Estimation of land surface temperature from atmospherically corrected LANDSAT TM image using 6S and NCEP global reanalysis product

Environmental Earth Sciences

Volumn 72, Issue 12, 2014, Pages 5183-5196

  Srivastava, Prashant K ^a,b,c   Han, Dawei ^c   Rico Ramirez, Miguel A ^c   Bray, Michaela ^d   Islam, Tanvir ^c,e,f   Gupta, Manika ^g   Dai, Qiang ^c  

^a NASA GODDARD SPACE FLIGHT CENTER   (United States)

^b University of Maryland   (United States)

^c UNIVERSITY OF BRISTOL   (United Kingdom)

^d CARDIFF UNIVERSITY   (United Kingdom)

^e NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^f Department of Environmental and Radiological Health Sciences   (United States)

^g INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

6S correction; Agricultural landscape; Land surface temperature (LST); Precipitable water vapour; Weather research and forecasting model (WRF)

Indexed keywords

ATMOSPHERIC TEMPERATURE; LAND SURFACE TEMPERATURE; SATELLITES; SOIL MOISTURE; SURFACE MEASUREMENT; SURFACE PROPERTIES; WATER VAPOR;

AGRICULTURAL LANDSCAPES; ATMOSPHERIC CORRECTIONS; NATIONAL CENTER FOR ENVIRONMENTAL PREDICTIONS; OPTICAL SATELLITE IMAGES; PRECIPITABLE WATER VAPOUR; S CORRECTION; VERTICAL DISTRIBUTIONS; WEATHER RESEARCH AND FORECASTING MODELS;

WEATHER FORECASTING;

ATMOSPHERIC CORRECTION; ESTIMATION METHOD; IMAGE ANALYSIS; LAND SURFACE; LANDSAT; PRESSURE EFFECT; SATELLITE IMAGERY; WATER VAPOR;

IOWA; UNITED STATES; WALNUT CREEK;

EID: 84912111097     PISSN: 18666280     EISSN: 18666299     Source Type: Journal    
DOI: 10.1007/s12665-014-3388-1     Document Type: Article

References (56)

