Urban built-up areas in transitional economies of Southeast Asia: Spatial extent and dynamics

Remote Sensing

Volumn 8, Issue 10, 2016, Pages

  Ouyang, Zutao ^a   Fan, Peilei ^a   Chen, Jiquan ^a  

^a MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Built up; DMSP OLS; Landsat; MODIS; SE Asia; Urban

Indexed keywords

ECONOMICS; RADIOMETERS; REMOTE SENSING; URBAN GROWTH;

BUILT-UP; DMSP/OLS; LANDSAT; MODIS; SE ASIA; URBAN;

TIME SERIES ANALYSIS;

EID: 85013633158     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs8100819     Document Type: Article

References (76)

1. Shepherd, J.M. A review of current investigations of urban-induced rainfall and recommendations for the future. Earth Interact. 2005, 9, 1-27
2. Imhoff, M.L.; Bounoua, L.; DeFries, R.; Lawrence,W.T.; Stutzer, D.; Tucker, C.J.; Ricketts, T. The consequences of urban land transformation on net primary productivity in the United States. Remote Sens. Environ. 2004, 89, 434-443
3. Gibson, J.; Li, C.; Boe-Gibson, G. Economic growth and expansion of China's urban land area: Evidence from administrative data and night lights, 1993-2012. Sustainability 2014, 6, 7850-7865
4. Churkina, G.; Brown, D.G.; Keoleian, G. Carbon stored in human settlements: The conterminous United States. Glob. Chang. Biol. 2010, 16, 135-143
5. Brabec, E.; Schulte, S.; Richards, P.L. Impervious surfaces and water Quality: A review of current literature and its implications for watershed planning. J. Plan. Lit. 2002, 16, 499-514
6. Uneralp, B.; Seto, K.C. Futures of global urban expansion: Uncertainties and implications for biodiversity conservation. Environ. Res. Lett. 2013, 8, 014025
7. Zhou, L.; Dickinson, R.E.; Tian, Y.; Fang, J.; Li, Q.; Kaufmann, R.K.; Tucker, C.J.; Myneni, R.B. Evidence for a significant urbanization effect on climate in China. Proc. Natl. Acad. Sci. USA 2004, 101, 9540-9544
8. Giannico, V.; Lafortezza, R.; John, R.; Sanesi, G.; Pesola, L.; Chen, J. Estimating Stand Volume and above-Ground Biomass of Urban Forests Using LiDAR. Remote Sens. 2016, 8, 339
9. 2.5 in Nanjing? Ecol. Process. 2016, 5
10. Ellis, E.C.; Ramankutty, N. Putting people in the map: Anthropogenic biomes of the world. Front. Ecol. Environ. 2008, 6, 439-447
11. Schneider, A.; Mertes, C.M.; Tatem, A.J.; Tan, B.; Sulla-Menashe, D.; Graves, S.J.; Patel, N.N.; Horton, J.A.; Gaughan, A.E.; Rollo, J.T.; et al. A new urban landscape in East-Southeast Asia, 2000-2010. Environ. Res. Lett. 2015, 10, 034002
12. Saksena, S.; Fox, J.; Spencer, J.; Castrence, M.; DiGregorio, M.; Epprecht, M.; Sultana, N.; Finucane, M.; Nguyen, L.; Vien, T.D. Classifying and mapping the urban transition in Vietnam. Appl. Geogr. 2014, 50, 80-89
13. Schneider, A.; Friedl, M.A.; Potere, D. A new map of global urban extent from MODIS satellite data. Environ. Res. Lett. 2009, 4, 044003
14. Kuang, W.; Liu, J.; Zhang, Z.; Lu, D.; Xiang, B. Spatiotemporal dynamics of impervious surface areas across China during the early 21st century. Chin. Sci. Bull. 2013, 58, 1691-1701
15. Jing,W.; Yang, Y.; Yue, X.; Zhao, X. Mapping urban areas with integration of DMSP/OLS nighttime light and MODIS data using machine learning techniques. Remote Sens. 2015, 7, 12419-12439
16. Potere, D.; Schneider, A.; Angel, S.; Civco, D. Mapping urban areas on a global scale: Which of the eight maps now available is more accurate? Int. J. Remote Sens. 2009, 30, 6531-6558
