.W. (2007). Complexity of coupled human and natural systems. Science, 317, 1513-1516.

Lu, D.S., & Weng, Q.H. (2006). Use of impervious surface in urban land-use classification. Remote Sensing of Environment, 102, 146-160.

Lu, D.S., Weng, Q.H., & Li, G.Y. (2006). Residential population estimation using a remote sensing derived impervious surface approach. International Journal of Remote Sensing, 27, 3553-3570.

Lucht, W., Schaaf, C.B., & Strahler, A.H. (2000). An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Transactions on Geoscience and Remote Sensing, 38, 977-998.

Marcotullio, P.J., & Boyle, G. (2003). Defining an Ecosystem Approach to Urban Management and Policy Development. UNU/IAS Report. Tokyo: United Nations University Institute of Advanced Studies.

Martilli, A., Clappier, A., & Rotach, M.W. (2002). An urban surface exchange parameterisation for mesoscale models. Boundary-Layer Meteorology, 104, 261-304.

Mathieu, R., Freeman, C., & Aryal, J. (2007). Mapping private gardens in urban areas using object-oriented techniques and very high-resolution satellite imagery. Landscape and Urban Planning, 81, 179-192.

Matthew, M.W., Adler-Golden, S.M., Berk, A., Richtsmeier, S.C., Levine, R., & Bernstein, L.S. Status of atmospheric correction using a MODTRAN4-based algorithm Proceedings SPIE, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (pp. 199-207).

McGwire, K.C. (1996). Cross-validated assessment of geometric accuracy. Photogrammetric Engineering and Remote Sensing, 62, 1179-1187.

McMorrow, J.M., Cutler, M.E.J., Evans, M.G., & Al-Roichdi, A. (2004). Hyperspectral indices for characterizing upland peat composition. International Journal of Remote Sensing, 25, 313-325.

MEA [Millenium Ecosystem Assessment] (2005). Ecosystems and Human Well-being: Synthesis.Washington, DC: Island Press.

Meister, G., Rothkirch, A., Spitzer, H., & Bienlein, J. (2000). BRDF field studies for remote sensing of urban areas. Remote Sensing Reviews, 19, 37-57.

Melgani, F., & Bruzzone, L. (2004). Classification of hyperspectral remote sensing images with support vector machines. IEEE Transactions on Geoscience and Remote Sensing, 42, 1778-1790.

Mesev, V. (1998). The use of census data in urban image classification. Photogrammetric Engineering and Remote Sensing, 64, 431-438.

Meyerson, F.A.B., Merino, L., & Durand, J. (2007). Migration and environment in the context of globalization. Frontiers in Ecology and the Environment, 5, 182-190.

Miller, H.J., & Han, J. (Eds.) (2001). Geographic data mining and knowledge discovery. London:Taylor and Francis.

Miller, R.B., & Small, C. (2003). Cities from space: potential applications of remote sensing in urban environmental research and policy. Environmental Science & Policy, 6, 129-137.

Morawitz, D.F., Blewett, T.M., Cohen, A., & Alberti, M. (2006). Using NDVI to assess vegetative land cover change in central Puget Sound. Environmental Monitoring and Assessment, 114, 85-106.

Morse, C.C., Huryn, A.D., & Cronan, C. (2003). Impervious surface area as a predictor of the effects of urbanization on stream insect communities in Maine, USA. Environmental Monitoring and Assessment, 89, 95-127.

Müller, A., Richter, R., Habermeyer, M., Dech, S., Segl, K., & Kaufmann, H. (2005). Spectroradiometric requirements for the reflective module of the airborne spectrometer ARES. IEEE Geoscience and Remote Sensing Letters, 2, 329-332.

Nichol, J., & Wong, M.S. (2005). Modeling urban environmental quality in a tropical city. Landscape and Urban Planning, 73, 49-58.

Nicodemus, F.E., Richmond, J.C., Hsia, J.J., Ginsberg, I.W., & Limperis, T. (1977). Geometrical considerations and nomenclature for reflectance..Washington D.C.: US Department of Commerce, National Bureau of Standards.

