Urban vegetation cover extraction from hyperspectral imagery and geographic information system spatial analysis techniques: Case of Athens, Greece

Journal of Applied Remote Sensing

Volumn 9, Issue 1, 2015, Pages

  Petropoulos, George P ^a,b   Kalivas, Dionissios P ^b   Georgopoulou, Iro A ^b   Srivastava, Prashant K ^c,d  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

^b AGRICULTURAL UNIVERSITY OF ATHENS   (Greece)

^c NASA GODDARD SPACE FLIGHT CENTER   (United States)

^d UNIVERSITY OF MARYLAND   (United States)

Author keywords

Athens; Earth observation; geographical information systems; Greece; Hyperion; spectral angle mapper; support vector machines

Indexed keywords

ERROR STATISTICS; GEOGRAPHIC INFORMATION SYSTEMS; INFORMATION SYSTEMS; INFORMATION USE; MAPPING; SPECTROSCOPY; SUPPORT VECTOR MACHINES; URBAN PLANNING; VEGETATION;

ATHENS; EARTH OBSERVATIONS; GREECE; HYPERION; SPECTRAL ANGLE MAPPERS;

CLASSIFICATION (OF INFORMATION);

EID: 84922572580     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.9.096088     Document Type: Article

References (54)

1. J. Otukei and T. Blaschke, "Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms," Int. J. Appl. Earth Obs. Geoinf. 12, S27-S31 (2010).
2. R. Banerjee and P. K. Srivastava, "Reconstruction of contested landscape: detecting land cover transformation hosting cultural heritage sites from Central India using remote sensing," Land Use Policy 34, 193-203 (2013).
3. K.-y.Wu et al., "Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: the case of fast-growing Hangzhou metropolitan area, China," Cities 31, 276-284 (2013).
4. P. K. Srivastava et al., Remote Sensing Applications in Environmental Research, Springer International Publishing, Switzerland (2014).
5. G. Martine and A. Marshall, "State of world population 2007: unleashing the potential of urban growth," 2007, http://www.unfpa.org/sites/default/files/pub-pdf/695-filename-sowp2007-eng.pdf (6 January 2015).
6. S. K. Singh et al., "Modeling groundwater quality over a humid subtropical region using numerical indices, earth observation datasets, and x-ray diffraction technique: a case study of Allahabad district, India," Environ. Geochem. Health 37, 157-180 (2014).
7. T. Van de Voorde, W. Jacquet, and F. Canters, "Mapping form and function in urban areas: an approach based on urban metrics and continuous impervious surface data," Landsc. Urban Plan. 102(3), 143-155 (2011).
8. G. Xian, M. Crane, and J. Su, "An analysis of urban development and its environmental impact on the Tampa Bay watershed," J. Environ. Manage. 85(4), 965-976 (2007).
9. J. Zhang et al., "Response of ecological storage and conservation to land use transformation: a case study of a mining town in China," Ecol. Model. 221(10), 1427-1439 (2010).
10. S. K. Singh et al., "Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine," Environ. Earth Sci. 71(5), 2245-2255 (2014).
11. S. Mukherjee et al., "Effect of canal on land use/land cover using remote sensing and GIS," J. Indian Soc. Remote Sens. 37(3), 527-537 (2009).
12. H. S. Moghadam and M. Helbich, "Spatiotemporal urbanization processes in the megacity of Mumbai, India: a Markov chains-cellular automata urban growth model," Appl. Geogr. 40, 140-149 (2013).
13. P. K. Srivastava, S. Mukherjee, and M. Gupta, "Impact of urbanization on land use/land cover change using remote sensing and GIS: a case study," Int. J. Ecol. Econ. Stat. 18(S10), 106-117 (2010).
14. J. K. Brueckner, "Urban sprawl: diagnosis and remedies," Int. Reg. Sci. Rev. 23(2), 160-171 (2000).
15. F. Munoz, "Lock living: urban sprawl in Mediterranean cities," Cities 20(6), 381-385 (2003).
16. K. P. Beckett, P. Freer-Smith, and G. Taylor, "Urban woodlands: their role in reducing the effects of particulate pollution," Environ. Pollut. 99(3), 347-360 (1998).
17. B. A. Currie and B. Bass, "Estimates of air pollution mitigation with green plants and green roofs using the UFORE model," Urban Ecosyst. 11(4), 409-422 (2008).
18. H. Akbari, M. Pomerantz, and H. Taha, "Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas," Sol. Energy 70(3), 295-310 (2001).
19. D. J. Nowak et al., "Modeling the effects of urban vegetation on air pollution," Air Pollution Modeling and Its Application XII, pp. 399-407, Springer, New York (1998).
20. H. Akbari, "Shade trees reduce building energy use and CO2 emissions from power plants," Environ. Pollut. 116, S119-S126 (2002).
21. P. K. Srivastava et al., "Modeling impact of land use change trajectories on groundwater quality using remote sensing and GIS," Environ. Eng. Manage. J. 12(12), 2343-2355 (2013).
22. P. K. Srivastava et al., "Selection of classification techniques for land use/land cover change investigation," Adv. Space Res. 50(9), 1250-1265 (2012).
23. J. M. Henke and G. P. Petropoulos, "A GIS-based exploration of the relationships between human health, social deprivation and ecosystem services: the case of Wales, UK," Appl. Geogr. 45, 77-88 (2013).
24. A. Elatawneh et al., "Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data," Int. J. Dig. Earth 7(3), 194-216 (2012).