1. Abdel Wahab M, Sharif T (1995) Estimation of precipitable water at different locations using surface dew-point. Theor Appl Climatol 51(3):153–157
2. Anderson GP, Chetwynd JH, Kneizys FX et al (1994) MODTRAN 3: suitability as a flux-divergence code. In: Proceedings of the 4th ARM-Science Team Meeting, pp 75–80
3. Artis DA, Carnahan WH (1982) Survey of emissivity variability in thermography of urban areas. Remote Sens Environ 12(4):313–329
4. Bolton D (1980) The computation of equivalent potential temperature. Mon Weather Rev 108(7):1046–1053
5. Borge R, Alexandrov V, del Vas JJ, Lumbreras J, Rodriguez E (2008) A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula. Atmos Environ 42(37):8560–8574. doi:10.1016/j.atmosenv.2008.08.032
6. Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and leaf area index* 1. Remote Sens Environ 62(3):241–252
7. Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modelling system. Part I: model implementation and sensitivity. Mon Weather Rev 129(4):569–585
8. Etherton B, Santos P (2008) Sensitivity of WRF forecasts for South Florida to initial conditions. Weather Forecast 23(4):725–740
9. Fernandez LI, Salio P, Natali MP, Meza AM (2010) Estimation of precipitable water vapour from GPS measurements in Argentina: validation and qualitative analysis of results. Adv Space Res 46(7):879–894. doi:10.1016/j.asr.2010.05.012
10. Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). NCAR Technical Note NCAR/TN-398STR
11. Gupta M, Srivastava PK (2010) Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India. Water Int 35(2):233–245
12. Holben BN (1986) Characteristics of maximum-value composite images from temporal Avhrr data. Int J Remote Sens 7(11):1417–1434
13. Ishak AM, Bray M, Remesan R, Han D (2010) Estimating reference evapotranspiration using numerical weather modelling. Hydrol Process 24(24):3490–3509
14. Ishak A, Remesan R, Srivastava P, Islam T, Han D (2013) Error correction modelling of wind speed through hydro-meteorological parameters and mesoscale model: a hybrid approach. Water Resour Manage 27(1):1–23. doi:10.1007/s11269-012-0130-1
15. Islam T, Rico-Ramirez M, Han D, Bray M, Srivastava P (2013) Fuzzy logic based melting layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations. Theoret Appl Climatol 112(1–2):317–338. doi:10.1007/s00704-012-0721-z
16. Jade S, Vijayan MSM, Gaur VK, Prabhu TP, Sahu SC (2005) Estimates of precipitable water vapour from GPS data over the Indian subcontinent. J Atmos Sol-Terr Phys 67(6):623–635. doi:10.1016/j.jastp.2004.12.010
17. Jin S, Luo OF (2009) Variability and Climatology of PWV from global 13-year GPS observations. IEEE Trans Geosci Remote 47(7):1918–1924. doi:10.1109/Tgrs.2008.2010401
18. Jin SG, Luo OF, Cho J (2009) Systematic errors between VLBI and GPS precipitable water vapor estimations from 5-year co-located measurements. J Atmos Sol-Terr Phys 71(2):264–272. doi:10.1016/j.jastp.2008.11.018
19. Kaufman YJ, Sendra C (1988) Algorithm for automatic atmospheric corrections to visible and near-Ir satellite imagery. Int J Remote Sens 9(8):1357–1381
20. Kirk-Davidoff DB, Hintsa EJ, Anderson JG, Keith DW (1999) The effect of climate change on ozone depletion through changes in stratospheric water vapour. Nature 402(6760):399–401
21. Lu D, Mausel P, Brondizio E, Moran E (2002) Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int J Remote Sens 23(13):2651–2671
22. Mallick J, Singh CK, Shashtri S, Rahman A, Mukherjee S (2012) Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city. Int J Appl Earth Obs Geoinf 19:348–358
23. Markham BL, Halthore RN, Goetz SJ (1992) Surface reflectance retrieval from satellite and aircraft sensors—results of sensor and algorithm comparisons during fife. J Geophys Res-Atmos 97(D17):18785–18795
24. Molders N, Kramm G (2010) A case study on wintertime inversions in Interior Alaska with WRF. Atmos Res 95(2–3):314–332. doi:10.1016/j.atmosres.2009.06.002
25. Moran M, Clarke T, Inoue Y, Vidal A (1994) Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sens Environ 49(3):246–263
26. Moran M, Jackson R, Clarke T, Qi J, Cabot F, Thome K, Markha B (1995) Reflectance factor retrieval from Landsat TM and SPOT HRV data for bright and dark targets. Remote Sens Environ 52(3):218–230
27. Mukherjee S, Shashtri S, Singh C, Srivastava PK, Gupta M (2009) Effect of canal on land use/land cover using remote sensing and GIS. J Indian Soc Remote Sens 37(3):527–537
28. Nemani RR, Running SW (1989) Estimation of regional surface-resistance to evapotranspiration from Ndvi and thermal-Ir Avhrr data. J Appl Meteorol 28(4):276–284
29. Pinty B, Verstraete M (1992) GEMI: a non-linear index to monitor global vegetation from satellites. Plant Ecol 101(1):15–20
