Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in Sundarban Biosphere Reserve, India

Modeling Earth Systems and Environment - Tập 2 - Trang 1-11 - 2016
Mehebub Sahana1, Raihan Ahmed1, Haroon Sajjad1
1Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India

Tóm tắt

The paper utilized Landsat 5 TM and Landsat 8 OLI for analyzing land use/land cover change and its impact on land surface temperature in Sundarban Biosphere Reserve, India. Split window algorithm and spectral radiance model were used for determining land surface temperature from Landsat 8 OLI and Landsat 5 TM, respectively. The land use land cover change analysis revealed phenomenal increase in the waterlogged areas followed by settlement and paddy and a decrease in open forest followed by deposition and water body. The distribution of average change in land surface temperature shows that water recorded highest increase in temperature followed by deposition, open forest and settlement. Overlay of the transect profiles drawn on land use/land cover change map over land surface temperature map revealed that the land surface temperature has increased in those areas which were transformed from open forest to paddy, open forest to settlement, paddy to settlement and deposition to settlement. The study demonstrated that increase in non-evaporating surfaces and decrease in vegetation have increased the surface temperature and modified the temperature of the study area.

Tài liệu tham khảo

Abbasi HU, Soomro AS, Memon A, Samo SR, Karas IR (2012) Temperature modelling of indus basin using landsat data. Sindh Univ Res J Sci Ser 44(2):177–182 Ahmed B, Kamruzzaman M, Zhu X, Rahman MS, Choi K (2013) Simulating land cover changes and their impacts on land surface temperature in Dhaka, Bangladesh. Remote Sens 5:5969–5998. doi:10.3390/rs5115969 Banerjee K (2013) Decadal change in the surface water salinity profile of Indian Sundarbans: a potential indicator of climate change. J Mar Sci Res Dev. doi:10.4172/2155-9910.S11-002 Bera MK (2013) Adaptation with social vulnerabilities and flood Disasters in Sundarban Region: a study of Lodha Tribes in Sundarban, West Bengal. Indian J Dalit Tribal Stud 1(2):49–62 Buyadi SNA, Mohd WMNW, Misni A (2013) Impact of land use changes on the surface temperature distribution of area surrounding the National Botanic Garden, Shah Alam. Procedia Soc Behav Sci 101:516–525 Census of India (2011) Primary Census Abstracts. Office of the Register General and Census Commissioner, Ministry of Home Affairs, Government of India Chander G, Markham BL (2003) Revised Landsat-5 TM radiometric calibration procedures, and postcalibration dynamic ranges. IEEE Trans Geosci Remote Sens 41:2674–2677 Cristobal J, Munoz JCJ, Sobrino JA, Ninyerola M, Pons X (2009) Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapour and air temperature. J Geophys Res 114:08–103. doi:10.1029/2008JD010616 Islam MS, Islam KS (2013) Application of thermal infrared remote sensing to explore the relationship between land use-land cover changes and urban heat Island effect: a case study of Khulna City. J Bangladesh Inst Plan 6:49–60 Jalili SY (2013) The effect of land use on land surface temperature in the Netherlands.” Lund University, GEM Thesis Series nr 1 Julien Y, Sobrino JA, Matter C, Ruesca AB, Jimenezmuno JC, Soria G, Hidalgo V, Atitar M, Franch B, Cuenca J (2011) Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001. Int J Remote Sens 32(7):2057–2068 Kumar KS, Bhaskar PU, Padmakumari K (2012) Estimation of land surface temperature to study urban heat Island effect using Landsat ETM + Image. Int J Eng Sc Technol 4(2):771–778 Liu L, Zhang Y (2011) Urban heat Island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sens 3:1535–1552. doi:10.3390/rs3071535 Mallick J, Kant Y, Bharath BD (2008) Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J Ind Geophys Union 12(3):131–140 Marland G, Pielke RAS, Apps M, Avissar R, Betts RA, Davis KJ, Frumhoff PC, Jackson ST, Joyce LA, Kauppi P, Katzenberger J, MacDicken KG, Neilson RP, Niles JO, Niyogi DDS, Norby RJ, Pena N, Sampson N, Xue Y (2003) The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy. Clim Policy 3:149–157 Mbithi DM, Demessie ET, Kashiri T (2010) The impact of Land Use Land Cover (LULC) Changes on Land Surface Temperature (LST); a case study of Addis Ababa City, Ethiopia. Kenya Meteorological Services, Laikipia Airbase, P.O. Box 192-10400 Nanyuki Town, Kenya McMillin LM (1975) Estimation of sea surface temperatures from two infrared window measurements with different absorption. J Geophys Res 80:5113–5117 Mitra A, Gangopadhyay A, Banerjee K, Dube A, Schmidt A (2009) Observed changes in water mass properties in the Indian Sundarbans (northwestern Bay of Bengal) during 1980–2007. Curr Sci 97(10):1445–1452 Mondal I, Bandyopadhyay J (2014) Coastal zone mapping through geospatial technology for resource management of Indian Sundarban, West Bengal, India. Int J Remote Sens Appl 4(2):103–112 Omran ESE (2012) Detection of land-use and surface temperature change at different resolutions. J Geograph Inf Syst 4:189–203. doi:10.4236/jgis.2012.43024 Rajeshwari A, Mani ND (2014) Estimation of land surface temperature of Dindigul district using Landsat 8 data. Int J Res Eng Technol 3(5):122–126 Rozenstein O, Qin Z, Derimian Y, Karnieli A (2014) Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors 14:5768–5780. doi:10.3390/s140405768 Sameen MI, Kubaisy MAA (2014) Automatic surface temperature mapping in ArcGIS using Landsat-8 TIRS and ENVI tools case study: Al Habbaniyah, Lake. J Environ Earth 4(12):12–17 Srivastava PK, Majumdar TJ, Bhattacharya AK (2010) Study of land surface temperature and spectral emissivity using multi-sensor satellite data. J Earth Syst Sci 11:67–74