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Study On Land Use Pattern Forecast And Carbon Storage Value In Xi'an City

Posted on:2015-04-10Degree:MasterType:Thesis
Country:ChinaCandidate:M X JingFull Text:PDF
GTID:2279330434451485Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
Global climate change caused by the elevated levels of carbon dioxide. The carbon dioxide content increased global climate change has caused the human concern. Carbon balance plays an important role in ecological processes. The current study focuses on the changes in ecosystem carbon storage caused by land use change.Based on remote sensing data and meteorological data, and by means of the CA-Markov module in IDRISI and In VEST module in ArcGIS, this article took Xi’an as survey region, to study the effects that the change of land utilization on the carbon storage of ecosystem and assess its value. Firstly, this research analyzed the spatial-temporal variation characteristics of land utilization from2000to2010in Xi’an, and then simulated and predicted the pattern of the utilization of land in2015-2020in Xi’an under three scenarios. Secondly, the carbon storage of ecosystem from2000to2010and from2015to2020in Xi’an were estimate and predicted by assessment software of ecosystem service function combining of ground biomass and soil carbon density. Finally,this paper also analyzed the NPV of carbon from2000to2020in Xi’an under different scenarios.The main contents and conclusions are as follows:(1)Analysis of the characteristics of land use change. Xi’an land utilization remain show a stable structure from2000to2010, it mainly to cultivated land, forest land and grassland. And the area of cultivated land was the largest, then the woodland, grassland, construction land area, waters and the unused land, respectively. In ten years, cultivated land area and grassland area show a downward trend. But, Construction land area continued to increase. Woodland area showed a fluctuation, while waters in a constant increase. Unused land has no obvious changes. Spatially, taking the Xi’an urban area as the center, it was the place of dense buildings and the counties with the distribution of settlements around it. In the north, it has rich water resources with Yellow River and Wei River tributaries. In the south, it mainly distributed woodland and grassland which were close to Qinling Mountains. In10years, the land use types are converted to each other. The most obvious change is cultivated land and grassland turned into construction land.(2) Simulation and prediction results by the CA-Markov module. The results show that CA-Markov model is suitable for short-term land use pattern modeling and prediction with high accuracy of the model simulation. This article assumes three kinds of Xi’an land use scenarios for,2010-2020. Scenario1:passage of the status quo. Scenario2:protection policy. Scenario3:mandatory protection.(4) Estimation of carbon storage under different scenarios from2000to2020. The results show that carbon storage in Xi’an showed a downward trend from2000to2010.Based on the hypothesis that simulation scenario, amount of carbon and carbon sequestration scenario3is the highest, scenario2in the middle and scenario1is the worst.(6) Analysis carbon net present value under different scenarios from2000to2020. Under the same condition, NPVshows the tendency of decline.under the same price, The higher the discount rate, the higher the NPV.under the same price,The higher the NPV, the higher the discount rate. Based on the hypothesis that simulation scenario, analysis NPV of carbon scenario3is the highest, scenario2in the middle and scenario1is the least.The outstanding feature of this article is based on the analysis of scenarios, setting up different scenarios to predict the future under different land use development in Xi’an, and to assess the ecological value of carbon storage system under different scenarios from2000to2020, but also analyzes the different prices different discount rates, a10years carbon under different scenarios of future net present value.
Keywords/Search Tags:land use, dynamic simulation, CA-Markov model, InVEST model, NPV
PDF Full Text Request
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