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Research On Land Change Intensity Detection Method Based On Random And Systematic Change Characteristics

Posted on:2022-10-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:H M DuanFull Text:PDF
GTID:1481306725954009Subject:Geography
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Land change,especially land use and land cover change,is an important content of global and regional environmental changes,and it is the most direct manifestation of the impact of human activities on earth's surface environment,so it is also an important foundation and basic way to explore global and regional environmental issues.The intensity of change is one of the most important characteristics of land change.The intense changes could indicate the dominant signals of regional land change,and detecting the intensity of land change is helpful to explore the causes and driving factors of changes.At present,the public release of a large number of land use/land cover products provides favorable conditions for land change research,and also puts forward higher requirements for the intensity detection methods of land change.However,with the deepening of research,the existing methods and models have been found to have varying degrees of shortcomings and deficiencies,including the failure to fully consider the proportion of changes,the expansion and loss of category changes,and the joint analysis of multi-level change characteristics.These problems often make it difficult for existing methods to meet the needs of accurate research of land change.Based on the analysis of random and systematic changes characteristics,this thesis established a two-level analysis framework including transition level and category level to achieve effective detection of the intensity of land change.In this thesis,taking the Mu Us area as a case area,the intensity of land use change during 2000-2015 area were detected and the driving factors and causes of the change was analyzed,so as to test the detection ability of the new method and explain and verify the indicative significance of the intensity of land change.The main research contents and results are as follows:(1)Sorted out the basic steps of detecting the random and systematic characteristics of land change at the transition level;clarified the mathematical meanings of random change and systematic change,determined the correspondence between this two changes and the intensities of change;deduced the indicative significances of the random and systematic characteristics to the driving factors and causes of land change.By analyzing the formula of the random expected value of land transition area,this paper confirmed the physical meanings of the random change and the systematic change at the transition level,as well as the correspondence between these changes and intensities.The random change is a change in which the change proportion is at an average level,and its intensity is at a moderate level.The systematic change and the systematically suppressed change correspond to changes in the proportion of changes above and below the average level,respectively,and also to relatively intense and relatively dormant changes,respectively.The results of the application in the Mu Us area showed that the most systematic transitions indicated the most intense signals of regional land change,which reflected the main characteristics of the regional land change.(2)Provied a method for analyzing random and systematic characteristics of land change at the category level.The basic steps of this method include calculating the random expected values of the gross change area of a land category(including gross gain and gross loss),measuring the deviation of the actual change area from the expected area,identifying random and systematic changes based on a threshold method,and analyzing and explaining the characteristics of the changes.This method could detect the change intensity of a land category from the directions of gain and loss,respectively.The systematic change and the suppressed change correspond to relatively intense change and relatively dormant change,respectively.This new method was used to extract the land change characteristics in the Mu Us area.In the application results,the intensity of gain and loss of the main land categories were reasonably explained,which comfirmed the effectiveness of the method.(3)Established the relationship of random and systematic change characteristics between the category level and the transition level;on this basis,constructed a set of two-level analysis framework for detecting the intensity of land change.This technical framework could realize the decomposition of change characteristics of category level to the transition level and the transfer of change characteristics of transition level to the category level;the intensity of land changes and their indicative significances could also be transferred between levels accordingly.Based on the inter-level joint analysis of the two-level analysis framework,the indicative significances of the intensity characteristics of land change could become more clear,and the exploration of the driving factors and causes of the change could be more targeted.The main creative contributions of this research are as follows:(1)Clarified the mathematical meanings of random change and systematic change in land change,and their corresponding relationship with the intensity of change.Random changes are changes with average intensity,systematic changes are relatively intense changes,and suppressed changes are no intense changes.(2)Provied a method for analyzing random and systematic characteristics of land change at the category level.This method could detect the change intensity of land category from the directions of gain and loss,respectively,which is conducive to more accurately exploring the driving factors and causes of land change.(3)Constructed a set of two-level analysis framework including the category level and transition level,which could more comprehensively and effectively detect the intensity of land change and meet the needs of different levels of analysis.
Keywords/Search Tags:Land change, LUCC, Change intensity, Random change, Systematic change, driving factor, Mu Us area
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