Abstract
Keti Bunder is a small coastal community situated at about 200 km south east of Karachi. It has four major creeks namely Chann, Hajamro, Kangri (Turchhan) and Khober with an arid subtropical climate and temperature remaining moderate throughout the year. This paper reports the application of an integration of Remote Sensing (RS) and Geographic Information Systems (GIS) for analysis and monitoring of the relationship of land surface temperature (LST) with Normalized Difference Vegetation Index (NDVI) in the area. LST is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. [1-5]. Remote sensing in accord with tradition utilizes the NDVI to provide specific information on vegetation abundance to the LST–vegetation relationship. For mapping purposes, satellite images of Landsat-5 ETM+, Landsat-7 TM and Landsat-8 OLI / TIRS images, acquired on March 08, 2000, April 29, 2010 and April 08, 2014 respectively, were used. The results indicate that the maximum land surface temperature increased gradually from 39°C in 2000, to 42°C in 2010 and 45°C in 2014. Due to global warming and climatic changes. Keti Bunder of the Indus delta has experienced a serious condition over the past few years; the local communities have suffered badly from climate change impacts as heavy rainfalls, floods and cyclones have forced people to migrate to other places for their livelihood and shelter. However, mean NDVI value increased to -0.009 in 2014 as compared to 2010 (-0.165), due to several plantations of mangroves being established by the government. In the past, the mangrove forest was degraded due to lack of freshwater and seawater intrusion. The rate of degradation of mangrove forest in the delta was approximately 6 percent per year between 1980 and 1995 and only a small percentage of mangroves are now considered to be healthy [6-7].
References
Anderson MC, Norman JM, Kustas WP, Houborg R, Starks PJ, Agam N. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales. Remote Sensing of Environment 2008; 112: 4227-4241. http://dx.doi.org/10.1016/j.rse.2008.07.009
Brunsell NA, Gillies RR. Length scale analysis of surface energy fluxes derived from remote sensing. Journal of Hydrometeorology 2003; 4: 1212-1219. http://dx.doi.org/10.1175/1525-7541(2003)004<1212:LSAOSE>2.0.CO;2
Karnieli A, Agam N, Pinker RT, Anderson M, Imhoff ML, Gutman GG. Use of NDVI and land surface temperature for drought assessment: Merits and limitations. Journal of Climate 2010; 23: 618-633. http://dx.doi.org/10.1175/2009JCLI2900.1
Kustas W, Anderson M. Advances in thermal infrared remote sensing for land surface modelling. Agricultural and Forest Meteorology 2009; 149: 2071-2081. http://dx.doi.org/10.1016/j.agrformet.2009.05.016
Zhang R, Tian J, Su H, Sun X, Chen S, Xia J. Two improvements of an operational two-layer model for terrestrial surface heat flux retrieval. Sensors 2008; 8: 6165-6187. http://dx.doi.org/10.3390/s8106165
World Wildlife Fund - Pakistan. Keti Bunder Village Development Plan. WWF Regional Office Karachi 2005.
World Wildlife Fund - Pakistan. Study on Knowledge, Attitudes & Practices of Fisher folk Communities about Fisheries and Mangrove Resources - Keti Bunder 2005.
Kerr YH, Lagouarde JP, Nerry F, Ottlé C. Land surface temperature retrieval techniques and applications. In Quattrochi DA, Luvall JC, Eds. Thermal remote sensing in land surface processes 2000; (pp. 33-109). Boca Raton, Fla.: CRC Press.
Arnfield AJ. Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology 2003; 23: 1-26. http://dx.doi.org/10.1002/joc.859
Bastiaanssen WGM, Menenti M, Feddes RA, Holtslag AAM. A remote sensing Surface Energy Balance Algorithm for Land (SEBAL). Formulation. Journal of Hydrology 1998; 212: 198-212. http://dx.doi.org/10.1016/S0022-1694(98)00253-4
Hansen J, Ruedy R, Sato M, Lo K. Global surface temperature change. Reviews of Geophysics 2010; 48: RG4004. http://dx.doi.org/10.1029/2010RG000345
Kalma JD, McVicar TR, McCabe MF. Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surveys in Geophysics 2008; 29: 421-469. http://dx.doi.org/10.1007/s10712-008-9037-z
Kogan FN. Operational space technology for global vegetation assessment. Bulletin of the American Meteorological Society 2001; 82: 1949-1964. http://dx.doi.org/10.1175/1520-0477(2001)082<1949:OSTFGV>2.3.CO;2
Su Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes Hydrology and Earth System Sciences 2002; 6: 85-100. http://dx.doi.org/10.5194/hess-6-85-2002
Voogt JA, Oke TR. Thermal remote sensing of urban climates. Remote Sensing of Environment 2003; 86: 370-384. http://dx.doi.org/10.1016/S0034-4257(03)00079-8
Weng Q. Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS Journal of Photogrammetry and Remote Sensing 2009; 64: 335-344. http://dx.doi.org/10.1016/j.isprsjprs.2009.03.007
Weng Q, Lu D, Schubring J. Estimation of land surface temperature, vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment 2004; 89: 467-483. http://dx.doi.org/10.1016/j.rse.2003.11.005
Quattrochi DA, Luvall JC. Thermal infrared remote sensing for analysis of landscape ecological processes: Methods and applications. Landscape Ecol 1999; 14(6): 577-598. http://dx.doi.org/10.1023/A:1008168910634
Zhang J, Wang Y, Li Y. A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6. Computers Geosci 2006; 32: 1796-1805. http://dx.doi.org/10.1016/j.cageo.2006.05.001
Owen TW, Carlson TN, Gillies RR. An assessment of satellite remotely sensed land cover parameters in quantitatively describing the climatic effect of urbanization. International Journal of Remote Sensing 1998; 19: 1663-1681. http://dx.doi.org/10.1080/014311698215171
Gallo KP, Owen TW. Assessment of urban heat island: a multisensory perspective for the Dallas-Ft. Worth, USA region. Geocarto International 1998a; 13: 35-41. http://dx.doi.org/10.1080/10106049809354662
Gallo KP, Owen TW. Satellite-based adjustments for the urban heat island temperature bias. Journal of Applied Meteorology 1998b; 38: 806-813. http://dx.doi.org/10.1175/1520-0450(1999)038<0806:SBAFTU>2.0.CO;2
Weng Q. A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in Zhujiang Delta, China. International Journal of Remote Sensing 2001; 22(10): 1999-2014.
