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Special Issue "Methodological Advances in Research on Sustainable Ecosystems"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 January 2018)

Special Issue Editors

Guest Editor
Assoc. Prof. Xinyue Ye

Department of Informatics, Urban Informatics & Spatial Computation Lab, New Jersey Institute of Technology, Newark, NJ 07102, USA
Website | E-Mail
Interests: GIS; spatial analysis; urban and regional modeling
Guest Editor
Prof. Dr. Yichun Xie

Department of Geography and Geology and Institute for Geospatial Research and Education, Eastern Michigan University, Ypsilanti, MI 48197, USA
Website | E-Mail
Fax: +1-(734) 487-5394
Guest Editor
Prof. Dr. Victor Mesev

Department of Geography, Florida State University, Tallahassee, FL 32306, USA
Website | E-Mail

Special Issue Information

Dear Colleagues,

Rapid urbanization means more economic and social human activities are affecting natural ecosystems. It also means more natural land is being converted into urban land use; with consequential detrimental impacts on the processes and functions of ecosystems. In developing countries, economic growth is prioritized ahead of environmental conservation, but unprecedented urban growth has triggered drastic land use conversion, either replacing natural landscapes with semi-natural mixtures or complete urban development. Inevitably, areas converted into urban land use have altered the structure, pattern, and functionality of the ecosystems. More research is needed on sustainable urban development; an approach that harmonizes the demand for urban encroachment with the preservation of delicate ecosystems.

This Special Issue plans to focus on “Methodological Advances in Research on Sustainable Ecosystems”. It is a topic with immense collaborative potential and interdisciplinary challenges for environmental scientists, ecologists, economists, and policy-makers. Building on a series of three successful annual conferences in the USA and China (http://www.jicredt.com/GSES2017/), this Special Issue will bring together leading scholars in related disciplines to share their research on the challenges and solutions of Methodological Advances in Sustainable Ecosystems Research. This Special Issue will be open to the submission of manuscripts from outside the conference as well, provided that they fit within the scope of the Special Issue. Submitted manuscripts will need to be full-length papers that have not been previously published in a substantially-similar format. In addition, all manuscripts will need to be reviewed through electronic Manuscript Tracking System and according to the same editorial guidelines as all other submitted manuscripts.

Appropriate topics include, but are not limited to:

  • Advanced geo-computational ecosystems modelling

  • Creation of new visualization products that increase the understanding of large and diverse forms of ecosystems information

  • Discovery of patterns in large volumes of ecosystems data through analytic techniques such as data mining and predictive analytics in applications

  • Ecological, environmental and socioeconomic modeling and coupling

  • LULC change

  • Smart city and geo-design

  • Technological advances in hardware, storage, data management, networking and computing models, such as visualization and cloud computing for ecosystems applications

Prof. Dr. Xinyue Ye
Prof. Dr. Yichun Xie
Prof. Dr. Victor Mesev
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 papers will be 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. Sustainability 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 1400 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.

Published Papers (9 papers)

