Evaluation of rural landscape is the foundation of rural landscape planning. In order to better understand the influencing factors on rural landscape visual environment, the research uses VR panorama technology in the field of landscape architecture for the first time. VR panorama technology could record and simulate scene and space much better than traditional ways. Therefore, this paper uses VR panorama technology, taking the city young people as example, and then the original data was obtained in visual preference by doing the experiment in watching VR panorama. In this way, we improved the traditional SBE method and studied the rural landscape visual assessment and landscape element preference. Firstly, the visual evaluation model of rural landscape was constructed by using SBE method and SD method, and 4 significant indexes were identified as follows: architecture texture, plant species, road shape and hygiene status. Then according to the VR panorama, we made interviewers shoot at their prefer view, and then based on these preference pictures, we extracted 9 landscape preferences. By using linear regression method, we established model of the relationship among preference probability of the nine landscape indexes, the value of index, and SBE value of the scene to test whether there was a functional relationship among the three variables. Then we got the results: preference probability of architecture characteristics and the water quality only had significant relationship with their own value; the preference probability of architecture texture and farmland texture were impacted by their value and the scene SBE value; the preference probability of nature vision and other visual focus were influenced by scene SBE value; road shape, road materials and plant species preference probability had no significant relationship with either its own fractional values or the scene SBE value. Finally, the reasons for this preference were analyzed, and hope it will play a guiding role in the construction of rural landscape in the future.