25. G. P. Petropoulos, C. Kontoes, and I. Keramitsoglou, "Burnt area delineation from a unitemporal perspective based on Landsat TM imagery classification using support vector machines," Int. J. Appl. Earth Obs. Geoinf. 13(1), 70-80 (2011).
26. M. Gupta and P. K. Srivastava, "Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India," Water Int. 35(2), 233-245 (2010).
27. G. P. Petropoulos, K. Arvanitis, and N. Sigrimis, "Hyperion hyperspectral imagery analysis combined with machine learning classifiers for land use/cover mapping," Expert Syst. Appl. 39(3), 3800-3809 (2012).
28. G. P. Petropoulos, C. Kalaitzidis, and K. P. Vadrevu, "Support vector machines and objectbased classification for obtaining land-use/cover cartography from Hyperion hyperspectral imagery," Comput. Geosci. 41, 99-107 (2012).
29. T. R. Tooke et al., "Extracting urban vegetation characteristics using spectral mixture analysis and decision tree classifications," Remote Sens. Environ. 113(2), 398-407 (2009).
30. D. Lu and Q. Weng, "Extraction of urban impervious surfaces from an IKONOS image," Int. J. Remote Sens. 30(5), 1297-1311 (2009).
31. T. M. Lillesand, R. W. Kiefer, and J. W. Chipman, Remote Sensing and Image Interpretation, John Wiley & Sons Ltd., New York (2004).
32. R. Banerjee and P. K. Srivastava, "Remote sensing based identification of painted rock shelter sites: appraisal using advanced wide field sensor, neural network and field observations," Remote Sensing Applications in Environmental Research, pp. 195-212, Springer International Publishing, Switzerland (2014).
33. G. M. Foody and A. Mathur, "Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification," Remote Sens. Environ. 93(1), 107-117 (2004).
34. G. P. Petropoulos et al., "A comparison of spectral angle mapper and artificial neural network classifiers combined with Landsat TM imagery analysis for obtaining burnt area mapping," Sensors 10(3), 1967-1985 (2010).
35. S. Kolios and C. D. Stylios, "Identification of land cover/land use changes in the greater area of the Preveza peninsula in Greece using Landsat satellite data," Appl. Geogr. 40, 150-160 (2013).
36. D. G. Goodenough et al., "Processing Hyperion and ALI for forest classification," IEEE Trans. Geosci. Remote Sens. 41(6), 1321-1331 (2003).
37. M. Chi and L. Bruzzone, "Semisupervised classification of hyperspectral images by SVMs optimized in the primal," IEEE Trans. Geosci. Remote Sens. 45(6), 1870-1880 (2007).
38. G. P. Petropoulos, C. C. Kontoes, and I. Keramitsoglou, "Land cover mapping with emphasis to burnt area delineation using co-orbital ALI and Landsat TM imagery," Int. J. Appl. Earth Obs. Geoinf. 18, 344-355 (2012).
39. G. P. Petropoulos, K. P. Vadrevu, and C. Kalaitzidis, "Spectral angle mapper and objectbased classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region," Geocarto Int. 28(2), 114-129 (2013).
40. T. Ayala-Silva and C. A. Beyl, "Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency," Adv. Space Res. 35(2), 305-317 (2005).
41. D. P. Roy and L. Boschetti, "Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned-area products," IEEE Trans. Geosci. Remote Sens. 47(4), 1032-1044 (2009).
42. J. B. Lee, A. S. Woodyatt, and M. Berman, "Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform," IEEE Trans. Geosci. Remote Sens. 28(3), 295-304 (1990).
43. E. U. s. Guide, ENVI On-Line Software User's Manual," ITT Visual Information Solutions (2008).
44. F. Kruse et al., "The spectral image processing system (SIPS)-interactive visualization and analysis of imaging spectrometer data," Remote Sens. Environ. 44(2), 145-163 (1993).
45. S. Haykin, Neural Networks: a Comprehensive Foundation, 1994, McMillan, New Jersey (2010).
46. V. N. Vapnik and V. Vapnik, Statistical Learning Theory, Wiley, New York (1998).
47. R. G. Congalton, "Accuracy assessment and validation of remotely sensed and other spatial information," Int. J. Wildland Fire 10(4), 321-328 (2001).
48. C. Kontoes et al., "A comparative analysis of a fixed thresholding vs. a classification tree approach for operational burn scar detection and mapping," Int. J. Appl. Earth Obs. Geoinf. 11(5), 299-316 (2009).
49. M. Herold, N. C. Goldstein, and K. C. Clarke, "The spatiotemporal form of urban growth: measurement, analysis and modeling," Remote Sens. Environ. 86(3), 286-302 (2003).
50. M. Shafri, H. Zulhaidi, and F. Ramle, "A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island," Inf. Technol. J. 8(1), 64-70 (2009).
51. H. Z. Shafri, A. Suhaili, and S. Mansor, "The performance of maximum likelihood, spectral angle mapper, neural network and decision tree classifiers in hyperspectral image analysis," J. Comput. Sci. 3(6), 419 (2007).
52. M. Pal and P. Mather, "Support vector machines for classification in remote sensing," Int. J. Remote Sens. 26(5), 1007-1011 (2005).
53. B. Koetz et al., "Multi-source land cover classification for forest fire management based on imaging spectrometry and LiDAR data," For. Ecol. Manage. 256(3), 263-271 (2008).
54. O. De Carvalho and P. R. Meneses, "Spectral correlation mapper (SCM): an improvement on the spectral angle mapper (SAM)," 2000, ftp://eco.arc.nasa.gov/pub/stevek/Spectral% 20Correlation/Osmar-1-carvalho-web.pdf (6 January 2015).