Urban corridor development and ecosystem responses in Addis Ababa: A multi-parameter remote sensing analysis

Corridor-oriented urban development has emerged as a prominent strategy for improving mobility, public spaces, and urban livability. However, its cumulative effects on interconnected urban ecosystem processes remain poorly understood, particularly in rapidly urbanizing cities of Sub-Saharan Africa. This study develops and applies an integrated, cloud-based ecosystem assessment framework using Google Earth Engine to evaluate the early environmental responses associated with corridor-oriented urban development in Addis Ababa, Ethiopia, between 2020 and 2025. The framework integrates land-use and land-cover change, surface sealing, vegetation condition (NDVI, EVI, and LAI), land surface temperature, Urban Heat Island intensity, Urban Thermal Field Variance Index, soil moisture index, evapotranspiration, nighttime light intensity, and atmospheric pollutants (CO and SO₂) within a common spatial and temporal framework. Statistical analyses were conducted to examine relationships among environmental indicators and identify coupled ecosystem responses. The results reveal expansion of built-up and impervious surfaces, declines in vegetation condition and soil moisture, increased land surface temperatures and thermal stress, intensified nighttime light emissions, and localized deterioration in atmospheric quality. Correlation analyses demonstrate significant interactions among vegetation, thermal, hydrological, atmospheric, and urban activity indicators, highlighting the interconnected nature of ecosystem responses to urban transformation. While these environmental changes coincide with major corridor development initiatives, they represent early ecosystem responses that may also reflect broader urban growth, climatic variability, and other concurrent drivers. The proposed framework provides a scalable and transferable methodology for integrated urban ecosystem monitoring and supports ecosystem-sensitive planning and sustainable infrastructure development in rapidly urbanizing, data-constrained cities.