Google Earth Engine and Its Application in Forest Sciences

In order to support sustainable forest management, it is essential to estimate the extent and change of forest cover and to evaluate the environmental and socio-economic impacts of forest dynamics. It is challenging, however, to calculate forest area on a large scale using traditional statistical survey methods. Access to satellite images make it feasible to monitor the Earth’s forest at different spatial and temporal resolutions. The Google Earth Engine (GEE) is a cloud computing platform, which provides data analysis toolkits to access and to handle remote sensing datasets easily and freely. GEE has been used to analyze environmental changes with the emphasis of forest monitoring. Through GEE’s platform, the user can monitor forest cover by investigating satellite images in different spatial and temporal resolutions with acceptable accuracy. Moreover, this platform’s impressive satellite image archives, coupled with sophisticated in-built processing and analyzing toolkits, immensely help remote sensing-based studies. Hence, a systematic review has been conducted here to survey those studies that have employed this platform for forest monitoring. According to the analysis, when it comes to forest monitoring, the GEE’s platform has been mainly used for two objectives, namely, classification and change detection. Random forest has been identified as the most popular classification method and spectral index difference has been the most efficient method for forest change detection while considering GEE limitation for image preprocessing. Overall, the survey’s result revealed how applying this platform for forest monitoring is trending.