17. Friedl, M.A.; Sulla-Menashe, D.; Tan, B.; Schneider, A.; Ramankutty, N.; Sibley, A.; Huang, X. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sens. Environ. 2010, 114, 168-182
18. Bontemps, S.; Defourny, P.; Radoux, J.; Bogaert, E.; Lamarche, C.; Achard, F.; Mayaux, P.; Boettcher, M.; Brockmann, C.; Kirches, G.; et al. Consistent global land cover maps for climate modelling communities: Current achievements of the ESA' land cover CCI. In Proceedings of the ESA Living Planet Symposium 2013, Edinburgh, UK, 9-13 September 2013
19. Sutton, P.C.; Elvidge, C.D.; Tuttle, B.T.; Ziskin, D.; Baugh, K.; Ghosh, T. A 2010 mapping of the constructed surface area density for SE Asia-Preliminary results. Proc. Asia Pac. Adv. Netw. 2010, 30, 181-189
20. Mertes, C.M.; Schneider, A.; Sulla-Menashe, D.; Tatem, A.J.; Tan, B. Detecting change in urban areas at continental scales with MODIS data. Remote Sens. Environ. 2015, 158, 331-347
21. Liu, Z.; He, C.; Zhou, Y.;Wu, J. How much of the world's land has been urbanized, really? A hierarchical framework for avoiding confusion. Landsc. Ecol. 2014, 29, 763-771
22. Kuang, W.; Chen, L.; Liu, J.; Xiang, W.; Chi, W.; Lu, D.; Yang, T.; Pan, T.; Liu, A. Remote sensing-based artificial surface cover classification in Asia and spatial pattern analysis. Sci. China Earth Sci. 2016, 59, 1720-1737
23. Lu, D.; Li, G.; Moran, E. Current situation and needs of change detection techniques. Int. J. Image Data Fusion 2014, 5, 13-38
24. Zhang, C.; Chen, Y.; Lu, D. Detecting fractional land-cover change in arid and semiarid urban landscapes with multitemporal Landsat Thematic mapper imagery. GISci. Remote Sens. 2015, 52, 700-722
25. Imhoff, M.L.; Lawrence, W.T.; Stutzer, D.C.; Elvidge, C.D. A technique for using composite DMSP/OLS "City Lights" satellite data to map urban area. Remote Sens. Environ. 1997, 61, 361-370
26. Small, C.; Pozzi, F.; Elvidge, C.D. Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sens. Environ. 2005, 96, 277-291
27. Huang, X.; Schneider, A.; Friedl, M.A. Mapping sub-pixel urban expansion in China using MODIS and DMSP/OLS nighttime lights. Remote Sens. Environ. 2016, 175, 92-108
28. Zhang, Q.; Seto, K.C. Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data. Remote Sens. Environ. 2011, 115, 2320-2329
29. Huang, Q.; Yang, X.; Gao, B.; Yang, Y.; Zhao, Y. Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review. Remote Sens. 2014, 6, 6844-6866
30. Zhou, Y.; Smith, S.J.; Elvidge, C.D.; Zhao, K.; Thomson, A.; Imhoff, M. A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sens. Environ. 2014, 147, 173-185
31. Liu, Z.; He, C.; Zhang, Q.; Huang, Q.; Yang, Y. Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landsc. Urban Plan. 2012, 106, 62-72
32. Gibson, J.; Boe-Gibson, G.; Stichbury, G. Urban land expansion in India 1992-2012. Food Policy 2015, 56, 100-113
33. Chen, J.; Chen, J.; Liao, A.; Cao, X.; Chen, L.; Chen, X.; He, C.; Han, G.; Peng, S.; Lu, M.; et al. Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS J. Photogramm. Remote Sens. 2014, 103, 7-27
34. Kuang,W.; Chi,W.; Lu, D.; Dou, Y. A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces. Landsc. Urban Plan. 2014, 132, 121-135
35. Gong, P.; Wang, J.; Yu, L.; Zhao, Y.; Zhao, Y.; Liang, L.; Niu, Z.; Huang, X.; Fu, H.; Liu, S.; et al. Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. Int. J. Remote Sens. 2013, 34, 2607-2654
