UDC 332.68
This study proposes an integrated solution on the Google Earth Engine (GEE) cloud platform aimed at streamlining the organizational structure and optimizing land‐management procedures in the Socialist Republic of Viet Nam. First, a comprehensive assessment of existing governance models was conducted to identify “bottlenecks” within the three‐tier system (central - provincial - communal). Based on these findings, a new two‐tier framework was developed, establishing a single Central Land Authority and reducing the local administrative hierarchy to provincial and communal levels. The automated classification method for Sentinel-2 satellite imagery, employing a Random Forest algorithm and implemented directly in the GEE environment, demonstrated the ability to accelerate data processing by up to 60%, increase land‐use classification accuracy to 92%, and provide near real‐time visualizations of land‐use dynamics. The resulting thematic maps will serve as valuable reference materials for experts at the Ministry of Agriculture and Rural Development, enabling the timely updating of cadastral data and the formulation of scientifically grounded recommendations for precisely and effectively adjusting land‐use policy.
Google Earth Engine, land monitoring, automated classification, organizational reform, transparency, Viet Nam
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