Sentinel Series Applications on Urban Green Space: Current Progress and Future Research Pathway

Abstract

Green space is becoming increasingly recognized as a possible means of reducing heat island effects in urban contexts. Optimizing the advantages of urban green space (UGS) for metropolises and the urban environment broadly requires careful design and management. The creation of innovative remote sensing techniques for mapping and monitoring vegetation has drawn the attention of several researchers. This review is based on a comprehensive literature search, summarizing the primary strategies recommended for mapping UGS with high-resolution Sentinel-based remote sensing datasets, established on 96 studies and 2 reports published until 2024 September 21. Search engines such as Scopus, PubMed, Web of Science Core Collection, Semantic Scholar, and SciELO Citation Index are utilized. Urban areas still make it rare to have high spatial and temporal resolution imagery for obtaining phenological data to support mapping and species-level vegetation monitoring. Global research on UGS is very limited due to the limited time periods of Sentinel dataset availability (from 2015). This literature review contributes to the global body of knowledge on UGS analysis using Sentinel series datasets based on software applications, techniques, prior research on machine learning, and limitations.