基于邻近关系的林业数据综合

Forest data generalization based on proximity

科学的森林经营需要考虑林分、景观和自然地理区域三个逐渐增大的可行尺度,林业数据库中实现尺度变化通过空间数据综合实现,数据综合实现大比例尺到小比例尺的选取与图形概括。以森林资源二类调查1∶10 000的空间数据作为数据源,分析拓扑邻近和语义邻近,利用ArcGIS的图形综合功能,完成小班多边形聚合与融合操作。结果表明:以小班面积作为综合选取的条件,综合后小班数基本符合数据综合中的开方根规律;综合前后各个树种比例变化幅度不大,基本上满足树种之间的面积平衡。

Scientific forest management needs to consider the stand, landscape and natural geographic area possible three gradually increasing scale, the data generalization achieving large scale to small-scale through selection and the graphics summary By taking, 1 ： 10 000 forest inventory spatial data as the data sources, analyzing the topology ＆ semantic neighborhood,and using the ArcGIS graphics integrated capabilities, the operation of the sublot polygons aggregation and in tergration were carried out. The results show that： using a small area as a comprehensive selection of the conditions, the number of comprehensive data integration conformed with square root law; the proportion of all kinds of trees species had little change before and after the data generalization of the plots, and the area balance among the tree species was basically staisfied.