Land use change has gradually developed into a core area of global environmental change research. In this paper, we use object-orientated modeling to construct a model that combines Markov models, neural networks, and cellular automata. We extend the Markov model to the traditional CA, fully utilizing the advantage of ANN in simplifying the definition of land use transformation rules and obtaining a large number of spatial variable parameters of the model. This successfully simplifies the structure of the model and the definition of transformation rules. We apply the constructed Ann-CA-Markov land use change analysis model to the evolution and prediction of land use in County A. It has been found that the proportion of arable land area in County A decreased from 23.3% to 12.1%, and the proportion of construction land increased from 28.07% to 50.87%. From 2000 to 2020, other land continued to converge into construction land in large quantities, so the land area of County A increased from 1224.73km² to 1295.15km² in 2020. The area of arable land converted out is the largest among the five types of land, with an arable land area of only 308.11km² by 2020. The probability of conversion of four land types, namely, arable land, forest land, grassland, and watershed, to construction land is 21.7%, 10.5%, 10.9%, and 9.2%, respectively, by 2030, while the probability of conversion of construction land to arable land is 21.7%, 10.5%, 10.9%, and 9.2%, respectively. The probability of converting land to cropland is 13.9%. The model constructed in this paper shows strong performance in the analysis of land use change evolution and prediction of County A, which is in line with the design expectation and makes an innovative exploration for realizing the effective simulation of spatial and temporal land use changes.

The general land use planning is to arrange all kinds of land use behaviors in an orderly manner, and its own disorder will inevitably affect the scientific and authoritative nature of the general land use planning, which makes the effect of land management unsatisfactory. The reason is that there are differences in the spatial scale of general land use planning, which makes the analysis of land information not comprehensive enough. Therefore, this paper puts forward the dynamic planning of sustainable land use based on GIS and symmetry algorithm. The collected land information is preprocessed by ArcGIS, and the land remote sensing images are classified by decision tree combined with ENVI (Visual Image Environment), using local sparse coding to extract land use features, with enhancement and reconstruction of remote sensing images using symmetric algorithm. On this basis, the factors that limit the spatial expansion of land are analyzed, and the land planning is completed by substituting them into Arc Map software. Experiments show that the average accuracy rate of this method for land planning reaches 91.22%, which can effectively complete land planning.

为了探究不同退耕还林地的土壤养分保持特征,以黄土高原丘陵沟壑区岔口流域不同退耕还林地为研究对象,对实施退耕还林后的生态林地(刺槐、柏树)、经济林地(核桃林地)土壤样品进行采集,并以坡耕地土壤样本为对照,采用单因素方差分析(one-way ANOVA)的方法进行不同样地0～ 20和20 ～ 40 cm土层养分含量的多重比较,以皮尔逊相关系数进行土壤养分间的相关分析性,并以修正的内梅罗公式对不同退耕还林样地土壤养分进行评价.结果 表明:1)岔口流域退耕还林土壤养分含量多属于中等变异,表层(0 ～20 cm)土壤的各养分含量均高于20 ～ 40 cm土层;2)不同样地土壤养分含量总体上表现为生态林＞经济林＞坡耕地;3)退耕还林样地土壤的有机质与全氮、速效氮及速效钾含量呈显著相关;4)流域生态林土壤养分综合评价为“中”,经济林为“差”.该研究显示,岔口流域退耕还林地土壤养分保持效益总体上优于坡耕地,但不同退耕还林地土壤的各养分保持特征呈现出一定的差异性,对于生态林地与经济林地的土壤养分进行综合研究,可为不同模式退耕还林地土壤生态修复提供依据.

