Database

Mendeley Data2026-04-09 收录

数据链接：

https://data.mendeley.com/datasets/zszhv44sj2/2 数据链接链接失效反馈

官方服务：

资源简介：

This dataset includes ensemble code of machine learning and contributing factors (Processed) for flood susceptibility extraction.

Training and testing samples of three urban catchments in Beijing

洪水易发性

机器学习

This file included the training and testing samples of CNN model in three urban catchments (LSH, QH and BH catchments). Detailed descriptions of the data source and format are available in Zhao et al

DataCite Commons2021-01-21 更新60

Application of the Relative Elevation Model (REM) for the classification of flood-susceptible areas in the municipality of Rio Branco, Acre State, Brazil

洪水易发性

地理信息系统

This dataset was developed to support the application of the Relative Elevation Model (REM) methodology for the identification and classification of flood-prone areas within the urban perimeter of Rio

DataONE2025-10-09 更新30

Flood Susceptibility Modelling of Karnali River Basin using Different Machine Learning Techniques

洪水易发性

水文预测

This dataset is the data used for flood susceptibility modeling of Karnali River Basin of Nepal based on ten flood conditioning factors. The data and flood points are used for application of machine l

科学数据银行2023-07-11 更新30

The Camden area flood prone land study

洪水易发性

土地利用水环境影响

Environmental Impact Statement: The Camden area flood prone land study

Research Data Australia40

CATENA_Article2

洪水易发性

灾难评估

Research data used in article 2 intitled "Refining Flood Susceptibility Mapping: A Critical Review of Conditioning Factors and Conceptual Definitions"

NIAID Data Ecosystem30

Database

资源简介：

相关数据集