基于谷歌地球引擎和分形理论的黄河三角洲土地利用空间结构研究

基于谷歌地球引擎(Google earth engine, GEE)，以Landsat-5(TM)、Landsat-7(ETM)和Landsat-8(OLI)数据为遥感数据源，采用随机森林分类方法对黄河三角洲生态功能保护区1985—2020年的土地利用类型进行了划分，在此基础上利用分形理论方法计算了土地利用分形维数和稳定性指数，并分两个阶段对研究区土地利用空间结构的复杂度和稳定性进行了定量分析。结果表明：①1985—2020年，研究区的耕地面积逐渐减少；草地面积相对较稳定；水体面积逐渐扩大，2015—2020年增长率最高；裸地面积的变化较为波动，先增加后又逐渐下降；建筑物面积呈指数增长。②研究区土地利用空间结构的分形维数总体上呈降低趋势，表明土地利用复杂度降低。③研究区土地利用空间结构的稳定性指数总体上呈升高趋势，表明土地利用空间结构趋向稳定。总体上，黄河三角洲生态功能保护区随着环境保护政策的实施，土地利用空间结构逐渐得到改善，水、草等自然资源逐渐丰富。

Study on Land Use Spatial Structure Based on Google Earth Engine and Fractal Theory: A Case Study of Ecological Function Reserve in Yellow River Delta

Based on Google Earth Engine (GEE), Landsat-5 (TM), Landsat-7 (ETM) and Landsat-8 (OLI) data were used as remote sensing data sources to classify land use types from 1985 to 2020 with the random forest classification method. The fractal theory method was used to calculate land use fractal dimension and stability index, and the complexity and stability of the spatial structure of land use types were quantitatively analyzed in two stages of 1985—2005 and 2005—2020. The results showed that: 1) From 1985 to 2020, cultivated land gradually decreased, grassland changed little, water gradually expanded, with the highest growth rate in 2015—2020, bare land changed more irregularly, increasing first and then gradually decreasing, and buildings grew exponentially. 2) Fractal dimension of the spatial structure of land use types generally showed a decreasing trend, indicating a decrease in its complexity. 3) Stability index of the spatial structure of land use types tended to increase in general, indicating it tended to be stable. In conclusion, with the implementation of environmental protection policies, the spatial structure of land use types in the study area has been gradually improved, and natural resources such as water and grassland have been gradually enriched.