Estimation of land surface temperature from atmospherically corrected LANDSAT TM image using 6S and NCEP global reanalysis product
暂无分享,去创建一个
Dawei Han | Tanvir Islam | Prashant K. Srivastava | Miguel A. Rico-Ramirez | Manika Gupta | Qiang Dai | Michaela Bray | Dawei Han | M. Rico-Ramirez | P. Srivastava | Q. Dai | M. Gupta | T. Islam | M. Bray | M. Rico‐Ramirez
[1] Didier Tanré,et al. Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..
[2] D. Lu,et al. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .
[3] Prashant K. Srivastava. Soil moisture estimation from SMOS satellite and mesoscale model for hydrological applications , 2013 .
[4] B. Holben,et al. Aerosol optical properties measured in Argentina: wavelength dependence and variability based on sun photometer measurements , 2003 .
[5] David W. Keith,et al. The effect of climate change on ozone depletion through changes in stratospheric water vapour , 1999, Nature.
[6] Shuanggen Jin,et al. Systematic errors between VLBI and GPS precipitable water vapor estimations from 5-year co-located measurements , 2009 .
[7] M. Schaepman,et al. Retrieving sup-pixel land cover composition through an effective integration of the spatial, spectral, and temporal dimensions of MERIS imagery , 2005 .
[8] K. Taylor. Summarizing multiple aspects of model performance in a single diagram , 2001 .
[9] P. Salio,et al. Estimation of precipitable water vapour from GPS measurements in Argentina: Validation and qualitative analysis of results , 2010 .
[10] José A. Sobrino,et al. A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data , 2001 .
[11] Dawei Han,et al. Sensitivity and uncertainty analysis of mesoscale model downscaled hydro‐meteorological variables for discharge prediction , 2014 .
[12] Jing Zhang,et al. A soil moisture assimilation scheme using satellite-retrieved skin temperature in meso-scale weather forecast model , 2010 .
[13] José A. Sobrino,et al. Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data , 1996 .
[14] B. Holben. Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .
[15] B. Etherton,et al. Sensitivity of WRF Forecasts for South Florida to Initial Conditions , 2008 .
[16] I. Sandholt,et al. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status , 2002 .
[17] S. Solomon,et al. Contributions of Stratospheric Water Vapor to Decadal Changes in the Rate of Global Warming , 2010, Science.
[18] G. Grell,et al. A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .
[19] Wolfram Mauser,et al. Processing and accuracy of Landsat Thematic Mapper data for lake surface temperature measurement , 1996 .
[20] V. Gaur,et al. Estimates of precipitable water vapour from GPS data over the Indian subcontinent , 2005 .
[21] Dawei Han,et al. Comparative assessment of evapotranspiration derived from NCEP and ECMWF global datasets through Weather Research and Forecasting model , 2013 .
[22] W. Yue,et al. The relationship between land surface temperature and NDVI with remote sensing : application to Shanghai Landsat 7 ETM + data , 2009 .
[23] Dengsheng Lu,et al. Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research , 2002 .
[24] Dawei Han,et al. Data Fusion Techniques for Improving Soil Moisture Deficit Using SMOS Satellite and WRF-NOAH Land Surface Model , 2013, Water Resources Management.
[25] Y. Kaufman,et al. Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery , 1988 .
[26] Shuanggen Jin,et al. Variability and Climatology of PWV From Global 13-Year GPS Observations , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[27] Dawei Han,et al. Selection of classification techniques for land use - land cover change investigation , 2012 .
[28] Prashant K. Srivastava,et al. Impact of Urbanization on Land Use/Land Cover Change Using Remote Sensing and GIS: A Case Study , 2010 .
[29] M. S. Moran,et al. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .
[30] C. Justice,et al. Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation , 1997 .
[31] B. Pinty,et al. GEMI: a non-linear index to monitor global vegetation from satellites , 1992, Vegetatio.
[32] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .
[33] Dawei Han,et al. Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application , 2013, Water Resources Management.
[34] G. Kramm,et al. A case study on wintertime inversions in Interior Alaska with WRF , 2010 .
[35] K. Tachiiri. Calculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: A case study in the Marsabit District, Kenya , 2005 .
[36] Brian L. Markham,et al. Surface reflectance retrieval from satellite and aircraft sensors: Results of sensor and algorithm comparisons during FIFE , 1992 .
[37] Javed Mallick,et al. Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city , 2012, Int. J. Appl. Earth Obs. Geoinformation.
[38] T. Carlson,et al. On the relation between NDVI, fractional vegetation cover, and leaf area index , 1997 .
[39] J. Dudhia,et al. Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity , 2001 .
[40] P. Deschamps,et al. Description of a computer code to simulate the satellite signal in the solar spectrum : the 5S code , 1990 .
[41] V. Alexandrov,et al. A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula , 2008 .
[42] P. Srivastava,et al. Effect of canal on land use/land cover using remote sensing and GIS , 2009 .
[43] F. X. Kneizys,et al. MODTRAN3: Suitability as a flux-divergence code , 1995 .
[44] R. Simpson. On The Computation of Equivalent Potential Temperature , 1978 .
[45] Kurtis J. Thome,et al. Reflectance factor retrieval from Landsat TM and SPOT HRV data for bright and dark targets , 1995 .
[46] K. Badarinath,et al. Comparison of ground reflectance measurement with satellite derived atmospherically corrected reflectance: A case study over semi-arid landscape , 2009 .
[47] Dawei Han,et al. Error Correction Modelling of Wind Speed Through Hydro-Meteorological Parameters and Mesoscale Model: A Hybrid Approach , 2012, Water Resources Management.
[48] S. Running,et al. Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data , 1989 .
[49] N. Seaman,et al. A Comparison Study of Convective Parameterization Schemes in a Mesoscale Model , 1997 .
[50] José A. Sobrino,et al. Land surface temperature retrieval from LANDSAT TM 5 , 2004 .
[51] Dawei Han,et al. Fuzzy logic based melting layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations , 2012, Theoretical and Applied Climatology.
[52] Dawei Han,et al. Estimating reference evapotranspiration using numerical weather modelling , 2010 .
[53] W. Yue,et al. The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data , 2007 .
[54] Prashant K. Srivastava,et al. Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India , 2010 .
[55] Yoram J. Kaufman,et al. Atmospheric correction against algorithm for NOAA-AVHRR products: theory and application , 1992, IEEE Trans. Geosci. Remote. Sens..
[56] E. Vermote,et al. Operational Atmospheric Correction of MODIS Visible to Middle Infrared Land Surface Data in the Case of an Infinite Lambertian Target , 2006 .
[57] D. Artis,et al. Survey of emissivity variability in thermography of urban areas , 1982 .