JOURNAL ARTICLE
Ecological Suitability Evaluation Method of Low-Carbon Urban Planning Based on Big Data Technology.
Published In: International Journal of High Speed Electronics & Systems, 2025, v. 34, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Wang, Nan; Li, Si-Meng; Cui, Tong 3 of 3
Abstract
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. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of High Speed Electronics & Systems. 2025/03, Vol. 34, Issue 1, p1
- Document Type:Article
- Subject Area:Politics and Government
- Publication Date:2025
- ISSN:0129-1564
- DOI:10.1142/S012915642540347X
- Accession Number:184145734
- Copyright Statement:Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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