Drought affects food security and social production and life seriously, so it’s crucial to obtain drought information timely. This paper conducted a comparative study of drought indices in Xinjiang. We used MOD13A2 and MOD11A2 to calculate AVI and TVDI, used daily precipitation and temperature data from 41 meteorological stations to calculate PDSI, compared their ability and analyzed their consistency, finally. The results showed that: (1) The average value of AVI and TVDI was consistent on inter-annual drought response and the correlation reached -0.54. (2) AVI responded poorly at the early stage of vegetation growth; TVDI responded poorly to drought events in the northern Xinjiang; and remote sensing indices possessed lag; PDSI responded to drought events not only in terms of magnitude of values, but also in terms of dynamic decline of values. (3) AVI-TVDI spatial correlation was poor; TVDI lag I / II -PDSI correlation was -0.28 and -0.31 in drought years, the consistency in the eastern part was larger than the western part, the northern part was larger than the southern part. The consistency of AVI-PDSI was poorer than TVDI-PDSI. The results aimed to provide help for drought assessment and new ideas to enrich the means of drought monitoring in Xinjiang.
In the agriculture sector, multispectral camera near-ground observations are currently in demand. Altum multispectral camera is a new type of agricultural multispectral camera, which can be installed on ground observation equipment to obtain near-ground remote sensing images with high resolution and multispectral information. However, the optical system of the Altum camera adopts a multi-lens beam splitting design, and the channel registration problem used near-ground remains to be solved. Therefore, a near-ground image registration method is proposed based on a combination of a channel transformation model and a mapping relationship of the homologous image points. The way first corrects the internal lens parameters using the distortion coefficient of each lens. It then constructs a channel transformation model in the pixel coordinate system based on the transformation relationship between the camera coordinate system and the pixel coordinate system. The following calculates the transformation parameters from the corrected internal parameters and the relative position parameters between the lenses to complete the channel transformation. Finally, the homography model is estimated according to the mapping relationship of the homologous image points to perform inter-channel fine registration. The results show that the error in each band after registration is less than 0.5 pixels when the observation distance is greater than 7 metres. The method can offer a pre-processing service for channel registration for the Altum multispectral camera near-ground applications.
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