Gowdy JM, Salman A. Institution and Ecosystem Functions: The Case of Keti Bunder, Pakistan. Ecosystem Services Economic (ESE), Division of Environmental Policy Implementation, Paper N° 10. The United Nation Environment Program 2011.
Abbasi AGN. Restoration of Singh’s primary rights over River Indus. 18th convention of SANA, Cherry Hill; NJ 2002; 4-7.
Glimpses. Indus for all programs, the journey a prosperous Indus ecoregion, WWF 2007-2008.
CSF: a joint project of USAID and Pakistan Ministry of Finance. Analysis of Coastal Processes in the Indus Delta: Recent Trends, Future Projections, and Practical Interventions to Maintain Infrastructure, Services, and Livelihoods in the Delta 2010.
Jensen JR. Introductory Digital Image Processing: A Remote Sensing Perspective. 2nd ed. Prentice Hall, Upper Saddle River, NJ 1996.
Jensen JR. Introductory digital image processing; 3rd ed. Upper Saddle River, NJ: Prentice Hall 1996.
Lillesand TM, Kiefer RW. Remote Sensing and Image Interpretation. 3rd ed. John Wiley & Sons, New York 1994.
Song C, Woodcock CE, Seto KC, Lenney MP, Macomber SA. Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? Remote Sensing of Environment 2001; 75(2); 230-244. http://dx.doi.org/10.1016/S0034-4257(00)00169-3
Bobrinskaya M. Remote Sensing for Analysis of relationships between Land Cover and Land Surface Temperature in Ten Megacities. Master’s of Science Thesis in Geoinformatics, TRITA-GIT EX 12-008, School of Architecture and the Built Environment, Royal Institute of Technology (KTH), Stockholm, Sweden 2012.
National Aeronautics and Space Administration (NASA). Landsat Project Science Office: Landsat-7 Science data users hand book. Chapter: 11, Data Products 2004. (http.//www.gsfc.nasa.gov/IAS/handbook.htmls).
Myneni RB, Dong JR, Tucker CJ, Kaufmann RK, Kauppi PE, Liski J, ZhouL, Alexeyev V, Hughes MK. A large carbon sink in the woody biomass of Northern Forests. Proceeding National Academy Sciences 2001; 98(26): 14784-14789. http://dx.doi.org/10.1073/pnas.261555198
Boone RB, Galvin KA. Generalizing El Nino effects upon Maasai livestock using hierarchical clusters of vegetation patterns. Photogrammetric Engineering and Remote Sensing 2000; 66(6): 737-744.
Chen D, Brutsaert W. Satellite-sensed distribution and spatial patterns of vegetation parameters over a tall grass prairie. Journal of the Atmospheric Sciences 1998; 55(7): 1225-1238. http://dx.doi.org/10.1175/1520-0469(1998)055<1225:SSDASP>2.0.CO;2
Gillies RR, Carlson TN, Cui J, Kustas WP, Humes KS. 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. International Journal of Remote Sensing 1997; 18(15): 3145-3166. http://dx.doi.org/10.1080/014311697217026
Weng Q, Lo CP. Spatial analysis of urban growth impacts on vegetation greenness with Landsat TM data. Geocarto International 2001; 16(4): 17-25. http://dx.doi.org/10.1080/10106040108542211
Rasul G, Mahmood A, Sadiq A, Khan SI. Vulnerability of the Indus Delta to Climate Change in Pakistan. Pakistan Journal of Meteorology 2012; 8(16).
Archer D. The Long Thaw. Princeton, NJ: Princeton University Press 2009.
Intergovernmental Panel on Climate Change. Climate Change 2007: The Physical Science Basis. Contribution of working group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, Geneva, Switzerland. Available at http://www.ipcc.ch
Reference available from URL http://www.pmd.gov.pk/rnd/ rndweb/rnd_new/climchange.php cited dated: 21 August 2014.
Reference available from URL http://karachimetrological. files.wordpress.com/2011/03cyclone-karachi.jpg. Cited dated: 29 November 2014.
Reference available from URL http://www.dawn.com/news/ 1013382/mangroves-plantation-near-keti-bunder-to-check-sea-intrusion cited dated: 30th May 2015.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2015 Zia Ur Rehman, Syed Jamil H. Kazmi, Farheen Khanum , Zuber Ali Samoon