Liang Jia Xin, Li Xin Ju
College of Resources and Environment, Shandong Agriculture University, Tai'an 271018, Shandong, China.
Ying Yong Sheng Tai Xue Bao. 2018 Feb;29(2):626-634. doi: 10.13287/j.1001-9332.201802.018.
With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.
以1985年、2000年Landsat 5 TM影像和2015年Landsat 8 OLI遥感影像为数据源，利用由敏感性指数和适应性指数构建的景观格局脆弱性指数，并结合半变异函数、空间自相关等空间统计方法，尝试选取合适的研究尺度，在此尺度下对南四湖湿地的时空分异特征进行研究。结果表明，1 km×1 km等距网格是合适的研究尺度，该尺度能够消除随机因素引起的空间异质性影响。1985—2015年，南四湖湿地景观格局脆弱性逐渐恶化。景观格局脆弱性高风险区随时间急剧扩张。景观格局脆弱性的空间异质性增加，非结构性因素对景观格局脆弱性的影响增强。受空间自相关影响的空间变异性略有减弱。景观格局脆弱性具有较强的全局空间正相关性，呈现出显著的空间集聚形态。随着时间的推移，正向空间自相关持续增强，空间集中现象越来越明显。以高高集聚区和低低集聚区为主的局部自相关在相邻空间单元间具有较强的空间自相关性。高高集聚区的显著性水平最强，低低集聚区的显著性水平随时间增加。温度、降水等自然因素影响水位和景观分布，进而改变南四湖湿地景观格局脆弱性。景观格局脆弱性恶化的主导驱动因素是人类活动，包括社会经济活动和政策制度。
