Overview
Environmental Index Modelling refers to the computation of satellite-derived indices that represent the condition, vigour, and variability of key ecological parameters across space and time. These indices offer a valuable way to monitor land degradation, vegetation health, hydrological stress, post-fire recovery, and seasonal dynamics of ecosystems. Unlike raw imagery, indices are ratio-based metrics that highlight specific features or conditions, reducing noise from non-target variables. For regions where regular environmental monitoring is logistically difficult, this service provides continuous, low-cost coverage that supports both research and policy evaluation. It is particularly relevant for natural resource managers, agricultural planners, and institutions concerned with climate adaptation and land-based mitigation strategies.
Features
This service involves the computation of vegetation indices such as the
- Normalized Difference Vegetation Index (NDVI),
- Enhanced Vegetation Index (EVI)
- Soil-Adjusted Vegetation Index (SAVI) among others.
For hydrological applications, indices such as
- Normalized Difference Water Index (NDWI)
- Moisture Stress Index (MSI) are used.
Fire-affected areas are assessed using indices like the
- Normalized Burn Ratio (NBR) and its derivative dNBR, which allow for pre- and post-fire severity assessments.
All indices are calculated from surface reflectance data (usually at 10–30 metre resolution), and processed using platforms like Google Earth Engine (GEE), QGIS, or ArcGIS Pro. Time-series analysis includes anomaly detection, seasonal trend decomposition, and pixel-based trend analysis (e.g., Mann-Kendall or Sen’s slope), depending on the nature of the inquiry
Goal
The goal of this service is to equip decision-makers, researchers, and field-based programmes with spatial intelligence that captures environmental changes before they become visible to the naked eye or measurable in field reports. Whether used for early warning in agricultural drought, planning reforestation efforts, or evaluating ecosystem health, environmental index modelling transforms satellite data into strategic insights. It shifts the approach from reactive to anticipatory, allowing interventions to be more targeted, timely, and grounded in observed environmental trends.