一种基于多源遥感数据的GDP空间化方法
By establishing a spatial model of GDP using multi-source remote sensing data, the problem of low fitting accuracy of GDP spatialization in existing technologies has been solved, enabling an accurate reflection of regional GDP spatial differences and supporting economic research and regulation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HEFEI UNIV OF TECH
- Filing Date
- 2022-08-24
- Publication Date
- 2026-07-17
AI Technical Summary
Most existing methods for analyzing the spatial distribution of GDP use nighttime light data to build single-factor models, which have low fitting accuracy and cannot effectively reflect the spatial differences in regional GDP.
A method based on multi-source remote sensing data was adopted. By acquiring correlation data of the study area, and after preprocessing, a GDP spatialization model was established using principal component analysis and random forest algorithm. Principal correlation factors were assigned and gridded to obtain the GDP spatialization results.
It can more quickly and accurately reflect the GDP of local areas and the differences within the region, providing data support for regional economic development regulation and sustainable resource development.
Smart Images
Figure CN115391624B_ABST