Skip to main content
Log in

Spatio-temporal variation of land surface temperature and temperature lapse rate over mountainous Kashmir Himalaya

  • Published:
Journal of Mountain Science Aims and scope Submit manuscript

Abstract

In this study, Land Surface Temperature (LST) and its lapse rate over the mountainous Kashmir Himalaya was estimated using MODIS data and correlated with the observed in-situ air temperature (Tair) data. Comparison between the MODIS LST and Tair showed a close agreement with the maximum error of the estimate ±1°C and the correlation coefficient >0.90. Analysis of the LST data from 2002-2012 showed an increasing trend at all the selected locations except at a site located in the southeastern part of Kashmir valley. Using the GTOPO30 DEM, MODIS LST data was used to estimate the actual temperature lapse rate (ATLR) along various transects across Kashmir Himalaya, which showed significant variations in space and time ranging from 0.3°C to 1.2°C per 100 m altitude change. This observation is at variance with the standard temperature lapse rate (STLR) of 0.65°C used universally in most of the hydrological and other land surface models. Snowmelt Runoff Model (SRM) was used to determine the efficacy of using the ATLR for simulating the stream flows in one of the glaciated and snow-covered watersheds in Kashmir. The use of ATLR in the SRM model improved the R2 between the observed and predicted streamflows from 0.92 to 0.97. It is hoped that the operational use of satellite-derived LST and ATLR shall improve the understanding and quantification of various processes related to climate, hydrology and ecosystem in the mountainous and data-scarce Himalaya where the use of temperature and ATLR are critical parameters for understanding various land surface and climate processes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adnan M, Nabi G, Poomee MS, Ashraf A (2016) Snowmelt runoff prediction under changing climate in the Himalayan Cryosphere: a case of Gilgit River Basin. Geoscience Frontiers. https://doi.org/10.1016/j.gsf.2016.08.008

    Google Scholar 

  • Anderson MC, Allen RG, Morse A, Kustas WP (2012) Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sensing of Environment 122:50–65. https://doi.org/10.1016/j.rse.2011. 08.025

    Article  Google Scholar 

  • Anderson S (2002) An evaluation of spatial interpolation methods on air temperature in Phoenix, AZ. Available online: http://www.cobblestoneconcepts.com/ucgis2summer/anders on/anderson.htm, accessed on 1 November 2015.

    Google Scholar 

  • Apaydin H, Sonmez FK, Yildirim YE (2004) Spatial interpolation techniques for climate data in the GAP region in Turkey. Climate Research 28(1):31–40. http://doi.org/10.3354/cr028031

    Article  Google Scholar 

  • Arnold NS, Willis IC, Sharp MJ, et al. (1996) A distributed surface energy–balance model for a small valley glacier. Journal of Glaciology 42(140): 77–89. https://doi.org/10.3189/S0022143000030549

    Article  Google Scholar 

  • Badar B, Romshoo SA, Khan MA (2013) Modelling the catchment hydrological response in a Himalayan lake as a function of changing land system. Earth System Science 112(2): 434–450. https://doi.org/10.1007/s12040-013-0285-z

    Google Scholar 

  • Becker-Reshef I, Vermote E, Lindeman M, Justice C (2010) A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sensing of Environment 114(6): 1312–1323. https://doi.org/10.1016/j.rse.2010.01.010

    Article  Google Scholar 

  • Benali A, Carvalho AC, Nunes JP, et al. (2012) Estimating air surface temperature in Portugal using MODIS LST data. Remote Sensing of Environment 124: 108–121. https://doi.org/10.1016/j.rse.2012.04.024

    Article  Google Scholar 

  • Blandford TR, Humes KS, Harshburger BJ, et al. (2008) Seasonal and synoptic variations in near-surface air temperature lapse rates in a mountainous basin. Journal of Applied Meteorology and Climatology 47(1): 249–261. https://doi.org/10.1175/2007JAMC1565.1

    Article  Google Scholar 

  • Blöschl G (1991) The influence of uncertainly in the air temperature and albedo on snowmelt. Hydrology Research 22: 95–108.