Nieke, J., Itten, K., Debruyn, W., & APEX-Team The airborne imaging spectrometer APEX: from concept to realisation. In Zagajewski, B. & sobczak, M. (Eds.) (2006), Proceedings 4th EARSeL workshop on Imaging Spectroscopy - "New Qualities in Environmental Studies", 27-29 April, 2005. Warschau, Poland: (pp. 73-80).

North, P.R.J. (1996). Three-dimensional forest light interaction model using a Monte Carlo method. IEEE Transactions on Geoscience and Remote Sensing, 34, 946-956.

NRC [National Research Council, Space Studies Board] (2007). Earth Science and Applications from Space: Natoinal Imperatives for the Next Decade and Beyond (Prepublication copy).Washington DC: National Academy of Science.

Pal, M., & Mather, P.M. (2006). Some issues in the classification of DAIS hyperspectral data. International Journal of Remote Sensing, 27, 2895-2916.

Park, J. Globalization and the Urban Century: Refashioning a Post-Habitat II Reseach Agenda Proceedings Post-Habitat II Action on International Co-operation and Partnership in the Asia-Pacific Region, 20-21 February, 1997. Fukuoka, Japan: United Nations Centre for Regional Development,

Patz, J.A., Daszak, P., Tabor, G.M., Aguirre, A.A., Pearl, M., Epstein, J., Wolfe, N.D., Kilpatrick, A.M., Foufopoulos, J., Molyneux, D., & Bradley, D.J. (2004). Unhealthy landscapes: Policy recommendations on land use change and infectious disease emergence. Environmental Health Perspectives, 112, 1092-1098.

Pauleit, S., & Duhme, F. (2000). Assessing the environmental performance of land cover types for urban planning. Landscape and Urban Planning, 52, 1-20.

Pauleit, S., Ennos, R., & Golding, Y. (2005). Modeling the environmental impacts of urban land use and land cover change - a study in Merseyside, UK. Landscape and Urban Planning, 71, 295-310.

Pearlmutter, D., Berliner, P., & Shaviv, E. (2007). Integrated modeling of pedestrian energy exchange and thermal comfort in urban street canyons. Building and Environment, 42, 2396-2409.

Pinty, B., Widlowski, J.L., Gobron, N., Verstraete, M.M., & Diner, D.J. (2002). Uniqueness of multiangular measurements - Part I: An indicator of subpixel surface heterogeneity from MISR. IEEE Transactions on Geoscience and Remote Sensing, 40, 1560-1573.

Richards, J.A. (2005). Analysis of remotely sensed data: The formative decades and the future. IEEE Transactions on Geoscience and Remote Sensing, 43, 422-432.

Richter, R., Müller, A., Habermeyer, M., Dech, S., Segl, K., & Kaufmann, H. (2005). Spectral and radiometric requirements for the airborne thermal imaging spectrometer ARES. International Journal of Remote Sensing, 26, 3149-3162.

Richter, R., & Schläpfer, D. (2002). Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: atmospheric/topographic correction. International Journal of Remote Sensing, 23, 2631-2649.

Ridd, M.K. (1995). Exploring a V-I-S (Vegetation-Impervious Surface-Soil) Model for Urban Ecosystem Analysis through Remote-Sensing - Comparative Anatomy for Cities. International Journal of Remote Sensing, 16, 2165-2185.

Roberts, D.A., Smith, M.O., & Adams, J.B. (1993). Green Vegetation, Nonphotosynthetic Vegetation, and Soils in AVIRIS Data. Remote Sensing of Environment, 44, 255-269.

Roessner, S., Segl, K., Heiden, U., & Kaufmann, H. (2001). Automated differentiation of urban surfaces based on airborne hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 39, 1525-1532.

Ross, J.K. (1981). The radiation regime and architecture of plant stands. The Hague: Dr. W. Junk Publishers.

Royer, A., Vincent, P., & Bonn, F. (1985). Evaluation and Correction of Viewing Angle Effects on Satellite Measurements of Bidirectional Reflectance. Photogrammetric Engineering and Remote Sensing, 51, 1899-1914.

RSI [Research Systems, Inc.] (2004). ENVI - Environment for Visualizing Images, Version 4.0.

Rydberg, A., & Borgefors, G. (2001). Integrated method for boundary delineation of agricultural fields in multispectral satellite images. IEEE Transactions on Geoscience and Remote Sensing, 39, 2514-2520.

