Systematic Review on Spatial Change Detection Using NDVI in Google Earth Engine

Objective: The objective of this study is to investigate the scientific production related to environmental change detection using the NDVI index within the Google Earth Engine (GEE) environment, aiming to identify trends, gaps, and relevant contributions in the field.   Theoretical Framework: To investigate the scientific production related to environmental change detection using the NDVI index within the Google Earth Engine (GEE) environment, aiming to identify trends, gaps, and relevant contributions.   Method: The fundamentals of remote sensing, the application of NDVI in analyzing vegetation cover changes, change detection techniques, and the use of GEE for processing large volumes of geospatial data are presented.   Results and Discussion: The results highlight the predominance of NDVI use in change detection studies with GEE, especially in deforestation and land use applications. The study identified thematic and geographic gaps and methodological limitations, such as reliance on the Scopus database.   Research Implications: The research contributes to advancing the understanding of GEE with NDVI for change detection, particularly in contexts under high anthropogenic pressure.   Originality/Value: The study stands out for its systematic application of ProKnow-C, offering an innovative approach for mapping trends and gaps in remote sensing research.