    Google Scholar 

  • Blum M, Lensky IM, Rempoulakis P, Nestel D (2015) Modeling insect population fluctuations with satellite land surface temperature. Ecological Modelling 311: 39–47.https://doi.org/10.1016/j.ecolmodel.2015.05.005

    Article  Google Scholar 

  • Braithwaite RJ, Raper SCB (2007) Glaciological conditions in seven contrasting regions estimated with the degree-day model. Annals of Glaciology 46: 297–302. https://doi.org/10.3189/172756407782871206

    Article  Google Scholar 

  • Brubaker K, Rango A, Kustas W (1996) Incorporating radiation inputs into the Snowmelt Runoff Model. Hydrological Processes 10: 1329–1343. https://doi.org/10.1002/(SICI) 1099-1085(199610)10:10<1329::AID-HYP464>3.0.CO;2-W

    Article  Google Scholar 

  • Chow V T, Maidment DR, Mays LW (1988) Applied hydrology. McGraw-Hill Series in Water Resources and Environmental Engineering. McGraw-Hill: New York. ISBN 0-07-010810-2.

    Google Scholar 

  • Czajkowski KP, Goward SN, Stadler S, Walz A (2000) Thermal remote sensing of near surface environmental variables: Application over the Oklahoma Mesonet. The Professional Geographer 52(2): 345–357. https://doi.org/10.1111/0033-0124.00230

    Article  Google Scholar 

  • Dar RA, Romshoo SA (2012) Estimating daily stream flow from the glacierized mountainous Kashmir Himalayan basin. Journal of Research and Development 12: 113–130. Available online: http://cord.uok.edu.in/Files/4701b853-a330-4f94-a00e-01555a32a0ff/Journal/9ef27cc3-2512-4ef9-95c5-2ee0a8a936e7.pdf, accessed on 1 October 2017.

    Google Scholar 

  • Dar RA, Paul, O, Murtaza, KO, Romshoo, SA (2017). Glacialgeomorphic study of the Thajwas glacier valley, Kashmir Himalayas, India. Quaternary International, 444: 157–171. https://doi.org/10.1016/j.quaint.2017.05.021

    Article  Google Scholar 

  • Datt P, Srivastava PK, Negi PS, Satyawali PK (2008) Surface energy balance of seasonal snow cover for snow-melt estimation in N–W Himalaya. Journal of Earth System Science 117(5): 567–573. https://doi.org/10.1007/s12040-008-0053-7

    Article  Google Scholar 

  • Diak GR, Mecikalski JR, Anderson MC, et al. (2004) Estimating land surface energy budgets from space: Review and current efforts at the University of Wisconsin-Madison and USDAARS. Bulletin of the American Meteorological Society 85(1): 65–78. https://doi.org/10.1175/BAMS-85-1-65

    Article  Google Scholar 

  • Eigdir AN (2003) Investigation of the snowmelt runoff in the Orumiyeh region, using modeling, GIS and RS techniques. M.Sc. thesis, Enschede, Netherlands, International Institute for Geoinformation Science and Earth Observation (ITC). Accessed online: https://www.itc.nl/library/papers_2003/msc/wrem/Najafi.pdf, accessed on 1 November 2016.

    Google Scholar 

  • Field CB, Behrenfeld MJ, Randerson JT, Falkowski P (1998) Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281(5374): 237–240. https://doi.org/10.1126/science.281.5374.237

    Article  Google Scholar 

  • Geiger R (1965) The Climate near the ground. Fourth Edition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Gu L, Meyers T, Pallardy SG, et al. (2007) Influences of biomass heat and biochemical energy storages on the land surface fluxes and radiative temperature. Journal of Geophysical Research: Atmospheres 112(D2). https://doi.org/10.1029/2006JD007425

  • Guzinski R, Anderson MC, Kustas WP, et al. (2013) Using a thermal-based two source energy balance model with timedifferencing to estimate surface energy fluxes with day-night MODIS observations. Hydrology and Earth System Sciences 17(7): 2809–2825. https://doi.org/10.5194/hess-17-2809-2013

    Article  Google Scholar 

  • Hachem S, Duguay CR, Allard M (2012) Comparison of MODISderived land surface temperatures with ground surface and air temperature measurements in continuous permafrost terrain. The Cryosphere 6(1): 51–69. https://doi.org/10.5194/tc-6-51-2012

    Article  Google Scholar 

  • Hartkamp AD, De Beurs K, Stein A, White JW (1999) Interpolation techniques for climate variables. NRG-GIS Series 99-01. Mexico, D.F.: CIMMYT. ISSN: 1405-7484. Available online: http://repository.cimmyt.org:8080/xmlui/bitstream/handle/10883/988/67882.pdf?sequence=1, accessed on 1 November 2016.

