Urban growth evaluation: A new approach using neighborhood characteristics of remotely sensed land use data

Abstract

Recently, there has been widespread concern about the understanding of land change and urban growth, in particular for addressing a wide range of issues in the urban environment. Although new and sophisticated methods have been developed and successfully applied to urban growth characterization, these methods require rich data input and limit their applicability in a data-poor context. For such contexts, we developed a new urban growth evaluation approach (UGEA) with freely available Landsat images that can be used to characterize urban growth by overcoming data limitations. Initially, we employed the neighborhood interactions of the surrounding area to rationally define urban land use (ULU). Subsequently, ULU changes were utilized to characterize major patterns of urban growth using three indicators: infill, extension, and leapfrog development. Later, these major patterns were further divided into low, moderate, and high sublevels, depending on the neighborhood interaction as a newly introduced approach into urban growth evaluation. We tested the performance of our approach using a case study on the Colombo metropolitan area of Sri Lanka. Our results indicate that the performance of our new approach is acceptable. We suggest UGEA for comparative urban studies rather than individual case studies in the future.