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tom 28
76-86
EN
This study is the regional mapping of Land Surface temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of south-south coastal settlements of Rivers State in Nigeria. The Google Earth Engine (GEE) of satellite remote sensing origin was used in the study. It was observed that land surface area of the south-south coastal settlements of the region hosting a total population of 3,344,706 persons had undergone severe modification and alteration of vegetal cover by increased human activities especially in the central area. Emissivity in the region increased from the center to the rural settlements with values ranging 0.98 to 0.99 and difference of 0.01 indicating that there was increased modification of the regional land surface. Land surface temperature decreased from the regional center to the rural settlements ranging between 22.12 ºC to 35.99 ºC with a difference of 13.87 ºC. However, LST was scattered in different settlement spots especially in the northern region such as Aleto, Finema (south); Rumuolu, Odogwa, Abara, Umuechem, Rumuola, Ambroda (north) among others. The normalized vegetation index showed -0.54358 to 0.409327 having the difference of 0.952907 indicating greater variation in vegetal cover across the region. Thus, NDVI in the region increased from the regional center to the outskirts of the area. Urbanization in the south-south region of Rivers State had extended severely to the rural settlements. Therefore, it is recommended that policy makers and regional planners should protect the area from adverse vegetal lost and heat effects by implementing regional greening practices.
EN
Land surface emissivity retrieval is important for the remote identifcation of natural materials and can be used to identify the presence of silicate minerals. However, its estimation from passive sensors involves an undetermined function related to radiance data, which is infuenced by the atmosphere. We tested three methods for temperature emissivity retrieval in a dune feld composed of 99.53% quartz (SiO2) using Advanced Spaceborne Thermal Emission and Refection Radiometer (ASTER) imagery. The tested methods were the reference channel method (RCM), emissivity normalization method (ENM), and temperature emissivity separation (TES) method. An average quartz reference spectrum for the dune samples was calculated from an emissivity database based on temperature and used to evaluate the emissivity products of four ASTER images. In general, the three tested methods had a good approximation when analysed the emissivity reference curve, especially for longer wavelengths that ranged between 2 and 4% of emissivity. The RCM and ENM produced very similar results with the coefcients of determination (R2 ) as 0.9960 (RMSE 0.0184) and 0.9959 (RMSE 0.0185), respectively. RCM method presented superior results (R2 : 0.9960, RMSE: 0.0184), compared to the TES method (R2 : 0.9947, RMSE: 0.0197). The TES method showed good results only for shorter wavelengths and, hence, to identify specifc targets using ASTER data, such as silicate minerals, it is better to use the RCM method. The emissivity value selected at the saturation point of the spectral library based on temperature is fundamental in acquiring more reliable data.
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