Spatial–temporal analysis of urban ecological comfort index derived from remote sensing data: a case study of Hefei, China

Li, Xinghua; Zhang, Hongyi; Yu, Junbo; Gong, Yuting; Guan, Xiaobin; Li, Shuang

doi:10.1117/1.jrs.15.042403

Cited by 13 publications

(3 citation statements)

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“…It also predicted the ecological environment of Beijing in 2025 and pointed out that the ecological environment of Beijing would significantly improve by then. Literature [18] proposed an effective, integrated remote sensing-based urban ecological environment evaluation method, took Hefei as the research object, and confirmed that the UECI of Hefei City was significantly improved from 2003 to 2019 according to the simulated numerical algorithm. Literature [19] empirically discusses the selection of community energy projects from the perspective of energy use, using renewable energy cooperatives as an example.…”

Section: Introductionmentioning

confidence: 85%

Exploration of Community Governance Paths in Urban Ecosystems Based on KANO-IPA Modeling

Tan,

Huang

2024

Applied Mathematics and Nonlinear Sciences

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This paper focuses on the research object of urban ecological environment governance on the urban community at the micro level, and pays attention to the problem of the realization path of urban community environment governance. The KANO-IPA model is established to study the urban ecological environment and the needs of community residents, and the importance of the survey data is evaluated by combining the theory of rough numbers to construct the community governance path of the urban ecological environment. The model analyzes the ecological environment of City H in Province A, and 10 communities are governed using the governance path constructed in this paper. The coal industry in City H dominates the economic development, and the total particulate emissions in the city will be 107,173.10 tons in 2021, and the contribution of the industrial emissions to the dustfall of heavy metal Ni will be 77.96%, and at the same time, there is a serious problem of arbitrary tampering with the data of ecological governance. The community governance path constructed in this paper achieves about 80% of resident satisfaction in 10 communities in H city. The governance path proposed by this study can be recognized by residents of the community and is expected to improve the ecological environment of the city.

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Section: Introductionmentioning

confidence: 85%

Exploration of Community Governance Paths in Urban Ecosystems Based on KANO-IPA Modeling

Tan,

Huang

2024

Applied Mathematics and Nonlinear Sciences

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“…In this regard, there have been some research results. For example, people can integrate big data to scientifically evaluate the ecological quality of their environment [11,12]. Even so, people can use big data to realize real-time management of cities [13].…”

Section: Methods In Terms Of Research Methods This Study Integrates T...mentioning

confidence: 99%

The Evolution of Ecological and Environmental Governance Attention Allocation in J City Based on Big Data Analysis

Gao

Sun

2022

Discrete Dynamics in Nature and Society

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Analysing the evolution process of attention allocation in city governance is an effective way to understand modern governance. Among the city types, heavy industry cities are special cities. It relies too much on heavy industry and is difficult to achieve ecological and environmental governance. This study takes J City in Northeast China as an example. Based on big data analysis, this study analyses the evolution process of governance attention allocation in J City. It can be found that the realization of ecological and environmental governance requires people’s participation. City development needs multiple synergies and an ecosystem-led governance model. However, this process is not a subjective product but needs to be promoted by history. Fundamentally, people need to change the logic of economic development.

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“…Taking Jingmen, Hubei Province, the representative of the "third-line" construction, as an example, an ecological restoration technology of "problem identifcation network construction task screening" is put forward. Li et al [4] have taken Hefei, China as an example and proposed a spatiotemporal analysis method of urban ecological comfort index based on remote sensing data. Harmonic analysis using time series method and spatiotemporal information fusion based on nonlocal mean fltering improved the quality of long-term remote sensing data from 2003 to 2019.…”

Section: Introductionmentioning

confidence: 99%

Urban Ecological Planning Model Based on Information Entropy and Meteorological Suitability Evaluation Algorithm

2023

Mathematical Problems in Engineering

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In order to improve the effect of regional urban ecological planning and ecological restoration, aiming at the problem of low accuracy of ecological planning and poor matching with the current situation, taking Yucheng County, Shangqiu City, Henan Province as an example, an urban ecological planning model based on information entropy and meteorological suitability evaluation algorithm is designed. The geographical environment of Yucheng County, Shangqiu City, Henan Province is analyzed. Based on the current situation of regional ecological environment, the meteorological suitability evaluation algorithm is introduced to establish the urban ecological planning model. Comprehensively considering land planning factors and meteorological factors, calculate the information entropy of each influencing factor, determine the weight, and optimize the ecological planning model. The experimental results show that this method has achieved good results in the accuracy of ecological planning and the matching degree of the current situation in the urban ecological planning of Yucheng County, Shangqiu City, Henan Province.

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Spatial–temporal analysis of urban ecological comfort index derived from remote sensing data: a case study of Hefei, China

Cited by 13 publications

References 0 publications

Exploration of Community Governance Paths in Urban Ecosystems Based on KANO-IPA Modeling

Exploration of Community Governance Paths in Urban Ecosystems Based on KANO-IPA Modeling

The Evolution of Ecological and Environmental Governance Attention Allocation in J City Based on Big Data Analysis

Urban Ecological Planning Model Based on Information Entropy and Meteorological Suitability Evaluation Algorithm

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