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Monitoring Of The Change Of JINPU District Land Use Based On Object-oriented Classification

Posted on:2017-07-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y J WangFull Text:PDF
GTID:2370330548983757Subject:Geodesy and Survey Engineering
Abstract/Summary:PDF Full Text Request
In recent years,with the overall development of China's economy,the various regions of the country are in development and change.Large scale urban expansion,as well as changes in the land policy of the national forest land,to the surface topography has brought a lot of changes.A comprehensive grasp of the current situation of land use is of great benefit to any region.At the same time it is a convenient,efficient and scientific to monitor the real time and dynamic of the land in a large area.Remote sensing technology has shown its advantage in this area.However,the choice of a high reliability,the effect of the ideal image interpretation and data extraction methods for the majority of remote sensing workers have put forward a challenge.Based on the remote sensing technology,the paper studies the land use and the change of the land use in the area of the foundation of the new area.The main research contents are as follows:(1)The object-oriented classification method of high resolution remote sensing image is selected to classify the remote sensing image of the new area in 2013.Firstly,the edge segmentation algorithm is used to achieve the segmentation of image,and the scientific classification system is constructed according to the feature of the feature.(2)Utilized census data of geographical conditions of the JINPU District in 2015,and combined it with the land use status of JINPU District in 2013.Fulfilled the land use comparative analysis of JINPU District after its establishment.(3)Calculated the land use transfer matrix of land use results obtained by the classification of the 2013 and the 2015 national census data of the monitoring area.By using the transfer matrix of land use,the change of the land and the transfer of the new district are analyzed.
Keywords/Search Tags:Change monitoring, Image classification, JINPU District, RS, Geographiccal conditions consus
PDF Full Text Request
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