## 3 Results  
### Hyperspectral and Thermal Imagery  
We obtained orthomosaic Cubert hyperspectral images of 4.5 mm resolution in this field campaign. Figure 2a shows an example of a false-color composite image taken on  
Figure 2: (**a**) False-color composite image from Cubert hyperspectral camera band 104, 29, and 12. Red color denotes vegetation and blue color bare soil. (**b**) Comparison of rice canopy reflectance measured by ASD spectroradiometer and Cubert camera after the empirical line correction using (**c**) reflectance of dark soil object, and (**d**) reflectance of bright metal box object (black line) in four days measurement (colored lines).  
14 November 2018. Individual rice leaf blades are visible. Figure 2b shows the comparison of hyperspectral reflectance curves measured by Cubert camera (after the empirical line correction) and ASD spectroradiometer on rice canopy. The two curves share a similar spectra pattern and show the reliability of UAV-based hyperspectral sensing in the campaign. Note that the last few bands of Cubert camera have large variations and were discarded from further analysis following the manufacturer's recommendation. In four days of measurements, the assumed static dark soil and white metal box objects had up to 30% deviations from day to day (Figure 2c,d), indicating the necessity for correcting the systematic day-to-day reflectance drift to obtain comparable results from the hyperspectral camera. The PRO4 SAIL model using normalized hyperspectral reflectance resulted in an average high R\({}^{2}\) of 0.96 and a low root-mean-squared-difference of 0.02 between the UAV-measured and the Pro4 SAIL-modeled hyperspectral reflectance (Supplementary Figure S2).  
The land surface radiometric temperature (LST) map (Figure 3) shows warmer bare soil and cooler green rice canopy during the local noontime flight on 16 November 2018, matching well with the land covers in Figure 2 false-color image. The air temperature was 26.7 \({}^{\circ}\)C at the flight time and 99% of the LST in the area was within 29.1 to 42.4 \({}^{\circ}\)C. The LST histogram of the whole area was bimodal, with two peak temperatures at 31.6 and 36.5 \({}^{\circ}\)C, corresponding to vegetation and bare soil respectively. The LST histogram of rice plots showed only one peak at 30.9 \({}^{\circ}\)C. Since all the parameters in the PRO4 SAIL model were set for the rice canopy, the output LAI and subsequently estimations of albedo and emissivity may not fit other vegetation types in the research area. Therefore, to avoid possible large errors, we only analyzed and presented the results of rice plots in the following sections.  
Combining the temperature and hyperspectral reflectance from UAV, and the auxiliary data from ground measurements, including weather station data, leaf water content, concentrations of leaf nutrients and soil total nitrogen, and soil water retention curve, we mmapped soil moisture content, soil matric potential, leaf and canopy properties, and energy components over the three experimental groups. The average changes of key variables after biochar application are summarized in Table 1. Detailed information is given in Supplementary Table S1.  
Figure 3: Land surface temperature (LST, 2.25 cm resolution) at 12:30 on 16 November 2018 estimated from the FLIR tau2 thermal camera and the Cubert-derived land surface emissivity. The yellow color indicates hot pixels and the dark color cool pixels.