Land Surface Temperature Dataset of Typical Stations in Middle Reaches of Heihe River Basin Based on UAV Remote Sensing(2020,V1)

Land Surface temperature is one of the important parameters of surface energy balance. This dataset is the monthly land surface temperature data of typical stations in Heihe River Basin from June to October in 2020; In flight, DJI M600 Pro UAV was equipped with the WIRIS Pro sc thermal imager. taking SD station in the wetland, DM station in the oasis and Hz station in the desert as the center, the land surface temperature was observed, and the surface brightness temperature image was obtained. The flying height of the UAV was about 300m, the pixel of the thermal imager was 336x256, and the spatial resolution of the image was 0.4m. The surface temperature retrieval algorithm is an improved single channel algorithm, which is applied to the surface brightness temperature data obtained by UAV thermal imager, and finally the land surface temperature data with 0.4 m spatial resolution is obtained.

0 2021-05-31

HiWATER: Simultaneous observation dataset of land surface temperature in the lower of Heihe River Basin on Aug. 01, 2014

The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature for different kinds of underlying surface, including the lager areas of homogeneous vegetation with high coverage, water, and concrete floor, while the thermal imager go into the experimental areas of the low reaches. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal imager and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the plausibility checks of the surface temperature product from remote sensing. 1. Observation time On 1 August, 2014 2. Observation samples Three field samples were chosen in the fly zone, which were large areas of homogeneous vegetation (with high coverage), water, and concrete floor. 3. Observation method Surface temperature values were observed continuously for each sample using handheld infrared thermometers during the imager went into the flying area. 4. Instrument parameters and calibration The field of view of the handheld infrared thermometer is one degree and the emissivity was assumed to be 0.95. All instruments were calibrated on 31 July, 2014 using a black body. 5. Data storage All the observation data were stored in an excel.

0 2019-09-15

WATER: Dataset of airborne L-band microwave radiometer and thermal imager mission in the Binggou-A'rou flight zone in the afternoon of Apr. 1, 2008

The dataset of airborne L-band microwave radiometer and thermal imager mission was obtained in the Binggou-A'rou flight zone in the afternoon of Apr. 1, 2008. The frequency of L bands was 1.4 GHz with back sight of 35 degree and dual polarization (H&V) was acquired. The plane took off at Zhangye airport at 12:48 (BJT) and landed at 16:35 along the scheduled lines at the altitude about 5000m and speed about 260km/hr.. The raw data include microwave radiometer (L) data, thermal imager data (7.5-13 um; FOV: 24×18º) and GPS data; the first were instantaneous non-imaging observation recorded in text, which could be converted into brightness temperatures according to the caliberation coefficients (filed with raw data together), and the third are aircraft longitude, latitude and attitude. Moreover, based on the respective real-time clock log, observations by the microwave radiometer and GPS can be integrated to offer coordinates matching for the former. Yaw, flip, and pitch motions of aircraft were ignored due to the low resolution of microwave radiometer observations. Observation information can also be rasterized, as required, after calibration and coordinates matching. L band resolution (x) and footprint can be approximately estimated as x=0.3H (H is relative flight height). The thermal imager was 320*240 pixels and with FOV of 24×18º. The thermal imager data were stored in binary format with a text header file. The recorded value was brightness temperature at sensor with scale and gain parameter recorded in the header file. And the thermal images were not geometrically corrected because there were gaps between sequential images.

0 2019-05-23