Assessing Pixel-Based Land Cover Classification Using Sentinel-2 10 Meter Resolution Imagery: A Case Study of Kuching, Sarawak, Malaysia

Abstract

Land cover maps are important in spatial planning and urban development as well as for environmental monitoring. It provides an overview on various types of land cover and that information is needed for the current and future land development and planning. While it is recognized that land cover maps are important, not many organizations have access to high resolution imagery due to budget constraints and therefore they will use whatever available satellite imagery to support their current business operations. With the available of Sentinel imagery data that provides 10-meter resolution with no cost or free for public to use, it serves as an initial data source when higher-resolution imageries are not available. However, the 10-meter resolution has a limited number of bands (Blue, Green, Red and Near-Infrared). This limitation reduces the spectral depth and often poses challenges in processing and disseminating the objects that have similar classes such as vegetation and forest. Therefore, this study evaluates the performance of the commonly used pixel-based classification technique under the limited spectral conditions. The findings provide practical guide for planners, researchers or even practitioners who rely solely on 10-meter resolution from Sentinel 2 to support their operational needs.