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

Local Project Nairobi, Kenya Chapter

Coordinated by the Lead of Kenya, Wangari Kimotho,

Status: Ongoing

Partnership.

Project background.

Nairobi city is globally admired and even termed the Green City in the Sun.

Over the years, however, the urban heat island effect has come into force. This is partially attributed to increase in greenhouse gas emissions and a decrease in tree cover as urban encroachment into forested areas ensues. Having this in mind, developing a workflow that can enable us to monitor change in the urban green areas is paramount and promises to be of use to local government and policymakers that could take the results from this project to make cities like Nairobi more green and sustainable.

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. 

Project goals.

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:

  • Change in green Areas per Capita as defined in the Global Urban Monitoring Framework (UMF-47). The methodology involves the estimation of a city area under vegetation cover for several time periods e.g., the years 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.
  • 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 years 2000, 2010, and 2020, and analyzing the change over time.

Project plan.

1. Extraction of data from satellite images hosted on cloud-based platforms.

Due date 9th December.

2. Define the city boundaries and generate statistics based on 2 indicators:

  • Change in Green Areas per capita
  • Change in Tree Cover

Due date 22 December.

3. Define future steps, document the work done during the project, and gather material and possible blog writing.

Due date 30 December.

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