A comparative estimate of air temperature from modis land surface temperatures in Ghana

被引:1
|
作者
Frimpong, Adubofour [1 ]
Forkuo, Eric Kwabena [2 ]
Osei, Edward Matthew [2 ]
机构
[1] Koforidua Tech Univ, Dept Civil Engn, Koforidua, Ghana
[2] Kwame Nkrumah Univ Sci & Technol, Fac Civil & Geo Engn, Dept Geomatic Engn, Kumasi, Ghana
来源
COGENT ENGINEERING | 2023年 / 10卷 / 01期
基金
美国国家航空航天局;
关键词
MODIS; Land Surface Temperature products (LSTs); Air Temperature (Tair); regression statistics; validation; statistical indices; Coefficient of Variation(CV);
D O I
10.1080/23311916.2023.2216047
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study is aimed at establishing a comparative estimate of air temperature (Tair) from Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) between 1 km and 6 km spatial resolutions and to investigate and quantify spatial variability of LST-Tair relationships. The test area is Republic of Ghana located in the sub-region of West Africa. The purpose of the research is to establish an optimal performance of Tair between two spatial resolutions. Arithmetic Mean method was employed for computation of the datasets. Seventy (70) pairs of composite LSTs consisting of Terra and Aqua MODIS observations which correspond to 70 meteorological stations were used. Due to problem of missing data and outliers, 277 pairs of LST data points per resolution were used. Application of Regression Analyses revealed a good direct correlation existing between values of Tair and LSTs in 1 km with coefficient of determination, R-2 = 0.8124 while, 6 Km resolution recorded R-2 = 0.8031. Hence, MODIS LST in 1 km is a better estimator of air temperature in Linear Regression study. Statistical indices of 1 km procedure were found to be lower than the 6 km procedure. The 1 km resolution registered a Root Mean Square Error (RMSE) of 1.97 degrees C, Standard Error of regression, 1.14 degrees C and Coefficient of Variation, CV of 10.19%. Meanwhile, 6 km resolution yielded a RMSE of 2.13 degrees C, Standard Error of regression, 1.22 degrees C and CV of 10.68% respectively. Therefore, 1 km resolution datasets show better accuracy and performance of air temperature estimation than 6 km data products. Hence, a good result would be achieved when 1 km datasets are processed.
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页数:21
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