[目的]探究山西省不同县域"三生"功能时空动态演化特征并分析其影响因素,为国土空间规划提供依据.[方法]基于山西省107个县2005,2010,2018年土地利用类型和统计数据,采用综合指数模型、动态度和空间计量模型分析其"三生"功能时空演化过程及影响因素.[结果]①2005-2018年山西省"三生"功能空间分异明显,生产、生活功能格局特征趋同,呈现出"平原高,山区低"的分布格局;生态功能分布特征与生产生活相反,空间格局稳定;"三生"综合功能提升明显,表现为"南高北低,中部高东西低"的局面.②2005-2018年生产和生态功能水平缓慢变化,呈现出先上升后下降波动变化趋势;生活功能处于快速提升阶段,提升明显;"三生"综合功能持续提高,但提升缓慢."三生"功能协调性提高,但功能单一化程度较高.③"三生"功能时空分异是自然地理环境、自然资源禀赋及社会经济因素综合作用的结果,"三生"功能受制于自然地理条件,自然资源禀赋是"三生"功能的基础和保障,社会经济因素则是"三生"功能的主要驱动力.[结论]山西省各县域需要在自然地理条件约束和经济社会转型发展背景下,促进"三生"功能各自提升与彼此协调,需要在明确各自主体功能定位的基础上,因地制宜,合理发展,依托自身区域优势与资源禀赋,构建起利益联结机制,推动山西省整体协调可持续发展.

在资源型城市城镇化过程中,要求城市内部经济与生态耦合发展.因此,研究生态视角下城市建设用地利用问题成为当前资源型城市发展亟需突破的瓶颈.基于山西省资源型城市2006—2016年面板数据,利用超效率DEA模型和Malmquist指数揭示资源型城市建设用地利用效率,并运用Tobit回归模型定量分析其影响因素.结果表明:1)山西省资源型城市建设用地利用效率整体处于中等水平,呈上升趋势;2)通过分析10个城市平均Malmquist指数,发现生产规模指数对TFP指数的促进作用更强,生产要素与规模匹配方面处于较优水平,但缺乏一定的技术创新能力;3)经济发展水平和环境质量指数是提高资源型城市建设用地利用效率的重要影响因素.

土地利用变化及生态敏感性研究已经成为当前土地研究的热点问题之一.本文以交口县为例,通过土地利用动态度、生态系统服务价值和单项生态系统服务价值对土地利用变化及生态敏感性进行分析.结果表明:2009-2013年,交口县耕地、建设用地面积持续增加;生态系统服务总价值减少16.9473×105元.在单项生态服务价值中,气体调节、气候调节、土壤形成与保护、生物多样性保护、原材料这5个单项服务价值减少,水源涵养、废物处理、食物生产、娱乐文化这4个单项服务功能价值呈现U型变化,先减后增.生态系统服务价值的敏感性指数都小于1,说明交口县的ESV对VC是缺乏弹性的,即生态系统指数的变化对生态系统服务价值的影响不大.

本文依据忻州市2000-2014年的社会经济统计资料,结合土地集约利用的内涵,采用层次分析法构建耕地集约利用评价指标体系,采用改进的熵值法确定权重,综合指数法定量计算2000-2014年耕地集约利用水平.结果表明投入强度对忻州市耕地集约利用水平影响最大,可持续利用状况对土地集约度的贡献较小;从时间上看,忻州市耕地集约利用总体呈上升趋势,这一结果为区域科学合理、持续利用耕地,保障农村经济发展提供参考依据.

Taking the 14 countries of Xinzhou City in Shanxi Province as evaluation units,this paper established evaluation index system of the agricultural land intensive utilization using analytic hierarchy process,calculated the level of agricultural land intensive utilization from 2000 to 2009 and analyzed the spatial difference using GIS technology. The result showed that the level mainly depended on high input and output into land,and sustainable utilization had little contribution to the degree of land intensity.In terms of temporal scale,the agricultural land intensive utilization becomes better and better in Xinzhou City,while the spatial scale it had big differences among the 14 counties,and the impacting factors were different in different areas.

改革开放以来,农民收入虽有增长,但与我国经济发展水平及城市居民收入水平相比,农民收入的现状不容乐观。制约农民收入增长的因素有客观的,也有农民自身主观的原因。要从多方面入手,开拓和扩展增加农民收入的途径。