Spatial Pattern of Residential Land Prices in Dar Es Salaam City, Tanzania

Abstract

The analysis of spatial patterns and variations in urban land prices aids urban planning, socioeconomic analysis, investment decisions, resource allocation, and monitoring of urban spatial growth and land market dynamics. However, scholarly research on the spatial patterns of urban land prices in Sub-Saharan African cities with predominantly informal land markets and settlements remains limited. This study applied spatial statistics to analyse the spatial autocorrelation of residential land prices (RLPs) in Dar es Salaam, Tanzania, aiming to understand their spatial distribution and variation. Global indicators of spatial association (GISA) and Local Indicators of Spatial Association (LISA) were utilised, calculating global Moran’s I and local Moran’s I, respectively, using 452 RLP data from 2020 collected by the Government Chief Valuer. GISA results revealed highly clustered RLPs with strong positive spatial autocorrelation (Moran’s I = 0.83). LISA analysis identified clusters of sub-wards with lower RLPs below the mean, dominating the city's land market. Statistically significant and non-significant LISA results delineated peri-urban and rapidly growing areas. This study provided evidence-based insights for urban planning, policies, infrastructure development, and investor decisions, highlighting the importance of spatial statistics at the regional and sub-regional levels in understanding and improving urban dynamics and land market efficiency.