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赣南生态屏障区林地时空变化分情景模拟
引用本文:杨丽,傅春. 赣南生态屏障区林地时空变化分情景模拟[J]. 地理科学, 2018, 38(3): 457-463. DOI: 10.13249/j.cnki.sgs.2018.03.016
作者姓名:杨丽  傅春
作者单位:1. 南昌大学理学院,江西 南昌 330031
2.南昌大学管理学院,江西 南昌 330031
基金项目:教育部重点人文社科重点课题(15JJD790040)、江西省教育厅一般科学技术研究项目(150173)资助;Project of Key Research Base for Humanities and Social Sciences in Ministry of Education (15JJD790040), Science and Technology Project Founded by the Education Department of Jiangxi Province (150173).
摘    要:基于2000年和2010年土地利用遥感数据,从自然、区位、交通、人口和经济4个角度选取驱动因子,利用Logistic-CA-Markov土地利用综合模型预测赣南森林有林地、灌木林、疏林地和其它林地4种林地类型在当前模式、规划模式和保护模式3种情景下的空间演变格局。结果表明:到2020年,在当前模式和规划模式,林地总面积将减少,在保护模式则出现增加,3种情景都体现出有林地和其它林地增加、疏林地和灌木林缩减的趋势,只是增减幅度不同,但不论何种情形林地的组成结构都将发生较大程度的变化; 3种情景都是以疏林地→有林地、有林地→其它林地和灌木林→有林地这3种类型的转化为主,向有林地的转化分布都比较分散,而向其它林地的转化却集中在安远、信丰、于都、赣县四县交界处; 相较于当前模式,在规划模式下集中在安远县及其周边的有林地向其它林地的转化出现大量缩减,在保护模式下这种缩减更加明显。

关 键 词:CA-Markov  逻辑回归  空间格局  林地  赣南  
收稿时间:2017-03-07
修稿时间:2017-05-26

Spatio-temporal Simulation of Gannan Ecological Barrier Under Different Scenarios
Li Yang,Chun Fu. Spatio-temporal Simulation of Gannan Ecological Barrier Under Different Scenarios[J]. Scientia Geographica Sinica, 2018, 38(3): 457-463. DOI: 10.13249/j.cnki.sgs.2018.03.016
Authors:Li Yang  Chun Fu
Affiliation:1.School of Sciences, Nanchang University, Nanchang 330031, Jiagnxi,China
2. Management Department, Nanchang University, Nanchang 330031, Jiangxi, China
Abstract:Gannan forest is an important safety barrier in southeast China. It belongs to Nanling Mountain forest and biodiversity reserve of China. To analyze the evolution trend of Gannan forest, driving factors is chosen from the perspectives of natural, geographic, geographic traffic and economic and a Logistic-CA-Markov model is constructed based on land use of the year 2000 and 2010. According to the development status and existing issues in Gannan, three scenes are set to predict the spatial transfer pattern of closed forest land, shrubbery, open forest land and other forest land, which are current pattern, land use planning and forest protecting. The results show that: 1) Key driving forces for forest land use change are human activities, society and economy. Location and environment variables are secondary causes. For the change of closed forest land, shrubbery and other forest land, GDP and population are key explaining variables. For open forest land, the key driving force of its change is gradients. 2) In 2020, the area of total forest land will decrease under current trend scenario and land use planning scenario, while under forest protecting scenario there is an augment. No matter in which scenario, the increase of closed forest land and other forest land and the decline of open forest land and shrubbery are obvious, and the construction of forest land will definitely change a lot. 3) The main transfer trend in 3 scenarios are open forest land to closed forest land, closed forest land to other forest land and shrubbery to closed forest land. The transfer to closed forest land is dispersedly distributed, while the transfer to other forest land is concentrated in Anyuan County and its circum. 4) Compared to current trend scenario, the transfer from closed forest land use to other forest land will have a big shrinkage in land use planning scenario and the shrinkage will be lager in forest protecting scenario. In all, on one hand, the natural forest and planted forest of high canopy density is in a recovery increase, which shows that policies and regulation to protect forest resource has achieved initial success. On the other hand, with the development of urbanization and economic construction, the social and economic factors are posing greater influence to forest. The economy rise will accelerate forest land expansion structural adjustment of agriculture mobilized by forestry and fruit growing leads to rapid expansion of economic forest. But the farmland and construction land will erode the forest land in unavoidable way under urbanization background. The contradiction between forestry development and peasant’s life demand is becoming obvious.
Keywords:CA-Markov  Logistic Regression  spatial pattern  forest land  Gannan  
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