36. Chen, C.F. Urban growth mapping from Landsat data using linear mixture model in Ho Chi Minh City, Vietnam. J. Appl. Remote Sens. 2012, 6, 063543
37. Pham, H.M.; Yamaguchi, Y.; Bui, T.Q. A case study on the relation between city planning and urban growth using remote sensing and spatial metrics. Landsc. Urban Plan. 2011, 100, 223-230
38. Pham, H.M.; Yamaguchi, Y. Urban growth and change analysis using remote sensing and spatial metrics from 1975 to 2003 for Hanoi, Vietnam. Int. J. Remote Sens. 2011, 32, 1901-1915
39. International Monetary Fund. Transition Economies: An IMF Perspective on Progress and Prospects. Available online: http://www.imf.org/external/np/exr/ib/2000/110300.htm#I (accessed on 7 October 2016)
40. Than, M.; Thein, M. Transitional economy of myanmar-present status, developmental divide and future prospects. ASEAN Econ. Bull. 2007, 24, 98-118
41. Griffin, K. Economic Reform in Vietnam; Keith Griffin, S.T., Ed.; Martin's Press Inc.: New York, NY, USA, 1998
42. Elvidge, C.D.; Ziskin, D.; Baugh, K.E.; Tuttle, B.T.; Ghosh, T.; Pack, D.W.; Erwin, E.H.; Zhizhin, M. A fifteen year record of global natural gas flaring derived from satellite data. Energies 2009, 2, 595-622
43. Bernstein, L.S.; Adler-Golden, S.M.; Sundberg, R.L.; Levine, R.Y.; Perkins, T.C.; Berk, A.; Ratkowski, A.J.; Felde, G.; Hoke, M.L. Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi-and hyperspectral imagery. Proc. SPIE 2005, 5806, 668-678
44. GlobeLand30. Available online: http://glc30.tianditu.com/(accessed on 1 October 2016)
45. MODIS NDVI. Available online: https://modis.gsfc.nasa.gov/data/dataprod/mod13.php (accessed on 1 October 2016)
46. National Centers for Environmental Information. Available online: http://maps.ngdc.noaa.gov (accessed on 1 October 2016)
47. USGS Eearth Explorer. Available online: http://earthexplorer.usgs.gov/(accessed on 1 October 2016)
48. Land Scan. Available online: http://web.ornl.gov/sci/landscan/(accessed on 1 October 2016)
49. Google Earth. Available online: https://www.google.com/earth/(accessed on 1 October 2016)
50. Global Rural-Urban Mapping Project. Available online: http://sedac.ciesin.columbia.edu/data/set/grumpv1-settlement-points (accessed on 1 October 2016)
51. McIntyre, N.E.; Knowles-Yánez, K.; Hope, D. Urban Ecology as an Interdisciplinary Field: Differences in the use of "Urban" between the Social and Natural Sciences. In Urban Ecology; Springer: Boston, MA, USA, 2008; pp. 49-65
52. Wu, J. Urban ecology and sustainability: The state-of-the-science and future directions. Landsc. Urban Plan. 2014, 125, 209-221
53. Zhang, Q.; Schaaf, C.; Seto, K.C. The Vegetation Adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosity. Remote Sens. Environ. 2013, 129, 32-41
54. Lu, D.; Weng, Q. A survey of image classification methods and techniques for improving classification performance. Int. J. Remote Sens. 2007, 28, 823-870
55. Coppin, P.; Jonckheere, I.; Nackaerts, K.; Muys, B.; Lambin, E. Review Article Digital change detection methods in ecosystem monitoring: A review. Int. J. Remote Sens. 2004, 25, 1565-1596
56. Huang, Z.; Jia, X. Integrating remotely sensed data, GIS and expert knowledge to update object-based land use/land cover information. Int. J. Remote Sens. 2012, 33, 905-921
57. Hussain, M.; Chen, D.; Cheng, A.; Wei, H.; Stanley, D. Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS J. Photogramm. Remote Sens. 2013, 80, 91-106
