田超, 杨金泽, 石博安, 张杰, 邱瑞, 王观湧, 陈亚恒. 怀来县土地利用格局的影响因子分析[J]. 中国生态农业学报(中英文), 2016, 24(7): 957-968.
引用本文: 田超, 杨金泽, 石博安, 张杰, 邱瑞, 王观湧, 陈亚恒. 怀来县土地利用格局的影响因子分析[J]. 中国生态农业学报(中英文), 2016, 24(7): 957-968.
TIAN Chao, YANG Jinze, SHI Bo’an, ZHANG Jie, QIU Rui, WANG Guanyong, CHEN Yaheng. Analysis of landscape pattern and affecting factors in Huailai County[J]. Chinese Journal of Eco-Agriculture, 2016, 24(7): 957-968.
Citation: TIAN Chao, YANG Jinze, SHI Bo’an, ZHANG Jie, QIU Rui, WANG Guanyong, CHEN Yaheng. Analysis of landscape pattern and affecting factors in Huailai County[J]. Chinese Journal of Eco-Agriculture, 2016, 24(7): 957-968.

怀来县土地利用格局的影响因子分析

Analysis of landscape pattern and affecting factors in Huailai County

  • 摘要: 河北省怀来县作为北京首都及北方重要的生态屏障, 其土地利用格局不仅与县域土地资源利用有直接关系, 也对周边土地生态的可持续发展有一定影响。土地利用变化研究中驱动机制是重点, 揭示这种机制的关键是能否正确认识土地利用景观格局和影响因子之间的关系。本文以怀来县为研究区, 在遥感技术的支持下, 解译了1994年、2004年和2014年的土地利用数据, 并从社会经济因素和自然因素中选取平均高程、地形起伏度、年均降水量、温度季节性、距道路距离、距城镇中心距离、GDP密度和人口聚集度共8个因子, 结合景观格局梯度分析和CCA分析方法, 对土地利用景观格局和影响因子之间的关系进行研究。得出结论: 2014年怀来县土地利用景观的蔓延度指数、散布并列指数、香浓多样性等存在明显的空间差异, 均在东西方向及南北方向表现出一定的梯度特征; 东西轴线和南北轴线方向上, 蔓延度指数呈两端高中间低的趋势, 而散布并列指数、香浓多样性、香浓均匀度则与之相反。平均高程和人口聚集度对研究区土地利用景观类型的分布影响较大, GDP密度的影响较小; 1994年、2004年和2014年4个排序轴上累积土地利用类型数据与影响因子的解释量依次为99.1%、99.3%以及99.3%, 特征值总量分别为0.780、0.720和0.853, 从解释量数值上看2014年的特征值明显高于前两个时期, 其在描述土地利用类型与影响因子关系上体现出优越性; 影响因子中的地形起伏度、温度季节性、年均降水量、距道路距离和距城镇距离与研究区土地利用景观类型分布的相关性较大, 相关性系数相对较高; 随着研究时间的推移, 地形起伏度相关性逐渐减小, 其他4种影响因子的相关性逐渐增大。通过此项研究, 揭示了怀来县土地利用变化的原因, 并为土地利用的可持续发展提供了理论依据。

     

    Abstract: Huailai County of Hebei Province is an important ecological barrier protecting Beijing (the capital city) and the northern region. The land use pattern in Huailai not only directly affects the use of land resources but also critically influences sustainable development of the surrounding ecosystems. The goal of this research was to correctly understand the relationship between the landscape pattern and the driving factors of land use in the region for determination of the driving mechanism of land use change. Using remote sensing technology, the land use data of Huailai County in 1994, 2004 and 2014 was interpreted to find landscape pattern of land use. Then, eight driving factors were selected among a range of socioeconomic and natural factors, which were average height, relief, annual rainfall, temperature seasonality, distance from road, distance from downtown, GDP density and population density. Gradient analysis of landscape pattern and CCA were used to analyze the relation between landscape patterns of land use and the selected socioeconomic and natural factors, and to distinguish the main driving factors. The landscape indexes, such as spread degree, interspersion-juxtapostion index, Shannon’s diversity index and Shannon’s evenness index, in 2014 of the study area showed obvious gradient difference along east-west and north-south directions. Spread degree was higher in the middle and lower in the two ends, while other three indexes showed contrary tendencies. The average height and population density were the leading factors driving the distribution of landscape patterns of land use in the research area, while the GDP density was the minimal factor. The cumulative explanation values of impact factors of land use type for 1994, 2004 and 2014 were 99.1%, 99.3% and 99.3% and with the corresponding total characteristics of 0.780, 0.720 and 0.853, respectively. Based on the explanation values, the value for 2014 was obviously higher than those for preceding two years. This suggested that 2014 was had advantages in terms of explaining the relation between landscape patterns and the driving factors of land use in the study area. The driving factors, including relief, temperature seasonality, annual rainfall, distance from road and distance from downtown, were significantly related with the distribution of landscape patterns of land use in the research area. As time passed by, the correlation between landscape patterns and relief decreased, while those between landscape patterns and the other 4 driving factors increased. The above analysis revealed the reasons behind land use change in Huailai County, providing evidence of land resources sustainable development in the study area.

     

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