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Multi-Source Sensing of Urban Ecosystem and Sustainability

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 7683

Special Issue Editors

State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Interests: urban ecosystem; internet of things; remote sensing; sustainable development; GIS
Linköping University–Guangzhou University Research Center on Urban Sustainable Development, Guangzhou University, Guangzhou 510006, China
Interests: freshwater ecology; bivalve; biomanipulation; ecological restoration; river-chief system
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Interests: urban ecology; GIS; spatialtemporal big data; machine learning

Special Issue Information

Dear Colleagues,

Alongside with rapid urbanization and population expansion, public-health problems and socio-economic impact have raised concerns on urban livability and sustainability. Therefore, developing towards a long-term sustainable urban environment is an urgent task for government agencies and scientists. Prof. Zhao pioneered the scientific discipline of "Landsenses ecology" (Zhao et al., 2020), which aimed at people's subjective perceptions of security, beauty, and happiness. We would like to ask, do people familiar with their daily habitat? Furthermore, how to use frontier technologies to solve the problem of sustainable development? Especially the vision, smell, voice, feeling, happiness, or other human-oriented physical and psychological perspectives. 

The city is a complex social-economic-natural ecosystem. Enormous efforts have been devoted to a smarter, greener, and more livable cities. A smart and efficient urban sensing system, with the emerging technologies in GIS, remote sensing, crowdsourcing, machine learning, and other multi-source sensors to obtain a full view of the urban ecosystem are the basis for its success.   

This Special Issue will comprise a selection of papers presenting original and innovative contributions in the field of multi-source sensing research, including the Internet of Things and Landsenses ecology, Artificial Intelligence, sustainable greenspace systems, Spatialtemporal big data, and innovative use cases of such technologies in socio-cultural, political, environmental, and legal considerations. Empirical research involving innovative methods are also welcomed. 

The particular topics of interest include, but are not limited to the following:

  • Landsenses ecology
  • Multi-source data fusion
  • The Internet of Things or Artificial Intelligence applications
  • Sustainable greenspace systems
  • Healthy and sustainable living environment
  • Socio-cultural, political, economic, environmental, or legal considerations
  • urban ecological planning and management for SDGs goals
  • urban greening and public health

Dr. Rencai Dong
Dr. Yuxian Liu
Dr. Yonglin Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • internet of things and landsenses ecology
  • artificial intelligence
  • Spatialtemporal big data

Published Papers (3 papers)

