GIS Based Measurement and Regulatory Zoning of Urban Ecological Vulnerability

Zhang, Xiaorui; Wang, Zhenbo; Lin, Jing

doi:10.3390/su7089924

Cited by 45 publications

(19 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, vegetation cover ratio has been used as a proxy to evaluate the biophysical [106] and ecological [157] vulnerability, as well as resilience. A higher ratio of vegetation cover signified and increase in resilience (the vegetation coverage is one of the most important indicators for measuring ecological capacity for self-restoration).…”

Section: Socio-economic Statusmentioning

confidence: 99%

Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review

2018

View full text Add to dashboard Cite

Rapid increase in population and growing concentration of capital in urban areas has escalated both the severity and longer-term impact of natural disasters. As a result, Disaster Risk Management (DRM) and reduction have been gaining increasing importance for urban areas. Remote sensing plays a key role in providing information for urban DRM analysis due to its agile data acquisition, synoptic perspective, growing range of data types, and instrument sophistication, as well as low cost. As a consequence numerous methods have been developed to extract information for various phases of DRM analysis. However, given the diverse information needs, only few of the parameters of interest are extracted directly, while the majority have to be elicited indirectly using proxies. This paper provides a comprehensive review of the proxies developed for two risk elements typically associated with pre-disaster situations (vulnerability and resilience), and two post-disaster elements (damage and recovery), while focusing on urban DRM. The proxies were reviewed in the context of four main environments and their corresponding sub-categories: built-up (buildings, transport, and others), economic (macro, regional and urban economics, and logistics), social (services and infrastructures, and socio-economic status), and natural. All environments and the corresponding proxies are discussed and analyzed in terms of their reliability and sufficiency in comprehensively addressing the selected DRM assessments. We highlight strength and identify gaps and limitations in current proxies, including inconsistencies in terminology for indirect measurements. We present a systematic overview for each group of the reviewed proxies that could simplify cross-fertilization across different DRM domains and may assist the further development of methods.While systemizing examples from the wider remote sensing domain and insights from social and economic sciences, we suggest a direction for developing new proxies, also potentially suitable for capturing functional recovery.2 of 30 threats, to reduce own overall vulnerability, and to allow the community to recover from adverse impacts when they occur. Decades of disaster research offer extensive findings in this respect [4][5][6][7]. Remote sensing (RS)-as an effective and rapid tool for monitoring large areas-is essential for the acquisition of geospatial data, which in turn constitutes the basis for risk assessment and management. RS is widely used for various aspects of the DRM, ranging from vulnerability [8] to rapid damage assessments [9], for diverse areas ranging from coastal ecosystems [10] to complex urban settings [11], and for disasters as diverse as landslides [12,13] or cyclones [14].Numerous methods have been developed to extract information from RS data to identify, characterize, or quantify different phases of the disaster risk cycle: response, recovery, prevention/mitigation, and preparedness [15]. However, early studies predominantly considered the physical side of the assessments for both ...

show abstract

Section: Socio-economic Statusmentioning

confidence: 99%

Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review

2018

View full text Add to dashboard Cite

show abstract

“…This paper introduces the natural variation index [41] and social variation index [42]. The natural variation index refers to the variation which results from the various natural disaster indices of regional natural factors.…”

Section: Quantitative Analysis Of Natural and Social Factorsmentioning

confidence: 99%

Ecosystem Services Value Assessment and Uneven Development of the Qingjiang River Basin in China

Lin

Qian

et al. 2017

Sustainability

View full text Add to dashboard Cite

Abstract:As an important ecological barrier in Southwest China, the Qingjiang river basin plays a vital role in shaping the mountainous terrain. This paper analyzes the Ecosystem Services Value (ESV) using a series of methods based on the data of changes in land use from 2000 to 2015 and the statistical yearbook. The changes in land use between 2000 and 2015 were dominated by forest land, which accounted for 60.63% of the total area, followed by arable landwhich accounted for about 22.26%, while grassland and other land use contribution rates were the lowest, accounting for only about 17.11%. Environmental changes and economic development were uneven. The regional comprehensive strength of En'shi City, Changyang County, and Yidu City were among the highest, while Badong County, Hefeng County, and Wufeng County were among the lowest in the area under study. In addition, the ESV in 2035 was estimated to be 1.56 billion dollars, a decrease of 27.64% when compared with the year 2000. The ESV of Yidu City, Lichuan City, Jianshi County, and Hefeng County grew faster, at the rates of 94.76%, 65.12%, 96.96%, and 92.38%, respectively. However, the ESV of En'shi City, Badong County, Wufeng County and Xuan'en County showed a downward trend, at the rates of −32.53%, −487.80%, −368.07%, and −181.52%, respectively.

show abstract

“…GIS has been widely used in disaster research [69,72,73,79]. In this research, the whole process of risk assessment of hail disasters affecting cotton, including data management, index construction, model running, thematic mapping, spatial and statistical analysis, were carried out with support of GIS platform.…”

Section: Technological Flow and Application Of Gismentioning

confidence: 99%

GIS-Based Risk Assessment of Hail Disasters Affecting Cotton and Its Spatiotemporal Evolution in China

Wang

Yue

et al. 2016

Sustainability

View full text Add to dashboard Cite

Understanding the spatiotemporal distribution pattern of hail disaster risk for cotton is crucial in mitigating hail disaster and promoting the sustainability of cotton farming. Based on such indexes as hail disaster frequency, spatiotemporal exposure, and vulnerability of cotton, we assess hail disaster risk for cotton, and analyze its spatiotemporal pattern and evolution in Mainland China from 1950 to 2009, supported by geographic information system (GIS). The following conclusions are drawn: (1) The proposed risk assessment method reveals the spatiotemporal difference of hail disaster risk for cotton at the county level.

show abstract

GIS Based Measurement and Regulatory Zoning of Urban Ecological Vulnerability

Cited by 45 publications

References 38 publications

Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review

Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review

Ecosystem Services Value Assessment and Uneven Development of the Qingjiang River Basin in China

GIS-Based Risk Assessment of Hail Disasters Affecting Cotton and Its Spatiotemporal Evolution in China

Contact Info

Product

Resources

About