| The national census of geographical national conditions is the basic national policy of China.The investigation is mainly based on the use of various surveying and mapping techniques to conduct scientific and accurate surveys on China's geographical information resources.The survey focused on nature,ecology,resources,environment,and human activities.The results of the census can be used for geographic information services in various fields.Geographical elements include many types,of which the ground vegetation is the most basic type.It is mainly used for research involving the ecological environment and resources and is a basic and important measure.The multi-source remote sensing image is used as the data in our country's geographic national survey work.In daily work,it is found that the multi-source and multi-temporal nature of remote sensing data will largely affect the quality of the estimation of the coverage of grassland with high,medium,and low coverage in the land cover classification system.At present,the method of artificial experience plus field verification is generally used to estimate and classify the coverage of the three types of grassland.However,this method is limited by human factors and data nature,which may result in problems such as low classification accuracy,low work efficiency,and long time-consuming.This paper takes Haibei Tibetan Autonomous Prefecture of Qinghai Province as the study area,based on the LandSat8 medium-resolution satellite image,calculates the inversion vegetation index,extracts the vegetation information,sets up a binary model for the remote sensing image,and combines field field sampling results to perform the grassland within a certain range.The coverage of high,medium and low coverage grassland was estimated,and the grassland category was automatically divided based on the estimation results.At the end of the experiment,the estimation results were compared with field measurement data.The results show that the... |
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