Advanced Application of Deep Learning, Statistical Modelling, and Numerical Simulation on Geo-Environmental Hazards

155.5K
views
310
authors
59
articles
Editors
4
Impact
Loading...
2,940 views
29 citations
3,074 views
32 citations
3,701 views
18 citations

Urbanization leads to changes in land use, and the expansion of impervious surfaces leads to an increase in flood vulnerability. Predicting and analyzing these landscape pattern changes are important in the early stages of urban planning. In practice, the threshold for obtaining comprehensive and detailed hydrological and meteorological data is high, which makes it difficult for landscape and urban planners to quickly evaluate urban floods. To compensate for these trends, we took Nanjing, China, as the study site and discussed the leading flood vulnerability landscape patterns based on quantitative assessments. We introduced catastrophe theory to integrate three indicators and seven subfactors for flood vulnerability assessment: exposure, including precipitation; sensitivity, including elevation, slope, soil and drainage density; and adaptability, including land use and forest coverage. Then, we calculated the landscape pattern metrics (shape index, fractal dimension index, related circumscribing circle, contiguity index and landscape division index) at the class level. Finally, we divided the city into four subregions, established regression models for the subregions and the whole city, and deduced the leading flood vulnerability landscape patterns in each region and the whole city. We found that the leading landscape patterns varied among different regions. According to the research results, the landscape pattern indexes identified in this paper can be interpreted intuitively, which can provide a reference for modifying the planning layout of regional green infrastructure, optimizing the vulnerability of urban floods, and providing a basis for further improving Nanjing urban planning and alleviating the urban flood vulnerability. The methods proposed herein also will benefit land use and green infrastructure management in other regions lacking meteorological and hydrological data.

3,632 views
9 citations
Fetching...
Open for submission
Recommended Research Topics
Frontiers Logo

Frontiers in Earth Science

Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods
Edited by Faming Huang, Jinsong Huang, Wei Chen, Jinquan Liu
106.8K
views
213
authors
42
articles
Frontiers Logo

Frontiers in Earth Science

Advances in Modeling, Assessment, and Prevention of Geotechnical and Geological Disasters
Edited by Xiaodong Fu, Yongtao Yang, Min Wang, Zetian Zhang
132.3K
views
232
authors
44
articles
Frontiers Logo

Frontiers in Earth Science

Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods - Volume II
Edited by Faming Huang, Zizheng Guo, Huokun Li, Hai Lin
79.1K
views
193
authors
36
articles
Frontiers Logo

Frontiers in Earth Science

Advances and Applications in Modeling, Assessment, and Mitigation of Landslide Disasters
Edited by Zhuo Chen, Danqing Song, Mukhiddin Juliev, Davide Tiranti, Omid Ghorbanzadeh, E Bruce Pitman, Thomas Oommen
15.2K
views
41
authors
7
articles
Frontiers Logo

Frontiers in Earth Science

Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-Based Methods,volume III
Edited by Faming Huang, Jingjing Meng, Sansar Raj Meena
31.4K
views
91
authors
18
articles