02414nas a2200289   4500000000100000008004100001653003600042653002300078653001500101653002100116653002700137653002600164653003400190653002300224653002500247653001700272653002100289653002500310100001100335700001700346700001600363245015500379856014700534490000900681520141400690022002002104                                       d10aClassification (of information)10aCloud technologies10aExtraction10ahuman activities10aInformation protection10aInformation recording10aIntangible cultural heritages10aInternet of things10aNatural environments10aPoint-clouds10aRural landscapes10aSpatial informations1 aLi Yue1 aZhang Yadong1 aChen Jinjin00aResearch on Rural Landscape Spatial Information Recording and Protection Based on 3D Point Cloud Technology under the Background of Internet of Things  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85131850595&doi=10.1155%2f2022%2f3772108&partnerID=40&md5=ed41ae9e4aabbd41b85539c31f0638e30 v20223 aThe village with historical and cultural accumulation not only is the witness of the interaction between human activities and natural environment but also contains a lot of intangible cultural heritage. It is an important research object in the history of human social development and has great reference value for the construction of modern Humayun settlements. With the continuous change of modern rural landscape, the traditional engineering drawing cannot meet the needs of people for spatial information measurement. There are some problems such as slow drawing, low precision, and poor benefit, so computer drawing must be used. Therefore, this paper puts forward the research on rural landscape spatial information recording and protection based on 3D point cloud technology under the background of Internet of Things and realizes the recording of rural landscape spatial information through the construction of 3D point cloud spatial information recording model. The experimental results show that the improved unit point cloud spatial information recording model has better feature extraction effect and feature point extraction efficiency, and can classify the point cloud more carefully. At the same time, the scene 3D point cloud classification method based on conditional random field can better deal with the interference factors in the outdoor landscape and show a better classification effect.  a16875265 (ISSN)