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机构地区:[1]中国科学院遥感与数字地球研究所,北京100101 [2]中国科学院大学,北京100101
出 处:《测绘科学》2017年第9期62-70,共9页Science of Surveying and Mapping
基 金:十二五国家科技支撑计划项目(2013BAK08B06;2015BAK01B01)
摘 要:针对榆林东北部地区新石器时代的环境宜居性分布规律进行研究,通过SOFM神经网络模型对研究区聚落等级进行划分,结合地形高程、坡度、坡向、距水系距离、植被覆盖度等因子,构建指数模型。研究结果表明,研究区遗址大都分布在海拔1 000~1 200m、坡度3~9°、距水系距离为0~800m、坡向为阳坡以及植被覆盖度较好的区域,一级聚落均分布在古代环境宜居性较高的区域。与仅使用地形因子建立的指数模型相比,加入植被覆盖度和聚落等级因子的模型对不宜居的沙漠和遗址分布空白区域划分的宜居性等级低,对遗址分布密集的宜居区域划分的宜居性等级高,宜居性等级划分结果与各等级遗址密度分布的客观事实更为吻合,综合因子模型对区域宜居性等级划分更为精确。The paper analyzed on the ancient environment livability in Northeast Yulin in the Neolithic Age. The settlements in the study area were classified by the Self-Organizing Feature Map(SOFM)neural network. Then the relative importance of settlement determinants including elevation, slope, aspect, dis- tance from water and vegetation cover to estabish an index model. The results show that these sites were located mostly in areas characterized by altitudes between 1 000-1 200 m, 3-9° slope gradient, 0-800 m distance from water, sunny slope aspect and dense vegetation cover. Level-one settlements were mainly located in the areas with a high environment livability level. Compared to the model which considers the terrain factor only, the comprehensive model that incorporated vegetation cover and settlement level factor shows a better consistency between the livability level and density distribution of the sites in each level. In the model, the livability level is low in the desert and blank site area, while it is high in the densely dis- tributed area. This comprehensive model could also classify the livability level more precisely.
关 键 词:自组织特征映射模型 指数模型 古代环境宜居性 聚落等级 植被覆盖度
分 类 号:P237[天文地球—摄影测量与遥感]
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