Urban land planning monitoring based on IKONOS remote sensing and GIS integration

This research aims to construct an object-based planning monitoring method that integrates IKONOS high-resolution remote sensing and Geographic Information System spatial operators to attain integrated calculations of urban construction land identification, temporal change analysis, and planning compliance determination. First, multi-source data standardization is completed through geometric correction of rational function model and enhanced Gram-Schmidt fusion. Secondly, a model based on multi-scale objects is constructed to generate stable spatial units. A multi-dimensional feature encoding system that integrates spectral features, texture features, geometric features, and neighborhood relationship features is built. The IKONOS remote sensing and geographical information system integration framework is constructed to achieve unified calculation of category mapping, feature space difference and planning constraint embedding. The experimental results presented that in the three types of scenarios: industrial park, old urban area and urban-rural fringe, the minimum boundary offset was 3.1 ± 0.3 pixel. The average value of multi-temporal change intensity identification reached 0.72 ± 0.08, which was significantly better than that of the pixel difference method and the object-oriented change vector analysis method. The multi-feature coding system enhanced the overall accuracy from 0.580 to 0.935. The association analysis showed that CC had the strongest relationship with overall classification accuracy, while different land-use categories exhibited heterogeneous responses to variations in ERGAS.