Sala, O.E., Chapin, F.S., Armesto, J.J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L.F., Jackson, R.B., Kinzig, A., Leemans, R., Lodge, D.M., Mooney, H.A., Oesterheld, M., Poff, N.L., Sykes, M.T., Walker, B.H., Walker, M., & Wall, D.H. (2000). Biodiversity - Global biodiversity scenarios for the year 2100. Science, 287, 1770-1774.

Sánchez-Rodríguez, R., Seto, K.C., Simon, D., Solecki, W.D., Kraas, F., & Laumann, G. (2005). Science Plan. Urbanization and Global Environmental Change. IHDP Report Series. Bonn: International Human Dimensions Programm on Global Environmental Change.

Sandmeier, S., Muller, C., Hosgood, B., & Andreoli, G. (1998). Physical mechanisms in hyperspectral BRDF data of grass and watercress. Remote Sensing of Environment, 66, 222-233.

Schiefer, S., Hostert, P., & Damm, A. An analysis of view-angle effects in hyperspectral data of urban areas. In Moeller, M. & Wentz, E. (Eds.) (2005), Proceedings 3rd Int. Symp. Remote Sensing and Data Fusion Over Urban Areas (URBAN 2005), 14-16 March, 2005. Tempe, USA:

Schiefer, S., Hostert, P., & Damm, A. (2006). Correcting brightness gradients in hyperspectral data from urban areas. Remote Sensing of Environment, 101, 25-37.

Schiefer, S., Hostert, P., Diermayer, E., & Damm, A. Compression and object-oriented processing of segmented hyperspectral images in ENVI. In Zagajewski, B. & Sobczak, M. (Eds.) (2006), Proceedings 4th EARSeL workshop on Imaging Spectroscopy - "New Qualities in Environmental Studies", 27-29 April, 2005. Warsaw, Poland: (pp. 609-616).

Schläpfer, D. (2005). PARametric GEocoding, User Guide, Version 2.2. ReSe Applications Schläpfer/Remote Sensing Laboratories of the University of Zurich.

Schläpfer, D., Nieke, J., Dell'Endice, F., Hüni, A., Biesemans, J., Meuleman, K., & Itten, K. Optimized workflow for APEX level 2/3 processing. In Reusen, I. & Cools, J. (Eds.) (2007), Proceedings 5th EARSeL Workshop on Imaging Spectroscopy - "Imaging Spectroscopy: Innovation in environmental research", 23-25 April, 2007. Bruges, Belgium:

Schläpfer, D., & Richter, R. (2002). Geo-atmospheric processing of airborne imaging spectrometry data. Part 1: parametric orthorectification. International Journal of Remote Sensing, 23, 2609-2630.

Schlerf, M., Atzberger, C., & Hill, J. (2005). Remote sensing of forest biophysical variables using HyMap imaging spectrometer data. Remote Sensing of Environment, 95, 177-194.

Schöpfer, E., & Moeller, M. (2006). Comparing Metropolitan Areas - A Transferable Object-Based Image Analysis Approach. Photogrammetrie-Fernerkundung-Geoinformation (PFG), 2006, 277-286.

Schueler, T. (1994). The importance of imperviousness. Watershed Protection Techniques, 1, 100-111.

Segl, K., Roessner, S., Heiden, U., & Kaufmann, H. (2003). 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, 58, 99-112.

SenStadt [Senatsverwaltung für Stadtentwicklung/Senate Department for Urban Develpment] (2007). Berlin Digital Environmental Atlas [online]. Available from: [accessed September 2007].

Seto, K.C., & Fragkias, M. (2005). Quantifying spatiotemporal patterns of urban land-use change in four cities of China with time series landscape metrics. Landscape Ecology, 20, 871-888.

Seto, K.C., & Liu, W.G. (2003). Comparing ARTMAP neural network with the maximum-likelihood classifier for detecting urban change. Photogrammetric Engineering and Remote Sensing, 69, 981-990.

Shackelford, A.K., & Davis, C.H. (2003). A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas. IEEE Transactions on Geoscience and Remote Sensing, 41, 2354-2363.

Small, C. (2001). Estimation of urban vegetation abundance by spectral mixture analysis. International Journal of Remote Sensing, 22, 1305-1334.

