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Geo-Informatics in Resource Management & Sustainable Ecosystem
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Geo-Informatics in Resource Management & Sustainable Ecosystem

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Resources and Sustainable Utilization".

Deadline for manuscript submissions: closed (30 December 2015) | Viewed by 38473

Special Issue Editors

Prof. Dr. Yichun Xie

E-Mail Website
Guest Editor
Institute for Geospatial Research and Education, Eastern Michigan University, Ypsilanti, MI 48197, USA
Interests: geographic information science; spatial modelling; remote sensing theory and methodology; spatiotemporal modelling of urban growth; grassland ecosystem; coupled impacts of human dynamics and environmental change on resource management and ecosystem recovery; land-use and land-cover changes
Special Issues, Collections and Topics in MDPI journals
Dr. Xinyue Ye

E-Mail Website
Guest Editor
Department of Informatics, Urban Informatics, Spatial Computation Lab, New Jersey Institute of Technology, Newark, NJ 07102, USA
Interests: geodesign; geographic information science; spatial network science; urban complexity; urban informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This special issue comprises selected papers from the Proceedings of the Third Annual International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem (GRMSE-2015), a conference that was held from October 16-18th, 2015 in Wuhan, Hubei, China (http://www.grmse2015.org/). Geo-Informatics cover Sustainability and sustainable development Resource Management, Environmental and Sustainable Ecosystem dimensions and require a multi-disciplinary approach in order to examine, explore and critically engage with issues and advances in these and related areas.

The Third Annual International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem (GRMSE-2015) attracts participants in a diverse range of fields, including geographic information science, ecological and environmental sciences, and resource management and policy. GRMSE-2015 continues the conference series’ unique blend of topics focusing on geo-spatial analyses and technologies and their applications in natural and societal resource management in the context of restoring sustainable ecosystems.

Geo-Informatics in Resource Management and Sustainable Ecosystem has also been covered in

-environmental sustainability,

-Resource Management sustainability,

-Sustainable Ecosystem, corporate sustainability strategy and economic sustainability,

-social values for a sustainable economy, energy efficiency and renewable energy sources,

-sustainable urban development, sustainable development policy, practice and education,

-sustainable entrepreneurship and sustainability innovation,

-sustainable agriculture and sustainable management of land and biodiversity.

Prof. Yichun Xie
Prof. Dr. Xinyue Ye
Guest Editor

Prof. Yichun Xie is Director of Institute for Geospatial Research and Education (IGRE), Eastern Michigan University.2004 Distinguished Scholarship Award, American Association of Geographers Regional Development & Planning Specialty Group, American Association of Geographers Philadelphia Centennial Meeting, Philadelphia, PA, March 14-19, 2004. One-Hundred Researchers: Distinguished Overseas Scholar Award, 2003-2006, Chinese Academy of Sciences. 1999 Distinguished Faculty Scholarly/Creative Activity Award, Eastern Michigan University.

Prof. Xinyue Ye is Director of Computational Social Science Lab, Kent State University. 2012 Regional Development and Planning (RDPSG) Emerging Scholar Award by the Association of American Geographers (AAG) and 2011 National First-place Award of "Research and Analysis" by University Economic Development Association on Space-Time Analysis of Economic Data and Toolbox Implementation.

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • Smart city in resource management & sustainable ecosystem
  • Spatial data acquisition through RS and GIS in resource management & sustainable ecosystem
  • Ecological and environmental data processing and management
  • Advanced geospatial model and analysis for understanding ecological and environmental process
  • Applications of Geo-Informatics in resource management & sustainable ecosystem

Published Papers (6 papers)