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Research

Open AccessArticle Spatial Pattern and Regional Relevance Analysis of the Maritime Silk Road Shipping Network
Sustainability 2018, 10(4), 977; https://doi.org/10.3390/su10040977
Received: 31 January 2018 / Revised: 23 March 2018 / Accepted: 26 March 2018 / Published: 27 March 2018
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Abstract
Under the strategy of “One Belt and One Road”, this paper explores the spatial pattern and the status quo of regional trade relevance of the Maritime Silk Road shipping network. Based on complex network theory, a topological structure map of shipping networks for
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Under the strategy of “One Belt and One Road”, this paper explores the spatial pattern and the status quo of regional trade relevance of the Maritime Silk Road shipping network. Based on complex network theory, a topological structure map of shipping networks for containers, tankers, and bulk carriers was constructed, and the spatial characteristics of shipping networks were analyzed. Using the mode of spatial arrangement and the Herfindahl–Hirschman Index, this paper further analyzes the traffic flow pattern of regional trade of three kinds of goods. It is shown that the shipping network of containers, tankers and bulk carriers are unevenly distributed and have regional agglomeration phenomena. There is a strong correlation between the interior of the region and the adjacent areas, and the port competition is fierce. Among them, the container ships network is the most competitive in the region, while the competitiveness of the tankers network is relatively the lowest. The inter-regional correlation is weak, and a few transit hub ports have obvious competitive advantages. The ports in Northeast Asia and Southeast Asia are the most significant. The research results combined with the Maritime Silk Road policy can provide reference for port construction, route optimization, and coordinated development of regional trade, which will help to save time and cost of marine transportation, reduce energy consumption, and promote the sustainable development of marine environment and regional trade on the Maritime Silk Road. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle A Parallel and Optimization Approach for Land-Surface Temperature Retrieval on a Windows-Based PC Cluster
Sustainability 2018, 10(3), 621; https://doi.org/10.3390/su10030621
Received: 14 January 2018 / Revised: 20 February 2018 / Accepted: 22 February 2018 / Published: 28 February 2018
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Abstract
Land-surface temperature (LST) is a very important parameter in the geosciences. Conventional LST retrieval is based on large-scale remote-sensing (RS) images where split-window algorithms are usually employed via a traditional stand-alone method. When using the environment to visualize images (ENVI) software to carry
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Land-surface temperature (LST) is a very important parameter in the geosciences. Conventional LST retrieval is based on large-scale remote-sensing (RS) images where split-window algorithms are usually employed via a traditional stand-alone method. When using the environment to visualize images (ENVI) software to carry out LST retrieval of large time-series datasets of infrared RS images, the processing time taken for traditional stand-alone servers becomes untenable. To address this shortcoming, cluster-based parallel computing is an ideal solution. However, traditional parallel computing is mostly based on the Linux environment, while the LST algorithm developed within the ENVI interactive data language (IDL) can only be run in the Windows environment in our project. To address this problem, we combine the characteristics of LST algorithms with parallel computing, and propose the design and implementation of a parallel LST retrieval algorithm using the message-passing interface (MPI) parallel-programming model on a Windows-based PC cluster platform. Furthermore, we present our solutions to the problems associated with performance bottlenecks and fault tolerance during the deployment stage. Our results show that, by improving the parallel environment of the storage system and network, one can effectively solve the stability issues of the parallel environment for large-scale RS data processing. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle An Ontology-Underpinned Emergency Response System for Water Pollution Accidents
Sustainability 2018, 10(2), 546; https://doi.org/10.3390/su10020546
Received: 23 January 2018 / Revised: 17 February 2018 / Accepted: 17 February 2018 / Published: 20 February 2018
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Abstract
With the unceasing development and maturation of environment geographic information system, the response to water pollution accidents has been digitalized through the combination of monitoring sensors, management servers, and application software. However, most of these systems only achieve the basic and general geospatial
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With the unceasing development and maturation of environment geographic information system, the response to water pollution accidents has been digitalized through the combination of monitoring sensors, management servers, and application software. However, most of these systems only achieve the basic and general geospatial data management and functional process tasks by adopting mechanistic water-quality models. To satisfy the sustainable monitoring and real-time emergency response application demand of the government and public users, it is a hotspot to study how to make the water pollution information being semantic and make the referred applications intelligent. Thus, the architecture of the ontology-underpinned emergency response system for water pollution accidents is proposed in this paper. This paper also makes a case study for usability testing of the water ontology models, and emergency response rules through an online water pollution emergency response system. The system contributes scientifically to the safety and sustainability of drinking water by providing emergency response and decision-making to the government and public in a timely manner. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns
Sustainability 2018, 10(2), 316; https://doi.org/10.3390/su10020316
Received: 26 December 2017 / Revised: 18 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
Cited by 1 | PDF Full-text (1173 KB) | HTML Full-text | XML Full-text
Abstract
Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is