Small, C. (2003). High spatial resolution spectral mixture analysis of urban reflectance. Remote Sensing of Environment, 88, 170-186.

Small, C. (2004). The Landsat ETM plus spectral mixing space. Remote Sensing of Environment, 93, 1-17.

Small, C., & Lu, J.W.T. (2006). Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis. Remote Sensing of Environment, 100, 441-456.

Small, C., Pozzi, F., & Elvidge, C.D. (2005). Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sensing of Environment, 96, 277-291.

Smith, M.O., Ustin, S.L., Adams, J.B., & Gillespie, A.R. (1990). Vegetation in deserts: I. A regional measure of abundance from multispectral images. Remote Sensing of Environment, 31, 1-26.

Soegaard, H., & Moller-Jensen, L. (2003). Towards a spatial CO2 budget of a metropolitan region based on textural image classification and flux measurements. Remote Sensing of Environment, 87, 283-294.

Song, M., Civco, D.L., & Hurd, J.D. (2005). A competitive pixel-object approach for land cover classification. International Journal of Remote Sensing, 26, 4981-4997.

Stangl, M., Werninghaus, R., Schweizer, B., Fischer, C., Brandfass, M., Mittermayer, J., & Breit, H. (2006). TerraSAR-X technologies and first results. IEE Proceedings-Radar Sonar and Navigation, 153, 86-95.

Stefanov, W.L., Ramsey, M.S., & Christensen, P.R. (2001). Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers. Remote Sensing of Environment, 77, 173-185.

Strahler, A.H., Woodcock, C.E., & Smith, J.A. (1986). On the Nature of Models in Remote-Sensing. Remote Sensing of Environment, 20, 121-139.

Sukopp, H. (Ed.) (1990). Stadtoekologie. Das Beispiel Berlin [Urban Ecology. The Berlin Case]. Berlin:Dietrich Reimer Verlag.

Svensson, M.K., & Eliasson, I. (2002). Diurnal air temperatures in built-up areas in relation to urban planning. Landscape and Urban Planning, 61, 37-54.

Svirejeva-Hopkins, A., Schellnhuber, H.J., & Pomaz, V.L. (2004). Urbanised territories as a specific component of the Global Carbon Cycle. Ecological Modelling, 173, 295-312.

Thanapura, P., Helder, D.L., Burckhard, S., Warmath, E., O'Neill, M., & Galster, D. (2007). Mapping urban land cover using QuickBird NDVI and GIS spatial modeling for runoff coefficient determination. Photogrammetric Engineering and Remote Sensing, 73, 57-65.

Tong, S.T.Y., & Chen, W.L. (2002). Modeling the relationship between land use and surface water quality. Journal of Environmental Management, 66, 377-393.

Toutin, T. (2004). Review article: Geometric processing of remote sensing images: models, algorithms and methods. International Journal of Remote Sensing, 25, 1893-1924.

Tsai, M.Y., & Chen, K.S. (2004). Measurements and three-dimensional modeling of air pollutant dispersion in an Urban Street Canyon. Atmospheric Environment, 38, 5911-5924.

Udelhoven, T., Naumann, D., & Schmitt, J. (2000). Development of a hierarchical classification system with artificial neural networks and FT-IR spectra for the identification of bacteria. Applied Spectroscopy, 54, 1471-1479.

UN [United Nations] (2006). World Urbanization Prospects - The 2005 Revision. Executive Summary.New York: United Nations Population Division.

Ustin, S.L., Roberts, D.A., Gamon, J.A., Asner, G.P., & Green, R.O. (2004). Using imaging spectroscopy to study ecosystem processes and properties. Bioscience, 54, 523-534.

Vane, G., Green, R.O., Chrien, T.G., Enmark, H.T., Hansen, E.G., & Porter, W.M. (1993). The Airborne Visible Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 44, 127-143.

Vapnik, V.N. (1998). Statistical Learning Theory. New York: Wiley.

Verhoef, W. (1984). Light-Scattering by Leaf Layers with Application to Canopy Reflectance Modeling - the Sail Model. Remote Sensing of Environment, 16, 125-141.

Vitousek, P.M. (1997). Human domination of Earth's ecosystems. Science, 278, 21-21.

