Journal of Geo-information Science

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Exploring Urban Renewal Consumption: A Rapid Estimation Method for Annual Urban Construction Waste Production Based on High-Resolution Remote Sensing Images

HUANG Lei, LIN Shaofu, LIU Xiliang, WANG Shaohua, CHEN Guihong, MEI Qiang

Journal of Geo-information Science, 2024, 26(9): 2192-2212. DOI: 10.12082/dqxxkx.2024.240199

Fig. 1 Overall system architecture for calculating annual production of construction waste

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Fig. 2 MS-FF-AENet network structure
Fig. 3 The detailed structure of the dual attention mechanism module (DAMM)
Tab. 1 Types of layers and corresponding heights for landfill construction
Fig. 4 Overview of the study area and data sources
Fig. 5 Part of the experimental data set images and labels
Tab. 2 Definition table for the confusion matrix for building and construction waste extraction
Tab. 3 Quantitative evaluation of different models on a dataset of buildings in Changping District, Beijing (%)
Fig. 6 Extraction results of different models on building dataset in Changping District, Beijing
Tab. 4 Quantitative evaluation of different models on construction waste disposal sites dataset (%)
Fig. 7 Extraction results of different models on construction waste disposal sites dataset
Tab. 5 Results of ablation experiments on construction waste disposal sites dataset (%)
Tab. 6 Results of ablation experiments on building dataset in Changping District, Beijing (%)
Tab. 7 Time complexity assessment results for different methods
Fig. 8 Building extraction results in Changping District, Beijing
Fig. 9 Change in the building area of each administrative area in Changping District, Beijing
Tab. 8 Changes in building area and construction waste production in Changping District, Beijing
Tab. 9 Extraction results of construction waste disposal sites in Changping District, Beijing (m²)
Fig. 10 The area of each area within the construction waste disposal sites in Changping District, Beijing, in 2019 and 2020
Tab. 10 Calculation of construction waste landfill volume
Fig. 11 Error recognition case study

模态框（Modal）标题

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