Correlation between the Construction of Zhejiang Coastal Military Settlements in the Ming Dynasty and the Natural Terrain

人类住区 自然(考古学) 地形 地质学 地理 考古 地图学
作者
Lifeng Tan,Jiayin Zhou,Yukun Zhang,Jiayi Liu,Hongwei Liu
出处
期刊:Journal of Coastal Research [Coastal Education and Research Foundation]
卷期号:106 (sp1): 381-381 被引量:6
标识
DOI:10.2112/si106-088.1
摘要

Tan, L.; Zhou, J.; Zhang, Y.; Liu, J., and Liu, H., 2020. Correlation between the construction of Zhejiang coastal military settlements in the Ming Dynasty and the natural terrain. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 381–387. Coconut Creek (Florida), ISSN 0749-0208.The military settlement for the coastal defense of Zhejiang Province in the Ming Dynasty (1368–1644) is representative of military settlements throughout ancient China. The distribution of military power was closely related to the natural terrain, and its military hierarchical structure conformed to fractal systems. Based on fractal theory, the box dimension method, which has been widely used in geography, was selected to calculate the geomorphic fractal dimension of coastal-defense settlements within a certain range. The traditional box-counting method was optimized by ArcGIS to obtain the geomorphic-complexity index. By analyzing the correlation between this index and the military-force scale data extracted from historical books, this article breaks through the qualitative conclusions of general studies and obtains the quantitative influence of the complexity of the natural terrain on military construction, especially on the distribution of the size of garrison troops. This method quantifies complex concepts through fractal dimensions and provides a new idea for research on the influence of the natural environment on the formation of traditional settlements.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
有何不可发布了新的文献求助10
1秒前
轻松音响完成签到,获得积分10
1秒前
科研通AI6.4应助喔喔糖采纳,获得10
1秒前
gyq完成签到,获得积分10
1秒前
轻松寻桃完成签到 ,获得积分10
1秒前
Xxy发布了新的文献求助10
2秒前
Xquery发布了新的文献求助10
2秒前
hhh完成签到,获得积分10
2秒前
华仔应助爽歪歪采纳,获得10
3秒前
nnn完成签到,获得积分10
3秒前
研友_8WMQ5n发布了新的文献求助10
4秒前
徐慕源完成签到,获得积分10
4秒前
科目三应助菜菜酱爱火锅采纳,获得10
5秒前
hwq123完成签到,获得积分10
5秒前
5秒前
会做饭的外星人完成签到 ,获得积分10
6秒前
6秒前
6秒前
6秒前
orixero应助杜文彦采纳,获得30
6秒前
唐德情完成签到,获得积分10
6秒前
yang完成签到 ,获得积分10
7秒前
Kao应助波利波利爱吃鱼采纳,获得10
7秒前
ling发布了新的文献求助10
7秒前
从不内卷完成签到,获得积分10
7秒前
8秒前
9秒前
9秒前
结实康完成签到,获得积分10
9秒前
YyLin发布了新的文献求助10
9秒前
夏夏霞发布了新的文献求助10
10秒前
zoe发布了新的文献求助10
10秒前
11秒前
小雏菊发布了新的文献求助10
11秒前
如意书桃完成签到 ,获得积分10
11秒前
12秒前
科研通AI6.2应助优美寒荷采纳,获得10
12秒前
小万完成签到 ,获得积分10
12秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Data book on fatigue strength of metallic materials 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7566546
求助须知:如何正确求助?哪些是违规求助? 9146702
关于积分的说明 19558071
捐赠科研通 7152905
什么是DOI,文献DOI怎么找? 3262662
关于科研通互助平台的介绍 2428886
邀请新用户注册赠送积分活动 2252636