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浏览/检索结果: 共5条，第1-5条 帮助 限定条件 发表日期：2019     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Eco-Environmental Risk Evaluation for Land Use Planning in Areas of Potential Farmland Abandonment in the High Mountains of Nepal Himalayas 期刊论文 SUSTAINABILITY, 2019, 卷号: 11, 期号: 24, 页码: 6931 作者:  Chaudhary, Suresh;  Wang, Yukuan;  Dixit, Amod Mani;  Khanal, Narendra Raj;  Xu, Pei 收藏  |  浏览/下载：21/0  |  提交时间：2020/03/06 eco-environmental risk assessment  land use planning  analytical hierarchy process  GIS  mountain region  Nepal   Sequential Hazards Resilience of Interdependent Infrastructure System: A Case Study of Greater Toronto Area Energy Infrastructure System 期刊论文 RISK ANALYSIS, 2019, 卷号: 39, 期号: 5, 页码: 1141-1168 作者:  Kong, Jingjing;  Simonovic, Slobodan P.;  Zhang, Chao 收藏  |  浏览/下载：13/0  |  提交时间：2019/08/22 Greater Toronto Area  interdependent infrastructure system  multiple hazards  resilience   A spatial design network analysis of street networks and the locations of leisure entertainment activities: A case study of Wuhan, China 期刊论文 SUSTAINABLE CITIES AND SOCIETY, 2019, 卷号: 44, 页码: 880-887 作者:  He, Sanwei;  Yu, Shan;  Wei, Ping;  Fang, Chuanglin 收藏  |  浏览/下载：48/0  |  提交时间：2019/05/23 Leisure  Entertainment  Spatial design network analysis  Spatial equity  Wuhan   MFCSNet: Multi-Scale Deep Features Fusion and Cost-Sensitive Loss Function Based Segmentation Network for Remote Sensing Images 期刊论文 APPLIED SCIENCES-BASEL, 2019, 卷号: 9, 期号: 19, 页码: 1-18 作者:  Zhang, Qingchun;  Ren, Mengcheng;  Yang, Jingchao;  Li Y(李勇);  Jiang, Yanmei 收藏  |  浏览/下载：37/0  |  提交时间：2019/11/30 Semantic segmentation  remote sensing images  feature fusion  cost-sensitive   MFCSNet: Multi-Scale Deep Features Fusion and Cost-Sensitive Loss Function Based Segmentation Network for Remote Sensing Images 期刊论文 APPLIED SCIENCES-BASEL, 2019, 卷号: 9, 期号: 19, 页码: 1-18 作者:  Wang ED(王恩德);  Jiang, Yanmei;  Li Y(李勇);  Yang, Jingchao;  Ren, Mengcheng 收藏  |  浏览/下载：29/0  |  提交时间：2019/11/30 Semantic segmentation  remote sensing images  feature fusion  cost-sensitive