    Google Scholar 

  • Hu L, Brunsell NA (2013) The impact of temporal aggregation of land surface temperature data for surface urban heat island (SUHI) monitoring. Remote Sensing of Environment 134: 162–174. https://doi.org/10.1016/j.rse.2013.02.022

    Article  Google Scholar 

  • Huete A, Didan K, Miura T, et al. (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 83(1): 195–213. https://doi.org/10.1016/S0034-4257(02)00096-2

    Article  Google Scholar 

  • IPCC (2007) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. In: Solomon S, Qin D, Manning M, et al. (eds.), Cambridge, United Kingdom: Cambridge University Press.

  • Ishtiaque A, Myint SW, Wang C (2016) Examining the ecosystem health and sustainability of the world's largest mangrove forest using multi-temporal MODIS products. Science of The Total Environment 569: 1241–1254. https://doi.org/10.1016/j.scitotenv.2016.06.200

    Article  Google Scholar 

  • Jain SK, Goswami A, Saraf AK (2013) Determination of land surface temperature and its lapse rate in the Satluj River basin using NOAA data. International Journal of Remote Sensing 29(11): 3091–3103. https://doi.org/10.1080/014311 60701468992

    Article  Google Scholar 

  • Jang JD, Viau AA, Anctil F (2004) Neural network estimation of air temperatures from AVHRR data. International Journal of Remote Sensing 25: 4541–4554. https://doi.org/10.1080/01431160310001657533

    Article  Google Scholar 

  • Jensen JR (2005) Introductory digital image processing: A remote sensing perspective (III Edition). Prentice-Hall Inc. ISBN: 0131453610

    Google Scholar 

  • Jensen JR (2007) Remote sensing of the environment: An earth resource perspective (II Edition). Prentice-Hall Inc. ISBN: 97881731716809

    Google Scholar 

  • Kattel DB, Yao T, Yang K, et al. (2013) Temperature lapse rate in complex mountain terrain on the southern slope of the central Himalayas. Theoretical and Applied Climatology 113(3–4): 671–682. https://doi.org/10.1007/s00704-012-0816-6

    Article  Google Scholar 

  • Kirchner M, Faus-Kessler T, Jakobi G, et al. (2013) Altitudinal temperature lapse rates in an Alpine valley: trends and the influence of season and weather patterns. International Journal of Climatology 33(3): 539–555. https://doi.org/10.1002/joc.3444

    Article  Google Scholar 

  • Koch J, Siemann A, Stisen S, Sheffield J (2016) Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics. Journal of Geophysical Research: Atmospheres 121(10): 5430–5452. https://doi.org/10.1002/2015JD024482

    Google Scholar 

  • König M, Winther JG, Isaksson E (2001) Measuring snow and glacier ice properties from satellite. Reviews of Geophysics 39(1): 1–27. https://doi.org/10.1029/1999RG000076

    Article  Google Scholar 

  • Kumar R, Singh S, Randhawa SS, et al. (2014) Temperature trend analysis in the glacier region of Naradu Valley, Himachal Himalaya, India. Comptes Rendus Geoscience 346(9): 213–222. https://doi.org/10.1016/j.crte.2014.09.001

    Article  Google Scholar 

  • Li X, Wang L, Chen D, et al. (2013) Near-surface air temperature lapse rates in the mainland China during 1962–2011. Journal of Geophysical Research: Atmospheres 118(14): 7505–7515. https://doi.org/10.1002/jgrd.50553

    Google Scholar 

  • Liu YQ, Mamtimin A, Huo W, et al. (2014) Estimation of the land surface emissivity in the hinterland of Taklimakan Desert. Journal of Mountain Science 11(6): 1543–1551. https://doi.org/10.1007/s11629-014-3090-5

    Article  Google Scholar 

  • Lulla K, Helfert M, Holland D (1994) The NASA Space Shuttle Earth Observations database for global change science. In Remote Sensing and Global Climate Change (pp. 355-365). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-79287-8_16

    Book  Google Scholar 

  • Martinec J (1975) Snowmelt-runoff model for stream flow forecasts. Hydrology Research 6(3): 145–154.

