多源数据融合在自然资源调查中的应用模式探索OACHSSCD

To address the limitations of traditional natural resource surveys,including restricted accuracy,low efficiency,and insufficient information representation from a single data source,an application model of multi-source data fusion for natural resource surveys was developed.A complete technical workflow was established,encompassing multi-source heterogeneous data acquisition and standardized preprocessing,spatiotemporal reference unification and geometric precise registration,multi-level data fusion and feature extraction for resource elements,as well as integrated output of survey results and accuracy quality control.A typical hilly and mountainous area was selected as the experimental site,where multi-source data,including optical remote sensing imagery,synthetic aperture radar,and light detection and ranging data,were integrated to conduct a land cover classification experiment.The results showed that the overall accuracy of the multi-source data fusion scheme reached 89.3%,with a Kappa coefficient of 0.86.The proposed approach effectively enhances the accuracy and reliability of natural resource survey results.