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Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regression (BLR), but fully considers the spatio-temporally localized spatial associations or characterization of neighborhood interactions (NIs) in the patterns of grassland vegetation. The BLR-NIs model was applied to a modeled vegetation degradation of grasslands in the Xilin river basin, Inner Mongolia, China. Residual trend analysis on the normalized difference vegetation index (RESTREND-NDVI), which excluded the climatic impact on vegetation dynamics, was adopted as a preprocessing step to derive three human-induced trajectory patterns (vegetation degradation, vegetation recovery, and no significant change in vegetation) during two consecutive periods, T1 (2000–2008) and T2 (2007–2015). Human activities, including livestock grazing intensity and transportation accessibility measured by road network density, were included as explanatory variables for vegetation degradation, which was defined for locations if vegetation recovery or no significant change in vegetation in T1 and vegetation degradation in T2 were observed. Our work compared the results of BLR-NIs and the traditional BLR model that did not consider NIs. The study showed that: (1) both grazing intensity and road density had a positive correlation to vegetation degradation based on the traditional BLR model; (2) only road density was found to positively correlate to vegetation degradation by the BLR-NIs model; NIs appeared to be critical factors to predict vegetation degradation; and (3) including NIs in the BLR model improved the model performance substantially. The study provided evidence for the importance of including localized spatial associations between the trajectory patterns for mapping vegetation degradation, which has practical implications for designing management policies to counterpart grassland degradation in arid and semi-arid areas. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China
Sustainability 2018, 10(1), 149; https://doi.org/10.3390/su10010149
Received: 14 November 2017 / Revised: 4 January 2018 / Accepted: 8 January 2018 / Published: 9 January 2018
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Abstract
The loss of lake area significantly influences the climate change in a region, and this loss represents a serious and unavoidable challenge to maintaining ecological sustainability under the circumstances of lakes that are being filled. Therefore, mapping and forecasting changes in the lake
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The loss of lake area significantly influences the climate change in a region, and this loss represents a serious and unavoidable challenge to maintaining ecological sustainability under the circumstances of lakes that are being filled. Therefore, mapping and forecasting changes in the lake is critical for protecting the environment and mitigating ecological problems in the urban district. We created an accessible map displaying area changes for 82 lakes in the Wuhan city using remote sensing data in conjunction with visual interpretation by combining field data with Landsat 2/5/7/8 Thematic Mapper (TM) time-series images for the period 1987–2013. In addition, we applied a quadratic exponential smoothing model to forecast lake area changes in Wuhan city. The map provides, for the first time, estimates of lake development in Wuhan using data required for local-scale studies. The model predicted a lake area reduction of 18.494 km2 in 2015. The average error reached 0.23 with a correlation coefficient of 0.98, indicating that the model is reliable. The paper provided a numerical analysis and forecasting method to provide a better understanding of lake area changes. The modeling and mapping results can help assess aquatic habitat suitability and property planning for Wuhan lakes. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Spatial-Temporal Dynamics of the Economic Efficiency of Construction Land in the Pearl River Delta Megalopolis from 1998 to 2012
Sustainability 2018, 10(1), 63; https://doi.org/10.3390/su10010063
Received: 14 November 2017 / Revised: 26 December 2017 / Accepted: 27 December 2017 / Published: 28 December 2017
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Abstract
Since the 1980s, the rapid, extensive, and dispersed urban expansion in the Pearl River Delta megalopolis (PRDM) has led to landscape fragmentation and the inefficient use of construction land. Like other developed regions in China that are subject to the dual challenges of
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Since the 1980s, the rapid, extensive, and dispersed urban expansion in the Pearl River Delta megalopolis (PRDM) has led to landscape fragmentation and the inefficient use of construction land. Like other developed regions in China that are subject to the dual challenges of shortages of construction land and deterioration of the ecological environment, it is becoming increasingly important in the PRDM to improve the land-use efficiency of urban construction. However, current methods for assessing land-use efficiency do not meet the emerging needs of land-use planning and policymaking. Therefore, using the American Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) nighttime light imagery and Landsat TM data, this study aims to develop a timely and efficient approach to model the high-resolution economic efficiency of construction land (EECL). With this approach, we mapped the reliable EECL of the PRDM at township level and with a one-kilometer grid. Next, the study compared the temporal changes and revealed the spatial-temporal dynamics in order to provide a scientific reference for informed land-use planning and policymaking. The results show that since 1998, the economic efficiency of construction land in the PRDM increased in general but varied significantly throughout the area. Further, these disparities widened from 1998 to 2012 between the PRDM’s inner and peripheral circles. Only one-fifth of the towns and subdistricts were categorized as fast-growth or ultrafast-growth, with the majority located in the most developed areas of the PRDM’s inner circle. In order to improve the efficiency of construction land in the PRDM and realize sustainable development, differentiated land-use policies for the inner and peripheral circles were proposed. The inner circle should focus on promoting the efficiency of existing construction land and encourage urban renewal, while the peripheral circle should enhance the control of new construction land and improve its efficiency. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Low-Carbon Transportation Oriented Urban Spatial Structure: Theory, Model and Case Study
