scholarly journals A Method for Geostationary Satellite Time-Series Thermal Infrared Data Simulation

2021 ◽  
Author(s):  
qian yonggang ◽  
kun li ◽  
Weiyuan Yao ◽  
Wan Li ◽  
Shi Qiu ◽  
...  
Keyword(s):  
Time Series ◽  
Thermal Infrared ◽  
Geostationary Satellite ◽  
Data Simulation ◽  
Infrared Data

The Time-series Mid-Infrared Data Simulation for High-temporal Resolution Geostationary Satellite

2020 ◽  
Author(s):  
Kun Li ◽  
Yonggang Qian ◽  
Ning Wang ◽  
Lingling Ma ◽  
Shi Qiu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Surface ◽  
Geostationary Satellite ◽  
High Temporal Resolution ◽  
Atmospheric Parameters ◽  
Data Simulation ◽  
Mid Infrared ◽  
Directional Emissivity ◽  
Infrared Data

<p>Geostationary remote sensing satellite can provide time-series mid-infrared (MIR) data at regional scale, which plays a significant role in many applications such as environmental monitoring, fire detection and temporal change of surface parameters. Therefore more geostationary remote sensing satellite missions for earth observation are carried out and focused on directional and high-temporal resolution. Given the complex nature of the data to be expected from these missions, it is essential for a thorough preparation, which can be accomplished by simulating the image data before the actual launch. The simulation can include the top-of-atmosphere (TOA) radiance data as well as all major process parameters such as land surface temperature/emissivity and atmospheric parameters. It can be used to evaluate the capabilities of target satellite observing the earth and optimize the system according to the further analysis. In addition, the development of the data simulation will provide a considerable support for the algorithms of quantitative application.</p><p>This work addressed a method for simulating the time-series mid-infrared data of geostationary satellite based on radiative transfer model. The simulation procedure, including directional emissivity, time-series LST, time-series atmospheric parameter, sensor performance, can be shown as follows. Firstly, an empirical Bidirectional Reflectance Distribution Function (BRDF) model, i.e., the Minnaert’s model, is introduced to describe the non-Lambertian reflective behavior of land surface. Then, the directional emissivity can be calculated based on the Kirchhoff’s law with the John Hopkins University (JHU) Spectral Library as the prior knowledge. Secondly, a semi-empirical Diurnal Temperature Cycle (DTC) model with six parameters (Göttsche, F. M., and Olesen, F. S., 2001) is used to simulate the time-series LST with the interval of 15min. Thirdly, the atmospheric profiles of pressure, temperature, relative humidity (RH), and geo-potential (GP) at 0.5° latitude/longitude spatial resolutions for 8 UTC times per day provided by European Centre for Medium-Range Weather Forecasts (ECMWF) are used for atmospheric parameters. A temporal interpolation method is proposed to obtain the time-series atmospheric parameters from the ECMWF 3-hour profile. Then, the MIR spectral radiance at the top of atmosphere can be simulated by MIR radiative transfer equation with the aid of MODTRAN 5 code. Finally, by convoluting the sensor’s spectral response function, the radiance received by the sensor can be got against the instrument noise. The results show that the time-series mid-infrared data for geostationary satellite of different surface types at any angle can be well simulated using the proposed method. More comparative analysis with the geostationary satellites, such as METEOSAT, GEOS, FENGYUN, GMS etc., will be done in the future work.</p>

scholarly journals Retrieval of Surface Temperature and Emissivity From Ground-Based Time-Series Thermal Infrared Data

2020 ◽  
Vol 13 ◽  
pp. 284-292
Author(s):  
Yonggang Qian ◽  
Ning Wang ◽  
Kun Li ◽  
Hua Wu ◽  
Sibo Duan ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Thermal Infrared ◽  
Infrared Data

Land surface temperature and emissivity retrieval from time-series thermal infrared data

2019 ◽  
Author(s):  
Yonggang Qian ◽  
Ning Wang ◽  
Yaokai Liu ◽  
Kun Li ◽  
Caixia Gao ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Infrared Data

scholarly journals Assessment of Urban Heat Island Patterns in Bangkok Metropolitan Area Using Time-Series of LANDSAT Thermal Infrared Data

2019 ◽  
Vol 17 (4) ◽  
pp. 87-102 ◽  
Author(s):  
Warisara Sanecharoen ◽  
◽  
Kanchana Nakhapakorn ◽  
Aeumphorn Mutchimwong ◽  
Supet Jirakajohnkool ◽  
...  
Keyword(s):  
Time Series ◽  
Urban Heat Island ◽  
Metropolitan Area ◽  
Thermal Infrared ◽  
Heat Island ◽  
Urban Heat ◽  
Infrared Data
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