58. Sesnie, S.E.; Gessler, P.E.; Finegan, B.; Thessler, S. Integrating Landsat TM and SRTM-DEM derived variables with decision trees for habitat classification and change detection in complex neotropical environments. Remote Sens. Environ. 2008, 112, 2145-2159
59. Yuan, H.; Van Der Wiele, C.F.; Khorram, S. An automated artificial neural network system for land use/land cover classification from Landsat TM imagery. Remote Sens. 2009, 1, 243-265
60. Blaschke, T.; Strobl, J. What's wrong with pixels? Some recent developments interfacing remote sensing and GIS. Interfacing Remote Sens. GIS 2001, 6, 12-17
61. Myint, S.W.; Gober, P.; Brazel, A.; Grossman-Clarke, S.;Weng, Q. Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sens. Environ. 2011, 115, 1145-1161
62. Xu, H. Extraction of urban built-up land features from Landsat imagery using a thematic-oriented index combination technique. Photogramm. Eng. Remote Sens. 2007, 73, 1381-1391
63. Benz, U.C.; Hofmann, P.; Willhauck, G.; Lingenfelder, I.; Heynen, M. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS J. Photogramm. Remote Sens. 2004, 58, 239-258
64. Ouyang, Z.T.; Zhang, M.Q.; Xie, X.; Shen, Q.; Guo, H.Q.; Zhao, B. A comparison of pixel-based and object-oriented approaches to VHR imagery for mapping saltmarsh plants. Ecol. Inform. 2011, 6, 136-146
65. Chen, Z.; Zhao, Z.; Gong, P.; Zeng, B. A new process for the segmentation of high resolution remote sensing imagery. Int. J. Remote Sens. 2006, 27, 4991-5001
66. Elvidge, C.D.; Baugh, K.E.; Kihn, E.A.; Kroehl, H.W.; Davis, E.R.; Davis, C.W. Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. Int. J. Remote Sens. 2010, 18, 1373-1379
67. Lu, D.; Tian, H.; Zhou, G.; Ge, H. Regional mapping of human settlements in southeastern China with multisensor remotely sensed data. Remote Sens. Environ. 2008, 112, 3668-3679
68. Cohen, W.B.; Maiersperger, T.K.; Yang, Z.; Gower, S.T.; Turner, D.P.; Ritts, W.D.; Berterretche, M.; Running, S.W. Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: A quality assessment of 2000/2001 provisional MODIS products. Remote Sens. Environ. 2003, 88, 233-255
69. Fan, F.; Deng, Y. Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters. Int. J. Appl. Earth Obs. Geoinf. 2014, 33, 290-301
70. Musakwa,W.; van Niekerk, A. Earth observation for sustainable urban planning in developing vountries: Needs, trends, and future directions. J. Plan. Lit. 2015, 30, 149-160
71. Amanollahi, J.; Tzanis, C.; Ramli, M.F.; Abdullah, A.M. Urban heat evolution in a tropical area utilizing Landsat imagery. Atmos. Res. 2016, 167, 175-182
72. Nowak, D.J.; Crane, D.E.; Stevens, J.C. Air pollution removal by urban trees and shrubs in the United States. Urban For. Urban Green. 2006, 4, 115-123
73. Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-resolution global maps of 21st-century forest cover change. Science 2013, 342, 850-853
74. Fan, P.; Chen, J.; John, R. Urbanization and environmental change during the economic transition on the Mongolian Plateau: Hohhot and Ulaanbaatar. Environ. Res. 2016, 144, 96-112
75. Elvidge, C.D.; Baugh, K.E.; Zhizhin, M.; Hsu, F.C. Why VIIRS data are superior to DMSP for mapping nighttime lights. Proc. Asia Pac. Adv. Netw. 2013, 35, 62-69
76. The World Bank. Available online: http://www.worldbank.org (accessed on 1 October 2016)