Clustering Urban Multifunctional Landscapes Using the Self-Organizing Feature Map Neural Network Model
Clustering Urban Multifunctional Landscapes Using the Self-Organizing Feature Map Neural Network Model
复制标题
使用自组织特征图神经网络模型聚类城市多功能景观
DOI：
10.1061/(asce)up.1943-5444.0000170
复制
发表时间：
2014-06
影响因子：
2.5
通讯作者：
Zhu, Yu-Kun
中科院分区：
文献类型：
--
作者：
Wang, Yang;Liu, Jin-Long;Li, Shuang-Cheng;Zhu, Yu-Kun
摘要城市生态系统的多功能性在过去的十年里受到了研究者和政策制定者的广泛关注。以深圳市为例，对城市多功能景观集群进行了研究。利用自组织特征映射（SOFM）神经网络模型，识别出6个不同的景观功能指数，城市多功能景观区划产生5个主要单元。根据SOFM聚类结果，各地区具有各自的主要功能，如天然气调节、供水、人文调节、土壤环境调节、经济、文化优先等。天然气调节生态支撑区（Ⅰ区）面积490.5 km 2，海岸线长，形成了以自然为主、人为影响较小的自然环境;供水生态支撑区（Ⅱ区）面积25.8 km 2，河网密度达0.986 km/km 2，具有水源涵养和供水功能。
AbstractMultifunctionality in urban ecosystems has received much attention in the last decade from researchers and policy makers. This paper provides research on urban multifunctional landscape clustering, using the city of Shenzhen, China, as a case study. Utilizing the self-organizing feature map (SOFM) neural network model, six different landscape functional indices were identified, and urban multifunctional landscape regionalization produced five major units. According to SOFM clustering results, each region had its respective primary function, such as gas regulation, water supply, human nature regulation, soil environmental regulation, economy, and cultural priority. The gas regulation ecological supporting region (Zone I) covers 490.5 km2, with long coastline form a nature-dominated, less human-influenced physical environment; the water supply ecological supporting region (Zone II) is 25.8 km2, and river network density reaches 0.986 km/km2, supporting function of water conservation and water sup...
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DOI：
10.1002/047134608x.w5513.pub2
发表时间：
2019-02
期刊：
Wiley Encyclopedia of Electrical and Electronics Engineering
影响因子：
--
作者：
K. Kulkarni;P. Turaga;Anuj Srivastava;Rama Chellappa
通讯作者：
K. Kulkarni;P. Turaga;Anuj Srivastava;Rama Chellappa
影响因子：
3.9
作者：
Lorenzo Vaquero;V. Brea;M. Mucientes
通讯作者：
Lorenzo Vaquero;V. Brea;M. Mucientes
DOI：
10.1049/iet-bmt.2018.5117
发表时间：
2016
期刊：
IET Biom.
影响因子：
--
作者：
Sheng He;Lambert Schomaker
通讯作者：
Sheng He;Lambert Schomaker
影响因子：
9.1
作者：
K. Bomans;Thérèse Steenberghen;Valerie Dewaelheyns;Hans Leinfelder;H. Gulinck
通讯作者：
K. Bomans;Thérèse Steenberghen;Valerie Dewaelheyns;Hans Leinfelder;H. Gulinck
DOI：
10.1007/978-3-319-92198-3
发表时间：
2018
期刊：
--
影响因子：
--
作者：
Chao Sui;Bennamoun;R. Togneri
通讯作者：
Chao Sui;Bennamoun;R. Togneri