    Google Scholar 

  • Mostovoy GV, King RL, Reddy KR, et al. (2006) Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi. GIScience & Remote Sensing 43(1): 78–110. https://doi.org/10.2747/1548-1603.43.1.78

    Article  Google Scholar 

  • Muster S, Langer M, Abnizova A, et al. (2015) Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes. Remote Sensing of Environment 168: 1–12. https://doi.org/10.1016/j.rse.2015. 06.017

    Article  Google Scholar 

  • Neteler M (2010) Estimating daily Land Surface Temperatures in mountainous environments by reconstructed MODIS LST data. Remote Sensing 2(1): 333–351. https://doi.org/10.3390/rs1020333

    Article  Google Scholar 

  • Panday PK, Williams CA, Frey KE, Brown ME (2014) Application and evaluation of a snowmelt runoff model in the Tamor River basin, Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach. Hydrological Processes 28(21): 5337–5353. https://doi.org/10.1002/hyp.10005

    Article  Google Scholar 

  • Pitman AJ (2003) The evolution of, and revolution in, land surface schemes designed for climate models. International Journal of Climatology 23: 479–510. https://doi.org/10.1002/joc.893

    Article  Google Scholar 

  • Prihodko L, Goward SN (1997) Estimation of air temperature from remotely sensed surface observations. Remote Sensing of Environment 60(3): 335–346. https://doi.org/10.1016/S0034-4257(96)00216-7

    Article  Google Scholar 

  • Prince SD, Goward SN (1995) Global primary production: a remote sensing approach. Journal of Biogeography 22: 815–835. https://doi.org/10.2307/2845983

    Article  Google Scholar 

  • Qin Z, Karnieli A, Berliner P (2002) Remote sensing analysis of the land surface temperature anomaly in the sand-dune region across the Israel-Egypt border. International Journal of Remote Sensing 23(19): 3991–4018. https://doi.org/10.1080/01431160110116310

    Article  Google Scholar 

  • Rashid I, Romshoo SA, Abdullah T (2017) The recent deglaciation of Kolahoi valley in Kashmir Himalaya, India in response to the changing climate. Journal of Asian Earth Sciences 138: 38–50. https://doi.org/10.1016/j.jseaes.2017. 02.002

    Article  Google Scholar 

  • Rashid I, Romshoo SA, Chaturvedi RK, et al. (2015) Projected Climate Change Impacts on Vegetation Distribution over Kashmir Himalayas. Climatic Change 132(4): 601–613. https://doi.org/10.1007/s10584-015-1456-5

    Article  Google Scholar 

  • Rather MI, Rashid I, Shahi N, et al. (2016) Massive land system changes impact water quality of the Jhelum River in Kashmir Himalaya. Environmental Monitoring and Assessment 188(3): 1–20. https://doi.org/10.1007/s10661-016-5190-x

    Article  Google Scholar 

  • Raza M, Ahmad A, Mohammad A (1978) The Valley of Kashmir: A Geographical Interpretation. Vikas Publishing House: New Delhi. ISBN: 9780890890585

    Google Scholar 

  • Romshoo SA, Bhat SA, Rashid I (2012) Geoinformatics for assessing the morphometric control on the hydrological response at watershed scale in Upper Indus basin. Earth System Science 121(3): 659–686. https://doi.org/10.1007/s12040-012-0192-8

    Article  Google Scholar 

  • Romshoo SA, Dar RA, Rashid I, et al. (2015) Implications of shrinking cryosphere under changing climate on the streamflows in the Lidder catchment in the Upper Indus Basin, India. Arctic Antarctic and Alpine Research 47(4): 627–644. https://doi.org/10.1657/AAAR0014-088

