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Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in arid regions (especially in deserts) because of inaccurate remote sensing LST products. In this study, LST was downscaled by a random forest model between LST and multiple remote sensing indices (such as soil-adjusted vegetation index, normalized multi-band drought index, modified normalized difference water index, and normalized difference building index) in an arid region with an oasis-desert ecotone. The proposed downscaling approach, which involves the selection of remote sensing indices, was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The spatial resolution of MODIS LST was downscaled from 1 km to 500 m. Results of visual and quantitative analyses show that the distribution of downscaled LST matched that of the oasis and desert ecosystem. The lowest (approximately 22 • C) and highest temperatures (higher than 37 • C) were detected in the middle oasis and desert regions, respectively. Furthermore, the proposed approach achieves relatively satisfactory downscaling results, with coefficient of determination and root mean square error of 0.84 and 2.42 • C, respectively. The proposed approach shows higher accuracy and minimization of the MODIS LST in the desert region compared with other methods. Optimal availability occurs in the vegetated region during summer and autumn. In addition, the approach is also efficient and reliable for LST downscaling of Landsat images. Future tasks include reliable LST downscaling in challenging regions.

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Simplified reduced-order extended Kalman filter linkage due to the permanent magnets, for a surface-mounted (EKF) models for a surface-mounted permanent magnet magnet BLAC motor under both rotor position and speed brushless AC motor are developed to estimate its winding sensorless and sensored operations. The paper proposes the resistance and flux-linkage due to permanent magnets, and simplified EKF models when the winding resistance and the potentially, the stator winding and rotor magnet temperature flux-linkage due to the permanent magnets are estimated rises. Two reduced-order EKF models are presented based on independently and reports the corresponding simulation the sensorless and sensored operation of rotor position and results. speed, respectively, and the corresponding simulated results are compared. Excellent agreement is achieved between the II. EKF MODEL FOR SENSORLESS BRUSHLESS AC MOTOR estimated and actual values. The sensorless control of PM BLAC drives, in which the I. INTRODUCTION rotor position and speed are estimated mathematically instead of by discrete sensors, has recently been received ueto their h r BAn eficen prment considerable attention, since, in addition to reducing the cost magnet (PM) brushless AC (BLAC) drives are now . . ' .'employed in wide ranging applications, from high and size of drive systems, it improves the reliability. Thus, a performance servo drives to aerospace aircraft flight control significant effort has been focused on identifying the states surface actuators. The continued reduction in the price of of a BLAC drive for sensorless control. high-energy permanent magnets, in particular NdFeB, will In order to estimate the rotor speed and position, a full further accelerate the uptake of PM brushless machine order EKF model has been proposed in [1], although it is technology in variable-speed applications. However, the relatively computationally intensive. The state equation of a power density and control performance of a BLAC drive are surface-mounted magnet BLAC motor in the stationary a-,8 significantly influenced by the temperature rise. On-line reference frame is given by: estimation of the temperature rise in the stator winding and r. A u the rotor magnets is particularly important since both the la al + m sinO+a stator winding resistance and the flux-linkage due to permanent magnets are affected by the temperature rise. The r 2_ A U w m ocoso+ value of winding resistance will directly affect the accuracy L L L (1) of stator flux-linkage estimation in vector and direct torque 3 2 B T controlled drive systems, while the characteristics of NdFeB 2 (-i,X sinO+i/ cosO)-J-p L magnets deteriorate as the temperature increases and 2 excessive temperature rise may cause irreversible 0 o 0 demagnetization of magnets and thus limit the torque/power where X = [Ia 1/3 0 T is the state vector, density. l1hThe Kalman filter is an optimal recursive algorithm which u = [ua u/3lt is the input vector, y = [i ia,1/ is the can tolerate measurements errors as well as inaccuracies in m...