Abstract
As the world's second-largest rice exporter, Vietnam's monitoring of land cover changes and carbon stock estimation is crucial for achieving its carbon neutrality goals amidst deforestation and industrial upgrading. This study developed a new land cover classification method based on the phenological characteristics of rice, using the Google Earth Engine (GEE). The method significantly improves the identification accuracy of farmland by extracting rice phenological bands from Sentinel-1 radar data and Sentinel-2 multispectral data. Carbon stock data from 2015 to 2023 were generated using the InVEST model, and their spatial-temporal variations were analyzed. Additionally, the driving factors behind the changes in carbon stocks in forests, grasslands, and croplands were quantitatively explored using the geographic detector(Geo-Detector). The results show that: (1) The classification method for land cover created in this research exhibits greater accuracy than the European Space Agency (ESA) global land cover map and the Japan Aerospace Exploration Agency (JAXA) forest/non-forest maps from Japan, achieving an overall classification accuracy that surpasses 90%. This method also addresses the issue of low identification accuracy of croplands in traditional methods. (2) From 2015 to 2023, Vietnam's LULC changes were mainly characterized by decreases in forests and croplands, and increases in grasslands, construction land, bare land, and water bodies. (3) Overall, natural factors have a greater influence on LULC distribution in Vietnam than human activities, with slope being the most influential factor, followed by altitude, temperature, and population. (4) The main factors affecting the reduction of forest and cropland areas were slope, altitude, and population, while the main factors influencing the changes in construction land area were population and the economy. (5) Vietnam's average carbon stock from 2015 to 2023 was 2.312 billion tons, with an average annual change rate of - 0.63%. Accurate identification of land cover types is a prerequisite for precise carbon stock estimation, and accurate carbon stock estimates are crucial for advancing Vietnam's carbon neutrality goals.