    Article  Google Scholar 

  • Romshoo SA, Koike M, Hironaka S, et al. (2002) Influence of Surface and Vegetation Characteristics on C-band Radar Measurements for Soil Moisture Content. Journal of Indian Society of Remote Sensing 30(4): 229–244. https://doi.org/10.1007/BF03000366

    Article  Google Scholar 

  • Romshoo SA, Rashid I (2010) Potential and Constraints of Geospatial Data for Precise Assessment of the Impacts of Climate Change at Landscape Level. International Journal of Geomatics and Geosciences 1(3), 386–405. Available online: http://www.ipublishing.co.in/jggsvol1no12010/EIJGGS2009. pdf, accessed on 1 November 2016.

    Google Scholar 

  • Running SW, Nemani RR, Heinsch FA, et al. (2004) A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54(6): 547–560. https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMO G]2.0.CO;2

    Article  Google Scholar 

  • Sharma V, Mishra VD, Joshi PK (2012) Snow cover variation and streamflow simulation in a snow-fed river basin of the Northwest Himalaya. Journal of Mountain Science 9(6): 853–868. https://doi.org/10.1007/s11629-012-2419-1

    Article  Google Scholar 

  • Singh P (1991) A temperature lapse rate study in western Himalayas. Hydrology Journal (Indian Association of Hydrologists) 14: 156–163.

    Google Scholar 

  • Snyder W, Wan Z, Zhang Y, Feng YZ (1998) Classification-based emissivity for land surface temperature measurement from space. International Journal of Remote Sensing 19: 2753–2774. https://doi.org/10.1080/014311698214497

    Article  Google Scholar 

  • Streutker DR (2002) A remote sensing study of the urban heat island of Houston, Texas. International Journal of Remote Sensing 23(13): 2595–2608. https://doi.org/10.1080/014311 60110115023

    Article  Google Scholar 

  • Sun Y (2011) Retrieval and application of land surface temperature Available online: http://www.geo.utexas.edu/courses/387h/papers/term%20paper-sun.pdf, accessed on 1 November 2016.

    Google Scholar 

  • Sun YJ, Wang JF, Zhang RH, et al. (2005) Air temperature retrieval from remote sensing data based on thermodynamics. Theoretical and Applied Climatology 80(1): 37–48. https://doi.org/10.1007/s00704-004-0079-y

    Article  Google Scholar 

  • Tahir AA, Chevallier P, Arnaud Y, et al. (2011) Modeling snowmelt-runoff under climate scenarios in the Hunza River basin, Karakoram Range, Northern Pakistan. Journal of Hydrology 409(1): 104–117. https://doi.org/10.1016/j.jhydrol. 2011.08.035

    Article  Google Scholar 

  • Thayyen RJ, Dimri AP (2014) Factors controlling Slope Environmental Lapse Rate (SELR) of temperature in the monsoon and cold-arid glacio-hydrological regimes of the Himalaya. The Cryosphere Discussions 8(6): 5645–5686. https://doi.org/10.5194/tcd-8-5645-2014

    Article  Google Scholar 

  • Vancutsem C, Ceccato P, Dinku T, Connor SJ (2010) Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sensing of Environment 114(2): 449–465. https://doi.org/10.1016/j.rse.2009.10.002

    Article  Google Scholar 

  • Vogt JV, Viau AA, Paquet F (1997) Mapping regional air temperature fields using satellite- derived surface skin temperatures. International Journal of Climatology 17(14): 1559–1579. https://doi.org/10.1002/(SICI)1097-0088(199711 30)17:14<1559::AID-JOC211>3.0.CO;2-5

    Article  Google Scholar 

  • Wan Z (1999) MODIS land-surface temperature algorithm theoretical basis document (LST ATBD). Institute for Computational Earth System Science, Santa Barbara, 75. Available online: https://modis.gsfc.nasa.gov/data/atbd/atbd_mod11.pdf, accessed on 1 November 2016.

    Google Scholar 

  • Wan Z (2006) MODIS land surface temperature products users’ guide. Institute for Computational Earth System Science, University of California, Santa Barbara. Available online: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.45 7.2833&rep=rep1&type=pdf, accessed on 1 November 2016.