Sustainability 2018, 10(1), 19; https://doi.org/10.3390/su10010019
Received: 29 October 2017 / Revised: 29 November 2017 / Accepted: 14 December 2017 / Published: 22 December 2017
Cited by 1 | PDF Full-text (4577 KB) | HTML Full-text | XML Full-text
Abstract
Optimising the spatial structure of cities to promote low-carbon travel is a primary goal of urban planning and construction innovation in the low-carbon era. There is a need for basic research on the structural characteristics that help to reduce motor traffic, thereby promoting
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Optimising the spatial structure of cities to promote low-carbon travel is a primary goal of urban planning and construction innovation in the low-carbon era. There is a need for basic research on the structural characteristics that help to reduce motor traffic, thereby promoting energy conservation. We first review the existing literature on the influence of urban spatial structure on transport carbon dioxide emissions and summarise the influence mechanisms. We then present two low-carbon transportation oriented patterns of urban spatial structure including the traditional walking city and the modern transit metropolis, illustrated by case studies. Furthermore, we propose an improved model Green Transportation System Oriented Development (GTOD), which is an extension of traditional transit-oriented development (TOD) and includes the additional features of a walking city and an emphasis on the integration of land use with a green transportation system, consisting of the public transportation and non-auto travel system. A compact urban form, effective mix of land use and appropriate scale of block are the basic structural features of a low-carbon transportation city. However, these features are only effective at promoting low-carbon transportation when integrated with the green traffic systems. Proper integration of the urban structural system with the green space system is also required. The optimal land use/transportation integration strategy is to divide traffic corridors with wedge-shaped green spaces and limit development along the transit corridors. This strategy forms the basis of the proposed urban structural model to promote low-carbon transportation and sustainable urban growth management. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Mapping Fine Spatial Resolution Precipitation from TRMM Precipitation Datasets Using an Ensemble Learning Method and MODIS Optical Products in China
Sustainability 2017, 9(10), 1912; https://doi.org/10.3390/su9101912
Received: 13 September 2017 / Revised: 16 October 2017 / Accepted: 19 October 2017 / Published: 23 October 2017
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Abstract
Precipitation data are important for the fields of hydrology and meteorology, and are fundamental for ecosystem monitoring and climate change research. Satellite-based precipitation products are already able to provide high temporal resolution precipitation information at a global level. However, the coarse spatial resolution
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Precipitation data are important for the fields of hydrology and meteorology, and are fundamental for ecosystem monitoring and climate change research. Satellite-based precipitation products are already able to provide high temporal resolution precipitation information at a global level. However, the coarse spatial resolution has restricted their use in regional level studies. In this study, monthly fine spatial resolution land precipitation data in China was obtained by downscaling the TRMM 3B43 V7 monthly precipitation products. The downscaling model was constructed based on the ensemble learning method called random forest (RF). In addition to the RF model, the classification and regression tree (CART) model was also used to downscale the precipitation data for the purpose of comparison. The results were validated with in situ measurements. Results showed that the RF model outperformed the CART model. The downscaled precipitation data were strongly correlated with the in situ measurements. The downscaling method was applied to mapping fine spatial resolution precipitation over all of China, and is valuable for developing high spatial resolution precipitation products for studies on hydrology, meteorology, and climate science. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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Open AccessArticle Notifiable Sexually Transmitted Infections in China: Epidemiologic Trends and Spatial Changing Patterns
Sustainability 2017, 9(10), 1784; https://doi.org/10.3390/su9101784
Received: 31 August 2017 / Revised: 25 September 2017 / Accepted: 28 September 2017 / Published: 1 October 2017
Cited by 2 | PDF Full-text (3183 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Sexually transmitted infections (STIs) have become one of the major public health threats to the sustainable development of human beings. Among all of the STIs in China, three are listed as the notifiable infectious diseases, i.e., gonorrhea, syphilis, and HIV/AIDS, which demand more
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Sexually transmitted infections (STIs) have become one of the major public health threats to the sustainable development of human beings. Among all of the STIs in China, three are listed as the notifiable infectious diseases, i.e., gonorrhea, syphilis, and HIV/AIDS, which demand more attention. This study aims to detect, describe, and compare the spatial-temporal clustering of these notifiable STIs in China and to relate spatial analysis results to epidemiologic trends during the past decade. A descriptive epidemiology analysis and a spatial autocorrelation analysis (global and local) are adopted to study the epidemiologic trends and spatial changing patterns of STIs respectively. The results indicated that there were regional disparities and spatial clusters in the spatial distribution of notifiable STIs in China. However, the incidence rates of the three notifiable STIs displayed relatively different characteristics in epidemiologic trends and the agglomeration level. Overall, the Yangtze River Delta region, the southwestern border area, and some other border regions are the places demanding more attention. In the end, we propose a three-dimensional prevention and control strategy, which focuses on not only the most-at-risk populations, but also the most-at-risk areas and most-at-risk timings. Besides, some measures targeting more than one STI should also be formulated. Full article
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
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