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Research

2177 KiB  
Article
Change Detection of Phragmites Australis Distribution in the Detroit Wildlife Refuge Based on an Iterative Intersection Analysis Algorithm
by Haixin Liu, Xiaoliang Meng, Tao Jiang, Xinxia Liu and Anbing Zhang
Sustainability 2016, 8(3), 264; https://0-doi-org.brum.beds.ac.uk/10.3390/su8030264 - 11 Mar 2016
Cited by 3 | Viewed by 4869
Abstract
Satellite data have been widely used in the detection of vegetation area changes, however, the lack of historical training samples seriously limits detection accuracy. In this research, an iterative intersection analysis algorithm (IIAA) is proposed to solve this problem, and employed to improve [...] Read more.
Satellite data have been widely used in the detection of vegetation area changes, however, the lack of historical training samples seriously limits detection accuracy. In this research, an iterative intersection analysis algorithm (IIAA) is proposed to solve this problem, and employed to improve the change detection accuracy of Phragmites area in the Detroit River International Wildlife Refuge between 2001 and 2010. Training samples for 2001, 2005, and 2010 were constructed based on NAIP, DOQQ high-resolution imagery and ground-truth data; for 2002–2004 and 2006–2009, because of the shortage of training samples, the IIAA was employed to supply additional training samples. This method included three steps: first, the NDVI image for each year (2002–2004, 2006–2009) was calculated with Landsat TM images; secondly, rough patches of the land-cover were acquired by density slicing using suitable thresholds; thirdly, a GIS overlay analysis method was used to acquire the Phragmites information in common throughout the ten years and to obtain training patches. In the combination with training samples of other land cover types, supervised classifications were employed to detect the changes of Phragmites area. In the experiment, we analyzed the variation of Phragmites area from 2001 to 2010, and the result showed that its distribution areas increased from 5156 acres to 6817 acres during this period, which illustrated that the invasion of Phragmites remains a serious problem for the protection of biodiversity. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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1815 KiB  
Article
The Effects of Ambient Water Quality and Eurasian Watermilfoil on Lakefront Property Values in the Coeur d’Alene Area of Northern Idaho, USA
by Felix Haifeng Liao, Frank M. Wilhelm and Mark Solomon
Sustainability 2016, 8(1), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/su8010044 - 05 Jan 2016
Cited by 16 | Viewed by 7228
Abstract
Amenity value of water resources has become a major driving force of recent population growth in the region centered on Coeur d’Alene Lake in northern Idaho, USA. Despite regulatory measures aimed to protect lake water quality, surface water quality is increasingly threatened by [...] Read more.
Amenity value of water resources has become a major driving force of recent population growth in the region centered on Coeur d’Alene Lake in northern Idaho, USA. Despite regulatory measures aimed to protect lake water quality, surface water quality is increasingly threatened by lakefront development and invasions of Eurasian watermilfoil (Myriophyllum spicatum), a non-indigenous aquatic plant species. We used hedonic modeling to estimate the effects of ambient water quality and the presence of Eurasian watermilfoil on lakefront property values of single-family homes in the Coeur d´Alene area. We find that property values are positively associated with Secchi depth (a proxy of water quality or clarity), and negatively related to the presence of watermilfoil. Results of spatial regime analysis indicate the geographical variations of these associations. The presence of watermilfoil was related to a 13% decline in mean property value, corresponding to $64,255 USD, on average, lower property sales price. Our study demonstrates that proactive mitigation approaches to cope with potential environmental degradation in lake ecosystems could have significant economic benefits to owners of lakefront properties and local communities. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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2834 KiB  
Article
An Efficient Graph-based Method for Long-term Land-use Change Statistics
by Yipeng Zhang, Yunbing Gao, Bingbo Gao, Yuchun Pan and Mingyang Yan
Sustainability 2016, 8(1), 9; https://0-doi-org.brum.beds.ac.uk/10.3390/su8010009 - 29 Dec 2015
Cited by 2 | Viewed by 4709
Abstract
Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In [...] Read more.
Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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13963 KiB  
Article
Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm
by Yandong Wang, Teng Wang, Xinyue Ye, Jianqi Zhu and Jay Lee
Sustainability 2016, 8(1), 25; https://0-doi-org.brum.beds.ac.uk/10.3390/su8010025 - 28 Dec 2015
Cited by 94 | Viewed by 10092
Abstract
With the proliferation of social media, information generated and disseminated from these outlets has become an important part of our everyday lives. For example, this type of information has great potential for effectively distributing political messages, hazard alerts, or messages of other social [...] Read more.
With the proliferation of social media, information generated and disseminated from these outlets has become an important part of our everyday lives. For example, this type of information has great potential for effectively distributing political messages, hazard alerts, or messages of other social functions. In this work, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management and urban sustainability. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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1517 KiB  
Article
Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service
by Xicheng Tan, Liping Di, Meixia Deng, Jing Fu, Guiwei Shao, Meng Gao, Ziheng Sun, Xinyue Ye, Zongyao Sha and Baoxuan Jin
Sustainability 2015, 7(10), 14245-14258; https://0-doi-org.brum.beds.ac.uk/10.3390/su71014245 - 21 Oct 2015
Cited by 16 | Viewed by 5404
Abstract
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the [...] Read more.
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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1452 KiB  
Article
Assessment of Ecological Vulnerability under Oil Spill Stress
by Ling Cai, Li Yan, Jialin Ni and Cui Wang
Sustainability 2015, 7(10), 13073-13084; https://0-doi-org.brum.beds.ac.uk/10.3390/su71013073 - 24 Sep 2015
Cited by 22 | Viewed by 5029
Abstract
Using the constituent elements of vulnerability, an evaluation index system for the ecological vulnerability of coastal areas under oil spill stress is established based on “Sensitivity–Adaptive Capacity-Exposure”. After selecting a gulf in China as the main case study in this work, the cluster [...] Read more.
Using the constituent elements of vulnerability, an evaluation index system for the ecological vulnerability of coastal areas under oil spill stress is established based on “Sensitivity–Adaptive Capacity-Exposure”. After selecting a gulf in China as the main case study in this work, the cluster analysis and reference method were applied in grading and value assigning for all indexes. In addition, the analytic hierarchy process and expert evaluation method were used to determine the index weighting. Finally, a comprehensive evaluation method was adopted in the evaluation studies on the ecological vulnerability of the gulf coastal zone under oil spill stress. Results show the differences between the gulf area and areas that belong to different ecologically-vulnerable areas under oil spill stress. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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