(Appendix C) RF algorithm for LULC classification & Code for Statistics

Description

This repository code serves as supplementary data for the article titled 'Study the Past if You Would Define the Future: A Novel Retrospective Urban Planning Paradigm for Urban Floods Reduction.'

Steps to reproduce

The provided repository link includes all the codes used in the research, covering: 1.JavaScript codes for Land Use and Land Cover (LULC) identification and classification, specifically designed for Landsat and Sentinel series hyperspectral data, and compatible with the Google Earth Engine (GEE) platform. 2.Hydrological calibration and validation codes, which calculate Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and the Pearson correlation index. 3.Thirteen detailed statistical case codes, covering descriptive statistics, hypothesis testing, and logistic regression. 4.Calculation of Shannon's Land Use Diversity Index (SLD) used to describe land use diversity.

Institutions

• Harbin Institute of Technology

  Heilongjiang, Harbin

Categories

Funders

• Ministry of Science and Technology of the People's Republic of China

  Beijing, China

  Grant ID: 2022YFC3203402
• The Science and Technology Project in Key Areas of Foshan, China

  Grant ID: 2020001005987
• International Cooperation Training Program for Innovative Talents, China Scholarship Council (CSC)

  Grant ID: 202106120332

Licence