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Land Cover Monitoring In Nanjian County Based On RS And

Posted on:2017-04-02Degree:MasterType:Thesis
Country:ChinaCandidate:S O ZuoFull Text:PDF
GTID:2270330503473312Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
With the development of global environmental change, the demand of land use change monitoring in our city is increasing. The foreign satellite data of low resolution pixels, land coverclassification accuracy is not high. The previous object oriented land use information extractions are usually confined to some experimental area as a research exmaple, land use remote sensing information extraction based on the basic administrative unit is not studied yet withengineering application.Aiming at thelimitations of previous research, this study mainly selects Nanjian county administrative area as the study area, explores the land cover information extraction methods of object-oriented, combines the foreign satellite data withdomestic satellite data(2000 ETM + and 2014 GF-1) and applies the method in the land cover change information extraction further.The study has mainly achieved the following results:(1)With ETM + and GF-1 satellite remote sensing data of Nanjian county,the tools of ESP algorithm, the factors of the object-oriented classification methodsuch as the optimal segmentation scale and shape, firmness are obtained byexperiments. That is, the optimal segmentation scale for ETM+ is 20, and the optimal segmentation scale for GF-1 data is 40, the shape factor and firmness factor parameters are 0.4 and 0.6 respectively.(2)Withthe Nanjian county land cover investigationdata of 2000 and 2014, the land cover classification results of object-oriented accuracy are verified. The overall accuracy of GF-1 classification results is 88.1293%, and Kappa coefficient is 0.8469. Whereas, the overall accuracy of the ETM+ image classification results is 77.0385%, and Kappa coefficient is 0.6925. By this way,the study further confirms the GF-1 land cover classification has high acuuracy than the ETM+data. Therefore, the object-oriented classification method of GF–1 for the county is setted up,which was more practical as well.(3)Analyzingon the information on the dynamic change of land cover in Nanjian county from 2000 to 2014, the results indicated that land cover types ofNajian county in 2000 and 2014 are mainly forestland, which are 46.36% and 57.71% of the entire study area respectively. The grassland, cultivated land and construction land and unused land are less. The water is more less. As far as the changes of landcover types of Nanjian county from2000 to 2014 are concerned, the forest land has the biggest gains of 11.35%,unused land has the largest decline of 11.95%, other land types have less change. The land cover degree comprehensive index increased from 211 to 225.91,at an annual increasing rate of 1.065% from2000 to2014.The unused land rolled out significantly, whereas the forest land has least roll-out transformation. The water rolled in significantly, whereas the farmland has lest roll-in transformation.With the analysis of the data of Najian county land cover changes from2000 to 2014,the problems of Nanjian county are summarized as listed:the construction of land types are not resonable, and the land use level is not high, etc. ThenthesuggestionsforNanjian county land planning are put forward:The development of economic forest industry should be foucused and more protecting efforts need to do in arable land,the policy of returning farmland to forest and grass land use planning need to push as well.
Keywords/Search Tags:Land cover dynamic change, Object-oriented classification, Information extraction, Multi-scale segmentation technology, Nanjian
PDF Full Text Request
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