Tag Archives: emissivity

Assessment of Uncertainties in the Computation of Atmospheric Correction Parameters for Landsat 5 TM and Landsat 7 ETM+ Thermal Band from Atmospheric Correction Parameter (ATMCORR) Calculator (Published)

This research examines the uncertainties present when computing atmospheric correction parameters (upwelling (Lu) and downwelling (Ld) radiances, and transmittance ( )) for the 9 flaring sites in Rivers State, Nigeria; and to estimate the total uncertainty introduced into the land surface temperature (LST) when they are applied. 7 Landsat 5 Thematic Mapper (TM) and 7 Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 04 March 2000 to 08 August 2012 with < 10 % cloud contamination were considered in order to evaluate a trend. All the sites are located within a single Landsat scene (Path 188, Row 057). Option B of the Atmospheric Correction Parameter (ATMCORR) Calculator was adopted to obtain Lu, Ld and  for Landsat scenes analysed. The Lu, Ld and  obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (Lλ) with the emissivity ( ) of each station estimated by using standard values for determined land surface cover. The Planck equation was inverted using the calibration constants to derive LST. To determine the uncertainties introduced by applying the calculated Lu, Ld and , an uncertainty analysis was undertaken. The difference between the Lu, Ld and  interpolated for each study site and that of reference site (Chokocho) were calculated and used for the analysis with 4 Lλ scenarios. The results show that the larger the % of water body at the site, the higher is the uncertainty introduced into LST retrieved from Landsat scene; and that the maximum uncertainty obtained for all sites are below the expected maximum error (0.5  0.8 K). Therefore, it was concluded that ATMCORR Calculator, have the ability to provide an automated method to derive Lu, Ld and  needed for generating LST in the Niger Delta.


Keywords: Niger-Delta, atmospheric correction, atmospheric correction parameters (atmcorr) calculator, emissivity, land surface temperature (lst)

Mapping of land cover and estimation of their emissivity values for gas flaring sites in the Niger Delta (Published)

This study examines the changes in land cover (LC) types at 6 gas flaring sites in Rivers State, Niger Delta region of Nigeria; and to estimate their emissivity (Ɛ) values. 15 Landsat scenes (3 Landsat 5 Thematic Mapper (TM) and 12 Landsat 7 Enhanced Thematic Mapper Plus (ETM+)) from 17 January 1986 to 08 March 2013 with < 30 % cloud contamination were used. All the sites are located within a single Landsat scene (Path 188, Row 057). Radiometric calibration of the multispectral bands of the data, and atmospheric correction for multispectral bands using dark object subtraction (DOS) method was carried out. The first unsupervised cluster analysis of the atmospherically corrected reflectance (bands 1-4) using the K-mean function of the MATLAB tool was carried out. The results obtained give 3 classes of LC type and cloud as the 4th class. The second cluster analysis was performed with the cloud-masked reflectance (bands 1-4) to give vegetation, soil, built up area and water LC types for all flaring sites. This was confirmed through the fieldwork observation for ground validation of Landsat 5 TM and Landsat 7 ETM+ in the Niger Delta that LC types obtained from satellite data are the same with those observed during the fieldwork. The method used to estimate Ɛ value for LC types at these sites is based on the Ɛ of 4 LC types present at each site. The changes in LC differ throughout the period for the 6 sites due to different human activities within each site. The Ɛ values estimated for the 4 LC types for the sites are not stable but changing from 1986 to 2013 due to changes in LC types. The results of LC classification show that K-mean method can distinguish up to 4 LC types very well in the Niger Delta.   


Keywords: Estimation, Gas-flaring, Land Cover, Mapping, Niger-Delta, emissivity