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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。
According to the Neolithic environmental livability distribution pattern in the northeast of Yulin, the community level of the study area is divided by SOFM neural network model. According to the topographic, slope, aspect, distance from the water system and vegetation coverage, Build an exponential model. The results show that most of the sites in the study area are located at an altitude of 1 000-1 200 m, a slope of 3 to 9 °, a distance of 0-800 m from the river system, a sunny slope and a good vegetation coverage area In the ancient habitat livability of the region. Compared with the exponential model established by using only the topographic factors, the model incorporating the vegetation coverage and settlement level factors has a low livability rating for the inhospitable deserts and the blank areas for the site distribution, and the livable area for the densely distributed sites The livability level is higher, the livability rating results are more in line with the objective facts of the density distribution of each rank site, and the comprehensive factor model is more accurate for livability classification of the district.