Earth Observation Intraurban Analysis

Introduction

Intraurban analysis toolbox is an interactive API for on-the-fly analysis with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalogue of geospatial datasets and satellite imagery. In the recent years, earth observation imagery has become very popular in the global communities to empower diverse environmental applications, including in the domain of climate risk. Due to the vast potential, many individuals are keen to extract insights into social and economic factors, such as heat wave exposure or relative wealth.

This toolbox serves as the bridge in between to provide users with derived information about climate hazards without the need for preprocessing, modelling, and big data storage. It is intended for scholars worldwide, who would like to explore climate hazards in the urban environment. It is also designed for individuals planning to perform further analysis and visualization of the geospatial datasets.

🖱️ You can check out some of the available features below:

🔍 Data Explorer

👨🏻‍💻 Analysis Tool

📏 Comparison Tool

In Progress Items

• Integration of multiple vegetation indices, drought indices (1 & 2), and climate projection layers

• Support heat wave detection in the analysis tool

Analysis Tool

The toolbox allow users to easily download analysis-ready data layers, such as urban heat intensity and urbanisation trends within political-administrative boundaries worldwide. Users can download the results in CSV or GeoTIFF format for further GIS analysis.

• Heatwave Tracking

How did historical heatwaves spatial distributed? What are the long term trends in their frequency, intensity and duration?

• Urban Heat Island Effects

How is urban heat spatially distributed? Which neighborhood has more intense UHI effects?

• Land surface temperature time series for vegetation change hotspots

Are there relationship between urban heat and changes of urban green?

• Age Risk Factor

Senior population suffers more from heat waves. What are the risk factor for different cities and neighborhoods?

• Land Cover Ratio

How do different land cover type spatially distributed? What are the most dominent land uses?

• Population / Urban Density

Where do the majority of the population live in the city?

Comparison Tool

With the comparison tool users can examine different climate hazard factors (eg. relative wealth index, forest density) for any country on-the-fly.

Code Catalog

Below are lists of Javascript code for multiple climate risk analysis. Users can import functions in Google Earth Engine and perform analysis directly using the API.

(click to expand)

Socio-economical Vulnerability 🤒🏙️

Climate Vulnerability

1. WorldPop Age Risk 👉(open in code editor)
2. Relative Wealth Index 👉(open in code editor)
3. Critical Infrastructure 👉(open in code editor)
4. Landscan Population 👉(open in code editor)
5. Drought Index 👉(open in code editor)

Urban Heat 🥵🏙️

Urban Heat Island Analysis

1. MODIS-based Land Surface Temperature (LST) Choropleth 👉(open in code editor)
2. MODIS-based Monthly Median LST (2010-2020) 👉(open in code editor)
3. LST statitics for land use covers 👉(open in code editor)
4. Diurnal LST temperature variation in summers based on Landsat 👉(open in code editor)
5. UHI Effects Intensity 👉(open in code editor)
6. Counting very hot days based on MODIS 👉(open in code editor)
7. Heatwave events time series 👉(open in code editor)

Urbanization 👥🏙️

Population Changes and Urban Development

1. Age-based Risk Factor 👉(open in code editor)
2. Analysing Dense Urban Regions 👉(open in code editor)
3. Analysing Urbanization Changes 👉(open in code editor)
4. Population Count Choropleth 👉(open in code editor)
5. Population Density Choropleth 👉(open in code editor)

Land Surface Dynamics 🌳🌾

Land Use Changes and Vegetation Dynamics

1. Calculate Land Use Proportion 👉(open in code editor)
2. Evaluating impacts of vegetation changes on LST 👉(open in code editor)

Air Pollution 👥🏭

Air Pollutants and Public Health

1. ..

Flooding 🌊🏙️

Flooding History

1. ..

Helper 📦

General geospatial functions to aid analysis

1. Helper 👉️(open in code edito)
2. Customized Basemap 👉(open in code editor)
3. Choropleth Map 👉(open in code editor)

Interface 💻🖱️

Component to construct API

1. App for small raster download 👉(open in code editor)
2. Dataset selection 👉(open in code editor)
3. Resample output 👉(open in code editor)
4. Explorer Main Script 👉(open in code editor)
5. Dashboard Functions 👉(open in code editor)
6. Admin-boundary-based Analysis Framework 👉(open in code editor)
7. Data Explorer App 👉(open in code editor)
8. Data Explorer Functions 👉(open in code editor)
9. Data Explorer Dashboard Styling 👉(open in code editor)
10. Analysis Tool App 👉(open in code editor)
11. Analysis Tool Message 👉(open in code editor)
12. Analysis Tool Styling 👉(open in code editor)

Features

Below is a partial list of features available for the toolbox. This toolbox is currently under development and more features will be available soon.

• Download landuse cover for any global administrative boundaries (level 2) in customized resolution up to 10m
• Download smoothed daily land surface temperature (.csv) derived from MODIS for global administrative boundaries
• Address UHI hotspots for global administrative boundaries using UHI intensity index (day time and night time)
• Locate vegetation change hotspots for global administrative boundaries
• Download urban and population density map for global administrative boundaries
• Compare admin 2 level regions for different data layers such as population, relative wealth, and drought indices in a choropleth map
• Inspect spatial distribution of climate risk-vulnerability using state-of-the-art datasets: Relative Wealth Index & Critical Infrastructure Spatial Index

References

Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone.

World Bank Group. 2022. Pakistan Country Climate and Development Report. CCDR Series;. © World Bank, Washington, DC. http://hdl.handle.net/10986/38277 License: CC BY-NC-ND.