Increasing pace of urbanization is the leading cause of decline in natural areas and associated biodiversity in developing countries. Bird richness is considered as a key indicator of urban environment quality. We investigated the relationship between satellite image derived landscape variables and field surveyed bird counts to predict bird richness in a rapidly urbanizing city in Western Himalayan foothills of India. Predictor variables derived from remotely sensed data comprised of vegetation productivity, landscape metrics and topography. We found that bird richness in this low density residential urban environment was positively related to greenness, elevation, and the degree of contrast between neighbourhood patches, while it was negatively related to patch densities. The Generalized Linear Model (GLM) with lowest Akaike Information Criterion (AIC) explained about 90% variability in bird richness distribution. Results indicated high bird species richness in elevated remnant vegetation patches and green spaces compared to low lying “core” settlement areas. The study urges to consider conservation and protection of green cover spaces in urban areas through effective landscape and urban planning.