Spectral Visualization

Spectral Visualization of Nairobi County

Major anthropogenic activities such as; deforestation and rapid urbanization have a major impact on the optimum functioning of the natural ecosystem. These phenomena precedent the loss and degradation of natural habitats for the benefit of agricultural activities and the built environment. The impact of these anthropogenic activities necessitates the monitoring of arising land use and land changes. Monitoring land use and land changes is in line with the objectives of achieving the United Nations’ sustainable development goals (SDGs).

In developing spectral visualization of the County of Nairobi, there is an express linkage to the 11th, 13th, 14th, and 15th SDGs. Respectively, these SDGs aim to achieve sustainable cities and communities, climate action, life in water and terrestrial life. For instance, goal 13 on climate action becomes very relevant considering the frequent challenges of heatwaves and floods. As such, satellite imagery can enable the quick detection of changes to the ecosystem. This will then instigate the creation of policies to manage urban landscapes towards achieving climate resilience. This is in recognition of urban landscapes as key frontiers for action towards the ideals of sustainable development.

Various spectral indices have been utilized in Google Earth Engine (GEE), using Landsat imagery. These indices have been used to create a large-scale visualization of the County of Nairobi. Spectral index, is the combination of spectral reflectance from two or more wavelengths that indicate the relative abundance of certain phenomena. Some of these phenomena include vegetation, soil, water resources, and built-up features.

Spectral Indices

The specific spectral indices utilized and their descriptions are:

  • Bare Soil Index (BSI) – the amount of bare land (white-brown)
  • Green Coverage Index (GCI) – estimates the amount of chlorophyll in plants (white-green)
  • Moisture Stress Index (MSI) – Illustrates plant water stress (red-blue)
  • Normalized Difference Moisture Index (NDMI) – Calculates the water content in vegetation (white-blue)
  • Enhanced Vegetation Index (EVI) – Similar to NDVI but corrects for atmospheric noise (white-green)
  • Green Normalized Difference Vegetation Index (GNDVI) – A modified version of NDVI that is more sensitive to chlorophyll variation (brown-green)
  • Normalized Difference Built-up Index (NDBI) – Indicates the density of built-up areas (white-blue)
  • Normalized Difference Vegetation Index (NDVI) – Numerically indicates vegetation content (white-green)

The spectral visualization developed here can help to influence planning policy and natural habitat management towards sustainability.

Spectral Visualization NDVI
Nairobi County: Green Normalized Difference Vegetation Index
Spectral Visualization
Nairobi County: Normalized Difference Built-up Index

You can access the spectral visualization which is a shared GEE web app

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