[Thailand Chapter] Monitoring Change in Urban Green Areas and Tree Cover using Satellite Imagery in Thailand region

Challenge Background

Monitoring the changes in green landscapes using satellite images and demographical information. Since Thailand is an agricultural-based country, it is very natural to have green areas and trees more or less everywhere. Being a tropical country, it also rains a lot and there is no winter here. But this time, we can observe climate changes and feel a bit of the winter season. using satellite images and demographical information will be beneficial to monitor those changes in urban areas.

The Problem

Prosperous cities seek to increase their green areas for better air quality and improved quality of life for their populations. Green spaces in cities mitigate the effects of pollution and can reduce the urban heat island effect. At the same time, land use change in urban areas leads to a reduction in tree cover, contributing to the loss of biodiversity. Accordingly, it is important for cities to monitor their progress in maintaining and increasing their tree cover and green areas. The monitoring will enable city authorities to measure the environmental impacts of urban development against their mitigation measures, as well as support city policy actors in decision-making. 

Goal of the Project

The AI solution should involve the extraction of data from satellite imageries hosted on cloud-based platforms (e.g., the Earth Engine’s public data catalog), and within defined city boundaries, generate statistics on two urban indicators related to environmental sustainability. To enable comparison of city statistics, the project will utilize the urban boundaries generated through the harmonized city definition approach (JRC-UrbanCentresDatabase).

These indicators are:

1. Change in green Areas per Capita as defined in the Global Urban Monitoring Framework (UMF-47). The methodology involves estimation of a city area under vegetation cover for several time periods e.g., the year 2000, 2010, and 2020; the indicator has 2 key metrics: change in green areas over time, and change in per capita green areas over time, which factors the changes in city population.
2. Change in Tree Cover as defined in the Global Urban Monitoring Framework (UMF-48). The methodology involves estimation of the city area under tree cover for several time periods e.g., the year 2000, 2010 and 2020, and analysing the change over time.

Project Timeline

What you'll learn