2019
DOI: 10.3390/su11215953
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Conservation Value of World Natural Heritage Sites’ Outstanding Universal Value via Multiple Techniques—Bogda, Xinjiang Tianshan

Abstract: The protection of World Natural Heritage Sites (WNHSs) has become a global undertaking, wherein Outstanding Universal Value (OUV) is an important aspect of heritage protection. Focusing on the protection of the aesthetic and bioecological values of Bogda (one component of Xinjiang Tianshan WNHS), 17 indicators are selected to construct a Heritage Value Protection Significance Index (HVPSI) and a related Heritage Value Protection Index (HVI). From these, the level of OUV conservation is obtained according to th… Show more

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Cited by 17 publications
(21 citation statements)
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“…Samples from a total of 47 plots were collected. Next, as per previous studies [63][64][65][66], the EHA results were verified based on the vegetation coverage, diversity, richness, and evenness of the field vegetation. We used Spearman rank correlation coefficient to elucidate the relationship between the EHA results and the biodiversity of the field vegetation, with the aim of determining the accuracy of the EHA results.…”
Section: Verification Based On Field Datamentioning
confidence: 86%
See 1 more Smart Citation
“…Samples from a total of 47 plots were collected. Next, as per previous studies [63][64][65][66], the EHA results were verified based on the vegetation coverage, diversity, richness, and evenness of the field vegetation. We used Spearman rank correlation coefficient to elucidate the relationship between the EHA results and the biodiversity of the field vegetation, with the aim of determining the accuracy of the EHA results.…”
Section: Verification Based On Field Datamentioning
confidence: 86%
“…Hence, RS and GIS technologies are used widely in EHA [20,45]. RS large-scale data can quickly assess the space-time distribution and evolution of ecosystem health in heritage sites, but RS large-scale data have certain limitations in accurately reflecting the level of ecosystem health, thus, the ground-based field sampling small-scale data were used to verify the rationality of the results of RS large-scale data [65].…”
Section: Ecosystem Health Assessment Modelmentioning
confidence: 99%
“…Principal component analysis is skilled in reducing the dimensionality of a dataset by converting a set of observed correlated variables into a set of linearly uncorrelated variables through orthogonal transformation [46]. Moreover, spatial principal component analysis does not rely on the prior knowledge or experience of researchers, which can reduce subjective influence to some extent [47]. Remote-sensing data and geographic information system provide an available technique in integrating and analyzing a series of spatial data.…”
Section: Construction Of Remote-sensing Ecological Index (Rsei)mentioning
confidence: 99%
“…In the spatial correlation test, if the spatial lag model Lagrange multiplier test statistic LMLAG and spatial error LMERROR are not significant, then the OLS regression were selected. If LMLAG is more significant than the spatial error LMERROR, the SLM is selected, otherwise, the SEM is selected [47,55].…”
Section: Spatial Econometric Modelmentioning
confidence: 99%
“…The indicator system includes the systems of natural causes-result performance, influencing factors-performance factors-stress factors, and the natural-ecological-socioeconomic system [17]. Evaluation methods include the analytic hierarchy process (AHP) method [18], comprehensive index method [19], fuzzy mathematics method [20], principal component analysis (PCA) method [21], neural network method [22], entropy weight method [6], the method of landscape ecology [23], and the fuzzy matter-element evaluation method [2].…”
Section: Introductionmentioning
confidence: 99%