Ecological Suitability Evaluation Method of Low-Carbon Urban Planning Based on Big Data Technology

The ecological suitability evaluation of low-carbon urban planning is affected by the irregular distribution of ground buildings, resulting in low evaluation accuracy. Therefore, the ecological suitability evaluation method of low-carbon urban planning based on big data technology is proposed. The joint feature detection method of building and block data is used to realize visual remote sensing detection of low-carbon urban spatial planning. The collected remote sensing images of low-carbon urban spatial planning are vertically connected, spatially embedded, vertically stacked, and spatial planning parameters are extracted. The edge contour detection and feature clustering analysis of the remote sensing images of low-carbon urban spatial planning are carried out. It realizes the irregular point marking of the low-carbon city ecological adaptability spatial image and the fusion processing of the multi-spectral image and the full-color image, so as to generate the change detection map of the low-carbon city planning ecological suitability evaluation, and realize the optimization evaluation of the low-carbon city ecological adaptability space through the distribution of the detection map. The experiment shows that the accuracy of ecological suitability evaluation of low-carbon city planning using this method is high, and the model parameter detection effect of urban building space matching is good, which improves the evaluation ability of ecological suitability space of low-carbon city.