    Google Scholar 

  • Wan Z (2007) Collection-5 MODIS Land Surface Temperature Products Users' Guide. ICESS, University of California, Santa Barbara. Available online: http://www.icess.ucsb.edu/modis/LstUsrGuide/MODIS_LST_products_Users_guide_C5.pdf, accessed on 1 November 2016.

    Google Scholar 

  • Wan Z, Dozier J (1996) A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on Geoscience and Remote Sensing 34(4): 892–905. https://doi.org/10.1109/36.508406

    Article  Google Scholar 

  • Wan Z, Li ZL (1997) A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Transactions on Geoscience and Remote Sensing 35: 980–996. https://doi.org/10.1109/36.602541

    Article  Google Scholar 

  • Wan Z, Snyder W (2012) MODIS land-surface temperature algorithm theoretical basis document (LST ATBD). Version 3.3. Available online: https://modis.gsfc.nasa.gov/data/atbd/atbd_mod11.pdf, accessed on 1 November 2016.

    Google Scholar 

  • Wan Z, Zhang Y, Zhang Q, Li ZL (2002) Validation of the landsurface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment 83(1): 163–180. https://doi.org/10.1016/S0034-4257(02)00093-7

    Article  Google Scholar 

  • Wang W, Liang S, Meyers T (2008) Validating MODIS land surface temperature products using long-term nighttime ground measurements. Remote Sensing of Environment 112(3): 623–635. https://doi.org/10.1016/j.rse.2007.05.024

    Article  Google Scholar 

  • Weiss M, Troufleau D, Baret F, et al. (2001) Coupling canopy functioning and radiative transfer models for remote sensing data assimilation. Agricultural and Forest Meteorology 108(2): 113–128. https://doi.org/10.1016/S0168-1923(01)00234-9

    Article  Google Scholar 

  • Weng Q (2003) Fractal analysis of satellite-detected urban heat island effect. Photogrammetric Engineering and Remote Sensing 69(5): 555–566. https://doi.org/10.14358/PERS.69.5.555

    Article  Google Scholar 

  • Weng Q, Lu D, Schubring J (2004) Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment 89(4): 467–483. https://doi.org/10.1016/j.rse.2003.11.005

    Article  Google Scholar 

  • Willmott CJ, Robeson SM (1995) Climatologically aided interpolation (CAI) of terrestrial air temperature. International Journal of Climatology 15(2): 221–229. https://doi.org/10.1002/joc.3370150207

    Article  Google Scholar 

  • Zakšek K, Schroedter-Homscheidt M (2009) Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments. ISPRS Journal of Photogrammetry and Remote Sensing 64(4): 414–421. https://doi.org/10.1016/j.isprsjprs.2009.02.006

    Article  Google Scholar 

  • Zaz S, Romshoo SA (2013) Recent Variation of Temperature, Trends in Kashmir Valley (India). Journal of Himalayan Ecology & Sustainable Development 8: 42–63.Available online: http://envirsc.uok.edu.in/Files/ab1ac1f1-07e3-42a2-85bc-83717ef39155/Journal/c012e6c6-7355-4af1-8950-54f718b61828.pdf, accessed on 1 October 2017.

    Google Scholar 

  • Zhang X, Hu Y, Jia G, et al. (2015) Land surface temperature shaped by urban fractions in megacity region. Theoretical and Applied Climatology 127(3): 965–975. https://doi.org/10.1007/s00704-015-1683-8

    Google Scholar 

Download references

Acknowledgements

The work was conducted as part of the Department of Science and Technology (DST), Government of India sponsored consortium project titled “Himalayan Cryosphere: Science and Society” and the financial assistance received from the Department under the project to accomplish this research is thankfully acknowledged. The authors express gratitude to the three anonymous reviewers and the handling Editor for their valuable comments and suggestions on the earlier versions of the manuscript that have greatly improved the content and structure of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shakil Ahmad Romshoo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Romshoo, S.A., Rafiq, M. & Rashid, I. Spatio-temporal variation of land surface temperature and temperature lapse rate over mountainous Kashmir Himalaya. J. Mt. Sci. 15, 563–576 (2018). https://doi.org/10.1007/s11629-017-4566-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11629-017-4566-x

Keywords

Navigation