Garden Landscape Design of Sponge City Residential Area Based on Digital Technology

Sun, YunJuan; Jiang, Fang

doi:10.1155/2022/3684422

Cited by 1 publication

(3 citation statements)

References 19 publications

(18 reference statements)

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“…Neural network models can play a positive role in predicting the ecological emergy of building projects, similar to architectural engineering. While some scholars have conducted neural network evaluations for various aspects of building projects [43][44][45][46], research on the sustainable ecological energy value of landscape architecture is still in its early stages. This paper represents a forward-looking exploration of this aspect.…”

Section: Neural Network Model Prediction Analysismentioning

confidence: 99%

“…The efficiency of this aspect has been confirmed by relevant scholars. For specific details, please refer to references [45][46][47]. The main improvement measures in this section involve selecting three types o sponge city practice.…”

Section: Coupled Design Of the Sponge City Conceptmentioning

confidence: 99%

“…The efficiency of this aspect has been confirmed by relevant scholars. For specif details, please refer to references [45][46][47].…”

Section: Coupled Design Of the Sponge City Conceptmentioning

confidence: 99%

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Environmental Sustainability Study of Urban Waterfront Landscapes Based on the LCA–Emergy–Carbon Footprint and Artificial Neural Network Method

Jiang,

Zuo,

Asutosh

et al. 2024

Buildings

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The ecological landscape design of urban rivers plays a crucial role in mitigating the urban heat island effect and preserving urban ecology. This study focuses on the construction process data of key landscape nodes along Nanjing’s urban rivers. By employing a whole life cycle emergy approach and carbon emission method, the sustainable changes in the landscape system are quantitatively assessed. Furthermore, artificial neural networks have been used to conduct long-term sustainability analysis and predictions for the landscape system. The research findings reveal that over time, the maintenance investment in landscape projects gradually becomes dominant, increasing from 2% in the first year to approximately 75% after 30 years. This phenomenon signifies a decline in the efficiency of the landscape system. Sustaining the ecological balance of the landscape system necessitates continuous inputs of material flow, energy flow, and information flow. The major contributors to carbon emissions in the landscape engineering system are diesel fuel, cement, and steel. This highlights opportunities for sustainable improvement from a low-carbon perspective. To enhance the ecological sustainability of urban waterfront landscapes, three measures are proposed: sponge city construction concepts, coupled sewage treatment systems, and information flow monitoring systems. The effectiveness of these measures was preliminarily validated.

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Section: Neural Network Model Prediction Analysismentioning

confidence: 99%

Section: Coupled Design Of the Sponge City Conceptmentioning

confidence: 99%