ENVIRONMENTAL TIME SERIES ANALYSIS

Monitor landscape changes with satellite data.

Visualise environmental shifts over time.

The Environmental Time Series Analysis is a powerful web app designed for a variety of environmental applications, including monitoring vegetation health, deforestation analysis, drought assessment, land cover classification, tracking built-up area expansion (NDBI), flood monitoring (NDWI), and forest fire risk analysis (NDMI).

The web app provides three key visualisations:

  • Charts: Displaying average NDVI values per month over a selected year.

  • Maps: Showing geospatial distributions of NDVI values by month within the selected year.

  • Land-cover Explorer: Enabling detailed analysis by land cover class.

NDVI, or Normalised Difference Vegetation Index, is commonly used to track changes in vegetation, particularly in protected areas. Future versions of the app will also support additional indices, including NDMI (moisture), NDWI (water), NDBI (built-up), and EVI (for dense vegetation areas).

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  • The Time Series Chart reveals the seasonal dynamics of vegetation health within the selected region over a 12-month period. It highlights key trends and variations, offering insights into ecological patterns and changes. Higher NDVI values generally indicate denser, healthier vegetation, while lower values may reflect sparse growth, environmental stress, or land cover changes driven by factors such as drought, deforestation, or agricultural activity.

  • The Time Series Map visualises NDVI values across the selected region, with each pixel representing the value at a specific geographic location. This allows users to identify spatial patterns, detect anomalies, and compare NDVI values within the Area of Interest (AoI). Users can also calculate Delta NDVI, the difference between current and historical NDVI values for the same month. The Delta NDVI Heatmap highlights areas where vegetation health has improved or worsened compared to past years.

  • The Land-cover Explorer offers insights into average NDVI values for specific land cover types within the area of interest. Users can track NDVI fluctuations throughout the year, observing peaks during growing seasons and declines during dry or dormant periods. This visualisation is ideal for agricultural monitoring, ecosystem assessments, and climate impact studies.

  • The NDVI data used in this project comes from Sentinel-2 satellite imagery, specifically the "COPERNICUS/S2_SR_HARMONIZED" dataset via Google Earth Engine (GEE). This dataset provides atmospherically corrected surface reflectance imagery, ideal for vegetation monitoring.

CREDITS

The Evironmental Times Series Analysis App was developed by CorrelAid and Sensing Clues Foundation, and piloted in Zambia at the Mponda Dam Project by By Life Connected.