西藏“一江两河”流域土地利用时空分布与地形因子关系研究

Relationship Between Spatio-Temporal Distribution of Land Use and Topographic Factors in the Valleys of the Yarlung Zangbo River and Its Two Tributaries—the Nyangqu River and the Lhasa River in Tibet

以西藏的"一江两河"流域为例,以1990年、2000年、2010年、2015年4期土地利用现状数据和数字高程模型(DEM)派生数据坡度、坡向和高程3个地形因子信息为基础,基于DEM并结合ArcGIS技术,对地形因子和土地利用数据进行叠加提取,采用土地变化强度指数(K)、土地分布指数(LDI)和土地转移分布指数(p)3个指标分析总结了地形因子对流域土地利用时空变化的影响特征及规律.结果表明:1990-2015年期间,居民地用地强度变化呈现最大,其余地类变化缓和;耕地、居民地、林地和草地的分布指数随高程坡度变化分布指数差异大,不同地类在各级因子中优势分布差异显著;林地最容易转移,耕地和建设用地向低海拔低坡度半阳坡转移明显,其余地类转移较为缓慢.综合来看,地形因子对土地利用变化的影响作用明显,土地利用优势分布和土地利用转移均出现不同的时空变化特征.

A case study was made of the YNL basin（the Yarlung Zangbo River with its two tributaries-the Nyangqu River and the Lhasa River）in Tibet.Based on the land use status data in four periods and the DEM-derived data about slope,aspect and elevation,DEM（digital elevation model）and the technique of ArcGIS were employed in combination to extract the superposition of the terrain factors and land use data.The land use change intensity index（K）,the land distribution index（LDI）and the distribution of land transfer index（p）were used to analyze and summarize the influences of the terrain factors on the spatial and temporal variation of land use of the study area.The results showed that during the period of 1990-2015,inhabitant land had the largest change of land use intensity;that the distribution indexes of cultivated land,inhabitant land,woodland and grassland were different from the variation of elevation and slope,and the distribution indexes of different types of soil were significantly different at different levels;and that the most easily transferable was woodland,and much cultivated land and construction land had been transferred to the areas with low elevation of low semi-sunlit slope,the transfer of other land use classes was slow.To sum up,terrain factors have a significant influence on land use change in the YNL basin,and land use distribution and transfer of land use spatial and temporal variation characteristics are different.