闽东北沿海罗源县土地利用空间分布格局的多尺度分析

Multi-scale Spatial Characterization of Land-use Patterns of Luoyuan County in Northeast Fujian Province

在不同的空间尺度上,制约土地利用空间分布的影响因子及其影响程度并不相同,因此区域空间分布格局分析应优先考虑制约空间分布的影响因子识别及其影响程度的尺度依赖性的研究。本文以闽东沿海的罗源县为研究区域,采样统计方法与GIS技术,选取20个候选影响因子,研究了该县主要土地利用空间分布格局的影响因子及其空间尺度相关性。研究表明模型的解释能力、影响因子及其影响系数均会随研究尺度发生不同程度的变化,回归模型的解释能力以及主要影响因子的制约程度总体上均随研究尺度增大呈增强趋势。除受坡度、海拔高程等地形条件的严格制约外,罗源县主要地类均在一定程度上受到人口因素以及若干可达性因素的影响。

Land use patterns are governed by a broad variety of potential driving forces and constraints which act over a large range of scales. It has been recognized that the types and effects of land use drivers may vary with spatial scale, and multi-scale investigation of land use patterns is essential for full understanding of its complexity. The main purpose of this paper was to perform a multi-scale analysis of land use patterns of Luoyuan County in Fujian province by means of statistical analysis on the basis of bio-geophysical, socio-economic and infrastructural conditions. 20 variables were selected as the candidate land use drivers and 9 main land use types were considered. Land use data was derived from the 1：1 0000 survey map, terrain data from the 1：50000 DEM, and accessibility data, i.e. distance to the nearest rural road, from 1：10000 distribution map of rural road, river, residential area, and etc. But socio-economic data such as population census data was collected on the basis of administration areas. As a result, the spatial distribution of population data on cells was conducted based on the analysis of the relationship between population density and its influencing factors. The basic spatial organization in the analysis was a 100×100 meter geographical grid. Through aggregations of these cells, a total of 20 artificial aggregation levels were obtained. 9 independent main land use types, namely paddy land, dry land, garden plot, woodland, town land, agricultural residential area, industry land, water body and unused land, were constructed at multiple scales respectively. The results showed that： （1） Land use models varied with aggregation level indicating spatial scale effects. Independent variables explained more of the variance for the explanation of land use type at higher aggregation levels. Relationships obtained at a certain scale of analysis may not be directly applied at other scales. The variables included in the models and their relative importance also varied between land use types. （2） The distribution of paddy land was mainly restricted by slope, distance to the nearest rural road or city, aspect, agricultural population density, whose influence increases with scale, elevation and distance to nearest cover river, whose influence occur only in medium or small aggregation levels. For garden plot, the elevation and the distance to nearest coast or fresh water sea-route are the highest ranking variables and their contributions in- crease with aggregation levels. The slope and the distance to nearest town or line-river or city are the second ranking variables. For woodland, the slope and the distance to city or town are the most leading variables at almost all aggregation levels. Important variable also includes elevation at lower aggregation levels. Variables of distance to nearest highroad or low road or residential contribute to the models to a certain extent and their contributions increase with aggregation levels. Industry land is mainly related with distance to nearest fresh water sea-route, total population density, distance to nearest coast or road, slope and distance to nearest city, whose influences all increase with aggregation levels. Most land use types in Luoyuan County were restricted by topographic factors while topography changes little along with time. It is argued that these types of analyses can support the quantitative multi-scale understanding of land use, needed for the spatially explicit land use change models.