In view of the lack of standardized standards in the diagnosis of crop nitrogen nutrition based on UAV remote sensing to guide the data acquisition and processing in the application of drone, low-altitude UAV images with different resolutions were used to invert the nitrogen concentration of winter wheat plants. The research on the impact would provide a reference for the formulation of relevant standards and specifications in the acquisition of UAV images. To this end, a winter wheat water and nitrogen coupling experiment was conducted to obtain wheat plants with different nitrogen nutritional status. During the filling period of wheat growth, multispectral images of UAV with different resolutions were obtained by setting different flying heights of drones such as 15m, 30m, 50m and 80m, and ground experiments were conducted to collect nitrogen concentration information of winter wheat plants. Based on these data, the spectral information and texture features of the images at various resolutions were extracted, and models for inverting the nitrogen concentration of plants were established, such as spectral information, texture features, and spectral information + texture features, respectively. By comparing the estimated effects of the models in different scenarios, the results showed that when the image resolution was changed between 1.00cm and 5.69cm, the spectral information of the image had little effect on the inversion of the nitrogen concentration of the wheat plant. The difference of modeling results and verification results in each scenario was small;the effect of image texture feature on the inversion of wheat plant nitrogen concentration became worse as the image resolution was decreased;the image spectrum information + texture feature information on the inversion effect of wheat plant nitrogen concentration as a whole was increased with the increase of image resolution, and its inversion result was better than the inversion effect of a single spectral feature or a single texture feature.