30. Ristori P, Otero L, Fochesatto J, Flamant PH, Wolfram E, Quel E, Piacentini R, Holben B (2003) Aerosol optical properties measured in Argentina: wavelength dependence and variability based on sun photometer measurements. Opt Laser Eng 40(1–2):91–104 Pii S0143-8166(02)00057-X
31. Sandholt I, Rasmussen K, Andersen J (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens Environ 79(2–3):213–224
32. Schneider K, Mauser W (1996) Processing and accuracy of Landsat thematic mapper data for lake surface temperature measurement. Int J Remote Sens 17(11):2027–2041
33. Sharma AR, Badarinath KVS, Roy PS (2009) Comparison of ground reflectance measurement with satellite derived atmospherically corrected reflectance: a case study over semi-arid landscape. Adv Space Res 43(1):56–64. doi:10.1016/j.asr.2008.10.010
34. Sobrino JA, Li ZL, Stoll MP, Becker F (1996) Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data. Int J Remote Sens 17(11):2089–2114
35. Sobrino JA, Raissouni N, Li ZL (2001) A comparative study of land surface emissivity retrieval from NOAA data. Remote Sens Environ 75(2):256–266
36. Sobrino JA, Jimenez-Munoz JC, Paolini L (2004) Land surface temperature retrieval from LANDSAT TM 5. Remote Sens Environ 90(4):434–440. doi:10.1016/j.rse.2004.02.003
37. Solomon S, Rosenlof KH, Portmann RW, Daniel JS, Davis SM, Sanford TJ, Plattner GK (2010) Contributions of stratospheric water vapor to decadal changes in the rate of global warming. Science 327(5970):1219–1223. doi:10.1126/science.1182488
38. Srivastava PK (2013) Soil moisture estimation from SMOS satellite and mesoscale model for hydrological applications. Ph.D. thesis, University of Bristol, Bristol. doi:10.1002/asl.427
39. Srivastava PK, Mukherjee S, Gupta M (2010) Impact of urbanization on land use/land cover change using remote sensing and GIS: a case study. Int J Ecol Econ Stat 18(S10):106–117
40. Srivastava PK, Han D, Rico-Ramirez MA, Bray M, Islam T (2012) Selection of classification techniques for land use/land cover change investigation. Adv Space Res 50(9):1250–1265. doi:10.1016/j.asr.2012.06.032
41. Srivastava PK, Han D, Ramirez MR, Islam T (2013a) Machine learning techniques for downscaling SMOS satellite soil moisture using MODIS land surface temperature for hydrological application. Water Resour Manage 27(8):3127–3144
42. Srivastava PK, Han D, Rico-Ramirez MA, Al-Shrafany D, Islam T (2013b) Data Fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resour Manage 27(15):5069–5087
43. Srivastava PK, Han D, Rico Ramirez M, Islam T (2013c) Sensitivity and Uncertainty analysis of Mesoscale model downscaled hydro-meteorological variables for discharge prediction. Hydrol Process. doi:10.1002/hyp9946
44. Srivastava PK, Han D, Rico Ramirez MA, Islam T (2013d) Comparative assessment of evapotranspiration derived from NCEP and ECMWF global datasets through weather research and forecasting model. Atmos Sci Lett 14(2):118–125. doi:10.1002/asl2.427
45. Tachiiri K (2005) Calculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: a case study in the Marsabit District, Kenya. Isprs J Photogramm 59(3):103–114. doi:10.1016/j.isprsjprs.2004.09.001
46. Tanre D, Deroo C, Duhaut P, Herman M, Morcrette JJ, Perbos J, Deschamps PY (1990) Description of a computer code to simulate the satellite signal in the solar spectrum—the 5s code. Int J Remote Sens 11(4):659–668
47. Tanre D, Holben BN, Kaufman YJ (1992) Atmospheric correction against algorithm for NOAA-AVHRR products: theory and application. Geosci Remote Sens IEEE Trans 30(2):231–248
48. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106(D7):7183–7192
49. Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8(2):127–150
50. Vermote EF, Saleous NZ (2006) Operational atmospheric correction of MODIS visible to middle infrared land surface data in the case of an infinite Lambertian target. Earth Sci Satell Remote Sens 1:123–153
51. Vermote EF, ElSaleous N, Justice CO, Kaufman YJ, Privette JL, Remer L, Roger JC, Tanre D (1997a) Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: background, operational algorithm and validation. J Geophys Res-Atmos 102(D14):17131–17141
52. Vermote EF, Tanre D, Deuze JL, Herman M, Morcrette JJ (1997b) Second Simulation of the satellite signal in the solar spectrum, 6S: an overview. IEEE T Geosci Remote 35(3):675–686
53. Wang W, Seaman NL (1997) A comparison study of convective parameterization schemes in a mesoscale model. Mon Weather Rev 125(2):252–278
54. Weng Q, Lu D, Schubring J (2004) Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sens Environ 89(4):467–483
55. Yue W, Xu J, Tan W, Xu L (2007) The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data. Int J Remote Sens 28(15):3205–3226
56. Zhang J, Zhang XD (2010) A soil moisture assimilation scheme using satellite-retrieved skin temperature in meso-scale weather forecast model. Atmos Res 95(2–3):333–352. doi:10.1016/j.atmosres.2009.09.003