Integration of Landscape Metrics and Variograms to Characterize and Quantify the Spatial Heterogeneity Change of Vegetation Induced by the 2008 Wenchuan Earthquake

Tian, Bingwei; Koike, Katsuaki; Buting, Hong; Ren, Peng

doi:10.3390/ijgi6060164

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…As one of the most important sources of information for assessing urban DRM, the natural environment relies on the vegetation cover information. Vegetation spatial heterogeneity serves as a proxy to extract changes in vegetation pattern, and to monitor ecosystem changes before and after a disaster at the landscape scale for natural damage assessment [149]. Spatial heterogeneity may affect functions and processes in ecological systems, which is a key to assess ecosystem changes [150].…”

Section: Socio-economic Statusmentioning

confidence: 99%

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

2018

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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 ...

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Section: Socio-economic Statusmentioning

confidence: 99%

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

2018

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“…Among all studies that defined LH (n = 127), 24.4% considered both compositional and configurational components by explicitly stating the investigated components in the definitions (e.g., the 'spatial variation of the composition and configuration of landscapes'; Li et al 2015) or implicitly stating them (e.g., the 'land-cover types and their spatial arrangements'; Singh et al 2017). Lastly, only two articles considered temporal aspects in their definitions (Deutschewitz et al 2003, Wang et al 2017).…”

Section: Review Methodsmentioning

confidence: 99%

Landscape heterogeneity: concepts, quantification, challenges and future perspectives

et al. 2023

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Summary The intrinsic complexity, variety of concepts and numerous ways to quantify landscape heterogeneity (LH) may hamper a better understanding of how its components relate to ecological phenomena. Our study is the first to synthesize understanding of this concept and to provide the state of the art on the subject based on a comprehensive systematic literature review of 661 articles published between 1982 and 2019. Definitions, terminologies and measurements of LH were diverse and conflicting. Most articles (534 out of 661) did not provide any definition for LH, and we found great variation among the studies that did. According to our review, only 10 studies measured the effects of different land-cover types on biotic or abiotic processes (functional LH). The remaining 651 studies measured physical attributes of the landscape without mentioning that different land-cover types may impact biotic and abiotic processes differently (structural LH). The metrics most frequently used to represent LH were the Shannon diversity index and proportion of land-cover type. Most metrics used as proxies of LH also coincided with those used to represent non-heterogeneity metrics, such as fragmentation and connectivity. We identify knowledge gaps, indicate future perspectives and propose guidelines that should be addressed when researching LH.

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“…Geostatistics of remote sensing images can provide parameters for describing and quantifying theses spatial patterns [18][19][20] . The present work uses geostatistical tools to test the capability and potential use of EFAs and EFTs derived from Sentinel-2 data as early warning systems of landscape degradation in areas surrounding refugees camp using buffer areas.…”

Section: Introductionmentioning

confidence: 99%

Developing early warning systems for land degradation around refugee camps: a preliminary approach

Jenerowicz-Sanikowska,

Domingo-Marimon,

Pesquer Mayos

et al. 2023

Earth Resources and Environmental Remote Sensing/Gis Applications XIV

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The joint research initiative of H2020 EOTiST and ARICA projects aims to better understand the ecosystem conditions around refugee camps and evaluate the capability of Ecosystem Functional Attributes (EFA) as early warning indicators of ecosystem degradation. The analysis is based on Sentinel-2 optical satellite data and derived geospatial products for the period 2016-2022, reference data collected during the field campaign in 2022, and information gathered during interviews with local authorities and NGOs.The study area is the Mtendeli Refugee Camp (MRC), Kigoma region, Tanzania. The MRC was established over 30 years ago, in close proximity to the 6 000 km2 Moyowosi Game Reserve, an environmentally fragile area. It was reopened in 2015 at a nearby location and closed in December 2021 1 . The proposed approach consists of quantitative and qualitative temporal analysis of the ecosystem for the period 2016-2022 to assess anthropogenic impact on the camp surroundings. Firstly, the temporal trends and spatial heterogeneity in NDVI seasonal dynamics are derived from EFA 2 . Secondly, Ecosystem Functional Types (EFT) 3 are calculated for the same timeframe. Special attention is paid to the disturbances and anomalies in NDVI dynamics.In addition to the results of the spatio-temporal analysis, the context for the demonstrated changes was presented with reference to field research and expert knowledge. This approach, complemented with changes in land cover/use, may result in a protocol for early warning system, monitoring and evaluation of the refugee camp surroundings, supporting decisionmaking on mitigation of environment degradation.

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Integration of Landscape Metrics and Variograms to Characterize and Quantify the Spatial Heterogeneity Change of Vegetation Induced by the 2008 Wenchuan Earthquake

Cited by 9 publications

References 27 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

Landscape heterogeneity: concepts, quantification, challenges and future perspectives

Developing early warning systems for land degradation around refugee camps: a preliminary approach

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