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Research

15 pages, 3748 KiB  
Article
Effect of Increasing C/N Ratio on Performance and Microbial Community Structure in a Membrane Bioreactor with a High Ammonia Load
by Huaihao Xu, Yuepeng Deng, Xiuying Li, Yuxian Liu, Shuangqiu Huang, Yunhua Yang, Zhu Wang and Chun Hu
Int. J. Environ. Res. Public Health 2021, 18(15), 8070; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18158070 - 30 Jul 2021
Cited by 4 | Viewed by 1799
Abstract
Herein, the responses of the operational performance of a membrane bioreactor (MBR) with a high ammonium-nitrogen (NH4+-N) load and microbial community structure to increasing carbon to nitrogen (C/N) ratios were studied. Variation in the influent C/N ratio did not affect [...] Read more.
Herein, the responses of the operational performance of a membrane bioreactor (MBR) with a high ammonium-nitrogen (NH4+-N) load and microbial community structure to increasing carbon to nitrogen (C/N) ratios were studied. Variation in the influent C/N ratio did not affect the removal efficiencies of chemical oxygen demand (COD) and NH4+-N but gradually abated the ammonia oxidization activity of sludge. The concentration of the sludge in the reactor at the end of the process increased four-fold compared with that of the seed sludge, ensuring the stable removal of NH4+-N. The increasing influent COD concentration resulted in an elevated production of humic acids in soluble microbial product (SMP) and accelerated the rate of membrane fouling. High-throughput sequencing analysis showed that the C/N ratio had selective effects on the microbial community structure. In the genus level, Methyloversatilis, Subsaxibacter, and Pseudomonas were enriched during the operation. However, the relative abundance of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) involved in nitrification declined gradually and were decreased by 86.54 and 90.17%, respectively, with influent COD increasing from 0 to 2000 mg/L. The present study offers a more in-depth insight into the control strategy of the C/N ratio in the operation of an MBR with a high NH4+-N load. Full article
(This article belongs to the Special Issue Multi-Source Sensing of Urban Ecosystem and Sustainability)
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15 pages, 635 KiB  
Article
A Psychological Perception Mechanism and Factor Analysis in Landsenses Ecology: A Case Study of Low-Carbon Harmonious Discourse
by Lan Zhang, Guowen Huang, Yongtao Li and Shitai Bao
Int. J. Environ. Res. Public Health 2021, 18(13), 6914; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18136914 - 28 Jun 2021
Cited by 5 | Viewed by 2313
Abstract
Landsenses ecology has been widely applied in research into sustainable consciousness and behavior and the notion of landsense creation realizes the unity of the macro physical senses and micro psychological perceptions. However, a great deal of current research about landsenses ecology has concentrated [...] Read more.
Landsenses ecology has been widely applied in research into sustainable consciousness and behavior and the notion of landsense creation realizes the unity of the macro physical senses and micro psychological perceptions. However, a great deal of current research about landsenses ecology has concentrated on the dimension of the physical senses, while there have been relatively few studies on the dimension of its psychological perception. This paper begins by clarifying the concept of self and explaining out that the psychological perception mechanism of landsense creation represents a process of guiding people to know themselves and realize their ecological self. It then utilizes the example of low-carbon discourse to explore the factors contributing to the resonance of ecological self-vision. Our results show that the perceived self-efficacy, environmental concern and environmental knowledge triggered by ecological discourse are the main factors contributing to the resonance of sustainable vision, thus clarifying the indicators of landsenses ecology at the level of psychological perception. Our purpose is to effectively guide the landsense creation of harmonious discourse and promote people to engage in potentially more sustainable behavior. Full article
(This article belongs to the Special Issue Multi-Source Sensing of Urban Ecosystem and Sustainability)
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16 pages, 2991 KiB  
Article
The Premium of Public Perceived Greenery: A Framework Using Multiscale GWR and Deep Learning
by Yonglin Zhang, Xiao Fu, Chencan Lv and Shanlin Li
Int. J. Environ. Res. Public Health 2021, 18(13), 6809; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18136809 - 24 Jun 2021
Cited by 8 | Viewed by 2328
Abstract
Population agglomeration and real estate development encroach on public green spaces, threatening human settlement equity and perceptual experience. Perceived greenery is a vital interface for residents to interact with the urban eco-environment. Nevertheless, the economic premiums and spatial scale of such greenery have [...] Read more.
Population agglomeration and real estate development encroach on public green spaces, threatening human settlement equity and perceptual experience. Perceived greenery is a vital interface for residents to interact with the urban eco-environment. Nevertheless, the economic premiums and spatial scale of such greenery have not been fully studied because a comprehensive quantitative framework is difficult to obtain. Here, taking advantage of big geodata and deep learning to quantify public perceived greenery, we integrate a multiscale GWR (MGWR) and a hedonic price model (HPM) and propose an analytic framework to explore the premium of perceived greenery and its spatial pattern at the neighborhood scale. Our empirical study in Beijing demonstrated that (1) MGWR-based HPM can lead to good performance and increase understanding of the spatial premium effect of perceived greenery; (2) for every 1% increase in neighborhood-level perceived greenery, economic premiums increase by 4.1% (115,862 RMB) on average; and (3) the premium of perceived greenery is spatially imbalanced and linearly decreases with location, which is caused by Beijing’s monocentric development pattern. Our framework provides analytical tools for measuring and mapping the capitalization of perceived greenery. Furthermore, the empirical results can provide positive implications for establishing equitable housing policies and livable neighborhoods. Full article
(This article belongs to the Special Issue Multi-Source Sensing of Urban Ecosystem and Sustainability)
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