Abstract
This study presents an evaluation of urban micro-climate about the exsistence level urban vegetation, in association with the urban temperature (surface temperature) and urban built-up area of Bandung City. The changes in urban vegetation cover, urban temperature, and urban built-up area observed using Landsat 5 TM and Landsat 7 ETM + bands were evaluated on the basis of the WDRVI (Wide Dynamic Range Vegetation Indices), NDBI (Normalized Difference Built-up Index), and SAVI (Soil-Adjusted Vegetation Index). It was found that, due to the uncontrolled urban growth and the removal of urban vegetation cover and urban green space, there was a significant increase in urban temperature, in NDBI, but a decrease in WDRVI. The maximum urban temperatures, NDBI, and the minimum values of WDRVI indices were established in 2009. Therefore the results indicate a significant effect of higher density of impervious surfaces coverage (urban built-up area) contributing significantly to the increase of urban temperature. Again the results also confirm that urban vegetation landscape coverage in the surrounding of industrial area reduced the urban temperature. Based on the results, we recommend the city government to provide more urban green space by cooperating with private land owner, in order to decrease urban temperature and create a healthier living environment for urban inhabitants.
Abbreviations
- TM:
-
Thematic mapper
- ETM+:
-
Enhanced thematic mapper plus
- WDRVI:
-
Wide dynamic range vegetation index
- SAVI:
-
Soil-adjusted vegetation index
- NDBI:
-
Normalized difference built-up Index
References
Barsi JA, Schott JR, Palluconi FD, Helder DL, Hook SJ, Markham BL, Chander G, O’Donnell EM (2003) Landsat TM and ETM + thermal band calibration. Can J Remote Sens 29:141–153
Barsi JA, Hook SJ, Schott JR, Raqueno NG, Markham BL (2007) Landsat-5 thematic mapper thermal band calibration update. IEEE Trans Geosci Remote Sens 44:552–555
BMKG (Meteorological and Geophysical Bureau of Bandung City) (2011) Climate data of Bandung City year 1990–2010. Bandung, West Java. Indonesia
Carlson TN, Gillies RR, Perry EM (1994) A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote Sens Rev 9:161–173
Chrysoulakis N (2003) Estimation of the all-wave net radiation balance in urban environment with the combined use of terra/ASTER multispectral imagery and in-situ spatial data. J Geophys Res 108(D18):4582. doi:10.1029/2003JD003396
Excelisvis (2006) ENVI classic tutorial: decision tree classification. http://www.exelisvis.com/portals/0/pdfs/envi/Decision_Tree.pdf. Accessed 1 October 2012
Gallo KP, Owen TW (1998) Assessment of urban heat island: a multi-sensor perspective for the Dallas-Ft.Worth, USA region. Geocart Int 13:35–41
Gillies RR, Carlson TN (1995) Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models. J Appl Meteorol 34:745–756
Gillies RR, Carlson TN, Cui J, Kustas WP, Humes KS (1997) A verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation index (NDVI) and surface radiant temperature. Int J Remote Sens 18:3145–3166
Gitelson AA (2004) Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. J Plant Physiol 161:165–173
Government of Bandung City (2011). Climate and region. http://www.bandung.go.id/?fa=sekilas.detail&id=12. Accessed 24 September 2012
Government of West Java Province (2011). Population. http://www.jabarprov.go.id/index.php/subMenu/75. Accessed 17 April 2013
Goward SN, Xue Y, Czajkowski KP (2002) Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements: an exploration with the simplified simple biosphere model. Remote Sens Environ 79:225–242
Huete AR (1988) A soil-adjusted vegetation index (SAVI). Remote Sens Environ 3:295–309
Jackson RD, Huete AR (1991) Interpreting vegetation indices. Prev Veterin Med 11:185–200
Jiménez-Muñoz JC, Sobrino JA (2003) A generalized single channel method for retrieving land surface temperature from remote sensing data. J Geophys Res 108(D22):4688. doi:10.1029/2003JD003480
Jones HG, Vaughan RA (2010) Remote sensing of vegetation: principles, techniques, and applications. Oxford University Press, UK
Lo CP, Quattrochi DA, Luvall JC (1997) Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. Int J Remote Sens 18:287–304
Lu D, Weng Q (2006) Use of impervious surface in urban land use classification. Remote Sens Environ 102:146–160
Mahfouf JF, Richard E, Mascart P (1987) The influence of soil and vegetation on the development of mesoscale circulation. J Appl Meteorol 26:1483–1495
McPherson RA (2007) A review of vegetation—atmosphere interactions and their influences on mesoscale phenomena. Prog Phys Geogr 31:261–285
NASA (1998) Landsat 7 science data users handbook. Retrieved October 7, 2012. http://landsathandbook.gsfc.nasa.gov/pdfs/Landsat7_Handbook.pdf
Ray TW (1994) Vegetation in remote sensing FAQs, applications. ER Mapper Ltd, Perth
Schowengerdt RA (1997) Remote sensing, models and methods for image processing, 2nd edn. Academic, London
Sebari I, He D-C (2013) Automatic fuzzy object-based analysis of VHSR images for urban objects extraction. ISPRS J Photogram and Rem Sens 79:171–184
Sobrino JA, Jiménez-Muñoz JC, Paolini L (2004) Land surface temperature retrieval from LANDSAT TM 5. Remote Sens Environ 90:434–440
Statistical Beaureu of Bandung City. Population year 2011. http://bandungkota.bps.go.id/ Accessed 24 September 2012
Stewart ID, Oke TR (2012) Local climate zones for urban temperature studies. Bull Am Meteorol Soc 93:1879–1900
Taha H (1997) Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energy Build 25:99–103
Voogt J, Oke T (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86:370–384
Weng Q, Lu D, Schubring J (2004) Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ 89:467–483
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sens 3:583–594
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Ramdani, F., Setiani, P. Spatio-temporal analysis of urban temperature in Bandung City, Indonesia. Urban Ecosyst 17, 473–487 (2014). https://doi.org/10.1007/s11252-013-0332-1
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DOI: https://doi.org/10.1007/s11252-013-0332-1