# Monitoring Land Cover Change on a Rapidly Urbanizing Island Using Google Earth Engine
## 5 Conclusions  
Satellite classification has most often been used to document environmental losses in the face of urbanization. This study is unique because it provides an efficient methodology for temporal land use classification and forest detection for island environments while showing combined reforestation and urbanization over time. Google Earth Engine was used to classify Landsat satellite images to track land cover change for Haitan Island from 1990 to 2019. A multi-temporal, remote sensing database was instantly available via GEE's data library and cloud computing environment, which provides access to high-throughput computing at no cost for noncommercial uses. Image analysis in GEE showed that Haitan Island experienced a dramatic land cover change from 1990 to 2019. User and producer accuracies were consistently higher than 80% for the classified images. The overall accuracy and Kappa coefficient values ranged from 88.43% to 91.08% and 0.86 to 0.90, respectively. The results showed that over the past 30 years (1990-2019) Haitan Island has experienced an increase in forest land (30.94%) and built-up land (30.70%) and a decrease in cultivated land (13.63%) and sandy land (3.76%) in the study area. In general, LULC experienced a significant change, which may be due to socio-economic factors (e.g., population growth, anthropogenic activities), policy decision making (fast-growing economy and reforestation), and physical factors. The increases in the forest area show that the reforestation efforts have been successful even though there has been increased urbanization. These reforestation efforts are particularly important in this island environment where the trees serve as sand-control and  
Figure 8: Cultivated land in the north and west of Haitan Island: (**a**) fallow season, Landsat image obtained in April 2020, (**b**) growing season, Landsat image obtained in June 2020 (subset of Landsat 8 OLI, shown with band 5, 4, and 3 in red, green, and blue).  
windbreaks. Continuous monitoring of island environments and sustainability, in the face of climate change and population pressures, using GEE and satellite image classification helps regionalized land-use policy-making and represents an important example for other island environments that may face similar issues. Future analysis can be enhanced by using science-based \"forests\" category, which includes differentiating by the type of forests (e.g., native, non-native, etc.) and economic analysis of drivers in changes between native and non-native forests.  
Conceptualization, methodology and software, L.L. and Z.H.; investigation, K.Y. and L.Y.; data curation, writing--original draft preparation and visualization, L.L.; writing--review and editing, C.J.P. and E.A.M.; supervision, project administration, J.L.; funding acquisition, J.L. and K.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Major Science and Technology Projects of China, grant number 2018 YED060010304, Fujian Provincial Department of Science and Technology, grant number 2019N5012, and the scholarship program of China Scholarship Council, grant number 201908350124.  
We wish to thank the anonymous reviewers and editors for their professional comments and suggestions. We also want to thank [PERSON] and [PERSON] for technical support in Figure 5.  
The authors declare no conflict of interest.