README.md

sim_greenfacade

Investigating the Effects of Green Walls on Local Climate Regulation: A Case Study for Dresden

Overview

This repository contains the code and data used in the master thesis titled "Investigating the Effects of Green Walls on Local Climate Regulation: A Case Study for Dresden." The study explores the potential of facade greening to mitigate urban heat island effects and improve thermal comfort in urban settings, specifically in Dresden, Germany.

Table of Contents

• Introduction
• Methodology
• Results
• Usage
• Dependencies
• Contributors
• License

Introduction

Urban environments face significant challenges from heat island effects, air pollution, and declining biodiversity. This study investigates how green walls can help mitigate these issues by improving local microclimates. Using ENVI-met simulation software, the study assesses various thermal comfort variables under three scenarios:

1. With No Greenery
2. With Trees
3. With Trees & Green Facade

Methodology

1. LCZ Classification: Using the LCZ generator and Google Earth to create training areas and classify the urban landscape.

LCZ Generator Factsheet

LCZ Outcome Data

LCZ class	Count	Avg. area (km²)	Total area (km²)	Perimeter (km)	Shape	Vertices
2	5	0.2	1.0	1.9	1.9	7.4
5	7	0.3	2.4	2.6	1.7	7.6
6	6	0.3	1.7	2.1	1.4	4.3
10	4	0.3	1.2	2.5	1.6	7.0
11	4	0.4	1.7	2.8	1.5	5.8
12	5	0.1	0.3	1.1	1.6	4.6
14	4	0.2	0.9	2.3	1.9	4.8
16	3	0.1	0.4	1.5	1.4	6.7
17	5	0.1	0.5	1.6	2.3	4.8

2. Study Site Selection: Chose the outer Neustadt district in Dresden, characterized by Wilhelmine architecture and low greenery.
3. Database Development:
   • Building Materials: Information on wall compositions and thermal properties.
   • Building Footprints: Extracted from open geographical data.
   • Trees and Existing Greenery: Adjusted using field observations and refined open data.
   • Climbing Species: Selected Hedera Helix for its prevalence and characteristics.
   • Meteorological Data: Used EPW files for precise simulation inputs.
4. ENVI-met Simulation:
   • Built the simulation using the ENVI-met plugin in QGIS.
   • Developed three greening scenarios.
   • Extracted data using ENVI-met Leonardo for analysis.
5. Statistical Analysis:
   • Normality tests using Shapiro-Wilk.
   • Friedman Two-Way ANOVA for significance testing.
   • Post-hoc pairwise comparisons for detailed analysis.

Results

The results indicate significant improvements in microclimate parameters with the introduction of green facades and trees. Key findings include:

• Lower air temperature inside the buildings.

• Lower air temperatures.

• lower mean radiant temperatures.

• Enhanced relative humidity levels.

• Marginal effects on wind speed.

• Improved thermal comfort in urban environments.

• Dynamic PET (Physiological Equivalent Temperature). You can find two short videos demonstrating the simulation results at the following paths:

1. Trees & Green Facades vs. No Greenery
2. Trees & Green Facades vs. Only Trees

Usage

To run the analysis:

1. Clone this repository.
2. Ensure all dependencies are installed (see below).
3. Find the scripts in the /scripts directory to set up and run ENVI-met simulations.
4. Python scripts for statistical analysis and data visualization.

Dependencies

• ENVI-met software
• QGIS
• Python 3.11
  • pandas
  • numpy
  • scipy
  • matplotlib

Contributors

• Amir Raoufi - Main Author ([email protected])

This work is jointly supervised by:

• 1st Supervisor: Prof. Dr. rer. pol. Irene Ring, IHI-Zittau, TU Dresden, Germany.
• 2nd Supervisor: Dr.-Ing. Sujit Kumar Sikder, Leibniz Institute of Ecological Urban and Regional Development (IOER), Dresden, Germany.
• Mentor: M.Sc. André Tiemann, IHI-Zittau, TU Dresden, Germany.

License

Note that this are initial demo release, citable data license will be added later.