Wackernagel, M., & Rees, W.E. (1997). Perceptual and structural barriers to investing in natural capital: Economics from an ecological footprint perspective. Ecological Economics, 20, 3-24.

Walthall, C.L., Norman, J.M., Welles, J.M., Campbell, G., & Blad, B.L. (1985). Simple Equation to Approximate the Bidirectional Reflectance from Vegetative Canopies and Bare Soil Surfaces. Applied Optics, 24, 383-387.

Wang, C., Menenti, M., Stoll, M.P., Belluco, E., & Marani, M. (2007). Mapping mixed vegetation communities in salt marshes using airborne spectral data. Remote Sensing of Environment, 107, 559-570.

Wang, L., Sousa, W.P., & Gong, P. (2004). Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. International Journal of Remote Sensing, 25, 5655-5668.

Wanner, W., Li, X., & Strahler, A.H. (1995). On the Derivation of Kernels for Kernel-Driven Models of Bidirectional Reflectance. Journal of Geophysical Research-Atmospheres, 100, 21077-21089.

Ward, D., Phinn, S.R., & Murray, A.T. (2000). Monitoring growth in rapidly urbanizing areas using remotely sensed data. Professional Geographer, 52, 371-386.

Waske, B., & Benediktsson, J.A. (2007). Fusion of support vector machines for classification of multisensor data. IEEE Transactions on Geoscience and Remote Sensing, 45, 3858-3866.

Waske, B., & van der Linden, S. (2008). Classifying multilevel imagery from SAR and optical sensors by decision fusion. IEEE Transactions on Geoscience and Remote Sensing, 46, 1457-1466.

Weber, C., & Puissant, A. (2003). Urbanization pressure and modeling of urban growth: example of the Tunis Metropolitan Area. Remote Sensing of Environment, 86, 341-352.

Welch, R. (1982). Spatial resolution requirements for urban studies. International Journal of Remote Sensing, 3, 139-146.

White, H.P., Miller, J.R., & Chen, J.M. (2002). Four-Scale Linear Model for Anisotropic Reflectance (FLAIR) for plant canopies - Part II: Validation and inversion with CASI, POLDER, and PARABOLA data at BOREAS. IEEE Transactions on Geoscience and Remote Sensing, 40, 1038-1046.

Whitford, V., Ennos, A.R., & Handley, J.F. (2001). "City form and natural process" - indicators for the ecological performance of urban areas and their application to Merseyside, UK. Landscape and Urban Planning, 57, 91-103.

Wilson, E.H., Hurd, J.D., Civco, D.L., Prisloe, M.P., & Arnold, C. (2003). Development of a geospatial model to quantify, describe and map urban growth. Remote Sensing of Environment, 86, 275-285.

Woodcock, C.E., & Strahler, A.H. (1987). The Factor of Scale in Remote-Sensing. Remote Sensing of Environment, 21, 311-332.

Wu, C.S. (2004). Normalized spectral mixture analysis for monitoring urban composition using ETM plus imagery. Remote Sensing of Environment, 93, 480-492.

Wu, C.S., & Murray, A.T. (2003). Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 84, 493-505.

York, R., Rosa, E.A., & Dietz, T. (2003). Footprints on the earth: The environmental consequences of modernity. American Sociological Review, 68, 279-300.

Yuan, F., & Bauer, M.E. (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment, 106, 375-386.

Zhou, G.Q., Chen, W.R., Kelmelis, J.A., & Zhang, D.Y. (2005). A comprehensive study on urban true orthorectification. IEEE Transactions on Geoscience and Remote Sensing, 43, 2138-2147.


© Die inhaltliche Zusammenstellung und Aufmachung dieser Publikation sowie die elektronische Verarbeitung sind urheberrechtlich geschützt. Jede Verwertung, die nicht ausdrücklich vom Urheberrechtsgesetz zugelassen ist, bedarf der vorherigen Zustimmung. Das gilt insbesondere für die Vervielfältigung, die Bearbeitung und Einspeicherung und Verarbeitung in elektronische Systeme.
DiML DTD Version 4.0Zertifizierter Dokumentenserver
der Humboldt-Universität zu Berlin
HTML generated:
27.05.2008