喀斯特地区农村居民点对石漠化演变的影响

Influence of Rural Residential Areas on the Evolution of Rocky Desertification in Karst Area

以行政村作为基本研究单元,利用规模特征度量、密度分析、景观指数分析等研究1989—2017年平果县农村居民点和石漠化的时空演变规律,并在此基础上利用地理探测器发掘农村居民点与石漠化演变的内在驱动机理和相互作用。结果表明:①平果县农村居民点受交通干线和河流影响,空间分布不均,整体呈现东北、西南多,中部少的特点,密度特征表现为南北密、中部疏,景观形状指数南高北低、由西南向西北递减;②平果县石漠化规模排序依次是强度>潜在>中度>极强度>轻度,县域东北部、西南部等居民密集区石漠化较为严重,1989—2017年石漠化面积呈现增—减—增—减的波动变化趋势;③农村居民点演变速率、变异系数和景观形状指数和对石漠化演变具有较强的解释力和一定的协同力,对石漠化演变起重要作用,任意两个农村居民点驱动因素的交互作用对石漠化空间差异的影响均大于单一驱动因素,且交互作用类型均为双因子增强或非线性增强。

Taking administrative villages as the basic research unit,this research utilizes the scale characteristics index,kernel density analysis and landscape index to study the spatio-temporal evolution of rural settlements and rocky desertification in Pingguo county from 1989 to 2017,and explores internal driving mechanism and interaction of rural settlements and rocky desertification evolution with Geodetector.The results show that:1)The spatial pattern of rural settlements in Pingguo county is affected by roads and rivers,and has uneven spatial distribution which presents the northeast and the southwest Pingguo county are higher than the middle,the south and the north are both higher than the middle.In term of landscape index,the north is lower than the south,it decreases from the southwest to the northwest.2)The order of the degree of rocky desertification in Pingguo county is intensity,potential,moderate,extreme intensity,mild.Worse areas of rocky desertification mainly distribute in the northeast and the southwest county’s settlements.From 1989 to 2017,the area of rocky desertification shows an increase-decrease-increase-decrease trend.3)The evolution rate,coefficient of variation and landscape shape index of rural settlements have strong explanatory power and certain synergy in the evolution of rocky desertification.It plays an important role in the evolution of rocky desertification.The driving factor interaction of any two rural settlements has a greater impact on the spatial difference of rocky desertification than a single driving factor,and the types of interactions are both double-factor enhancement or nonlinear enhancement.