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Analysis Of The Dynamic Evolution Of Landscape Pattern In The Nansi Lake Basin In Shandong Province

Posted on:2019-06-15Degree:MasterType:Thesis
Country:ChinaCandidate:F WangFull Text:PDF
GTID:2430330548464526Subject:Cartography and Geographic Information System
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The landscape pattern is the performance of landscape heterogeneity.The dynamic changes of landscape pattern will have a certain influences on the energy flow and material cycling in eco-system,and then cause the change of eco-system structure and function.With the advance of urbanization,the construction land expanded significantly and the landscapes transformed obviously.Such changes have a profound impact on the landscape pattern and ecological environment.Nansihu lake basin of Shangdong province,as the important energy and grain production bases of Shandong province and even the whole country,its population increased significantly,economy developed rapidly,processes of industrialization and urbanization were accelerated noticeably,transportation systems became consummated step by step and the contradictions between population and land resources of the basin became increasingly prominent.All of the above changes lead to dramatic transformation of landscapes.So the thesis analyzed the characteristics,processes and driving mechanisms of landscape pattern evolution,and predicted the landscape pattern in 2047 under different simulated scenarios.This study is beneficial to understand the land-use evolution laws from the perspective of landscape pattern,and it can provide bases for land management decision,urban planning and ecological environmental protection of the basin,and can also provide references to resolve the contradiction between economic development and land-use balance.Based on landsat satellite images of 1987,2002 and 2017,other assisted datas,remote sensing and geographic information system technology,the CART decision tree classification was used to interpret the landscape datas of the Shandong Nansihu lake basin.According to the above datasets,the landscape index,dynamic change model,landscape transfer matrix,landscape gradient,logistic regression model and CLUE-S model were integrated to analyze the dynamic evolution of landscape spatial pattern from 1987 to 2017,driving mechanisms of the main landscape changes and predict the dynamic changes under different simulated scenarios in the next 30 years.Through the research,the main conclusions are as follows:(1)The landscape type of the basin was dominated by cultivated land and construction land,and the areas of the cultivated land decreased significantly,while the areas of construction land increased in the basin from 1987 to 2017,respectively.Because of the severe drought in 2002,the area of waters decreased firstly and then increased.The change of forestland was not obvious in the mass,while the grassland and unused land had a tendency to reduce.The degree of landscape fragmentation was strengthened and the distribution showed a diversified and uniform trend in the basin.(2)From the point of transfer dynamic change,the cultivated land and construction land changed significantly,which was reduced by 3011.97 km2 at 0.46% and increased by 3351.31 km2 at 3.82%,respectively.From the landscape transfer,it could be seen that the main change direction of the cultivated land reduction was the construction land,and the cultivated land with 4109.22 km2 was converted into construction land,accounting for 86.38% of the cultivated land change,and the contribution rate to the construction land was 95.24%.The dynamic degree of the waters reached 2.11%,and the sources of the increment was cultivated land and unused land.The transformational direction of the forestland and grassland was cultivated land.Dynamic calculation results,the unused land reached-2.95%.(3)The landscape evolution degree had the region differences.The central city of counties and cities showed high construction landscape gradient,with construction land gradually expanding to the surrounding areas and a large number of cultivated land was reclaimed,especially in the peripheral areas of central cities.Among them,in Mudan District of Heze,Jining Downtown and Tengzhou City,the areas of construction land and cultivated land changed more prominently.The proportion of cultivated land with high landscape gradient(80<DI?100)decreased from 67.13% to 38.96%,and the diminution of cultivated land reached 0.57 km2 to 0.99 km2 per unit area.Also,the increase in construction land reached 0.71 km2 to 0.99 km2 per unit area.The area of waters with high landscape gradient increased remarkably,with the maximum increment in unit area reached 1 km2.(4)The landscape changes were deeply influenced by the natural environment and socio-economic factors,and the latter were shown to be the dominant driving factors.During the two study periods,both the distance to cities and the distance to railways were the important driving factors.The regression coefficient of the distance to cities changed from negative number to positive number,with the model of construction land expanding changed from internal filled to external expansion.In any study period,the regression coefficient of the distance to traffic lines were negative number.It could be seen that the transport condition can promote the development of society economy and urbanization process.(5)There were significant differences in landscape evolution in different scenarios from 2017 to 2047.Under the natural development scenario,the change of cultivated and construction land would be the largest,and the forestland and grassland would have little changes.Under the ecological protection scenario,the area of grassland would increase sharply.The ecological land such as forestland,waters and grassland would have an ascending tendency.Under the situation of cultivated land protection,the rangeability of cultivated land and construction land would reduce drastically,therefore,cultivated land would get effective protection.The forestland and grassland would have a tendency to reduce.
Keywords/Search Tags:landscape pattern, dynamic evolution, driving mechanism, model analysis, Nansihu lake basin of Shandong Province
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