Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

Liu, Qin; Yang, Zhaoping; Han, Fang; Shi, Hui; Wang, Zhi; Chen, Xiao

doi:10.3390/su11226385

Cited by 29 publications

(25 citation statements)

References 65 publications

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“…The interactive detection values of the other factors were all less than 0.65. The results show that the explanatory power after the interactive detection of land use and other factors was greater than that of the original single-factor detection [64,65]. Based on the ecological detection ( Figure 6), the river ∩ slope, river ∩ road, temperature ∩ road, and road ∩ slope all present no significant differences, while the ecological detections among the other factors show significant differences.…”

Section: Analysis Of Driving Factors Of the Hami Oasis Based On Geogrmentioning

confidence: 92%

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

et al. 2020

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Given the restrictions on special geographic locations in development processes, the measurement and analysis of the ecological quality of the Hami Oasis are of great significance for the protection of this fragile oasis. In this study, the ecological quality of the Hami Oasis was monitored by constructing a remote sensing ecological index (RSEI) for arid areas. Using the standard deviation ellipse and moving window method, the ecological status and space–time changes were explored for both their external and internal factors in the Hami Oasis. Finally, a geo-detector was employed to determine the driving factors of the ecological quality of the Hami Oasis. The results revealed that: (1) In the remote sensing ecological index constructed in the Hami Oasis, the main influencing factors were dryness and wetness. The average value of the ecological quality of the oasis was less than 0.5, and the ecological quality level was relatively poor. Among the five grades of ecological quality in the Hami Oasis, the poor grade and the good grade showed the largest changes, decreasing by 200 and increasing by 300, respectively, which were mainly concentrated in the periphery of the oasis. (2) The improved ecological quality of the Hami Oasis was mainly manifested in the expansion of the artificial oasis, while the deteriorated area was manifested as an increase in the built-up area. Moreover, the ecological quality of the Hami Oasis presented a ringlike nesting distribution pattern from the internal built-up area to the artificial oasis periphery. (3) The external expansion direction of the ecological quality of the Hami Oasis featured southeast–northwest expansion, which was consistent with the direction of the rivers and traffic roads. The transformation between different ecological qualities in the oasis and the expansion of the built-up area were the reasons for the fragmentation of the Hami Oasis’ landscape. (4) Compared to a single factor, the dual-factor for the ecological quality of the Hami Oasis had stronger explanatory power. Moreover, changes in land use types caused changes in the ecological quality of the Hami Oasis. During the study period, we found that human activities had a more significant impact than natural factors on the development of the Hami Oasis. (5) The Moran’s I Index increased from 0.835268 in 2000 to 0.923976 in 2018, and the p values in the study area all reached a 0.05 significant level. At the same time, the areas with p values above the 0.01 and 0.001 significant levels have also increased significantly in the past 18 years.

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Section: Analysis Of Driving Factors Of the Hami Oasis Based On Geogrmentioning

confidence: 92%

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

et al. 2020

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“…It has already been used for spatial index calculations in the research of many scholars. Similarly, Liu et al constructed the Remote-Sensing Ecological Index based on PCA to measure the ecological status of Bayinbruck [35]. Xu et al constructed the Remote-Sensing Ecological Index based on PCA to quantify the ecological status of Fujian Province [30].…”

Section: Construction Of Veqimentioning

confidence: 99%

Spatiotemporal Pattern of Vegetation Ecology Quality and Its Response to Climate Change between 2000–2017 in China

Luo

et al. 2021

Sustainability

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Vegetation ecology quality (VEQ) is an important indicator for evaluating environmental quality and ecosystem balance. The VEQ in China has changed significantly with global warming and gradual intensification of human activities. It is crucial to research the spatiotemporal characteristics of VEQ and its response to climate change in China. However, most previous studies used a single indicator to reflect VEQ in China, which needs to combine the effects of multiple indicators to reveal its variation characteristics. Based on the six remote sensing indicators, fractional vegetation cover, leaf area index, net primary productivity, vegetation wetness, land surface temperature, and water use efficiency of vegetation, the vegetation ecology quality index (VEQI) was constructed by principal component analysis in this paper. The spatio-temporal distribution and trend characteristic of VEQ within disparate ecosystems in China from 2000 to 2017 were studied. How continuous climate change affected VEQ over time was also analyzed. The results showed that the differences in spatial distribution between the excellent and poor VEQ regions were significant, with the proportion of excellent regions being much larger than that of poor regions. The VEQ has been ameliorated continuously during the past 18 years. Simultaneously, the VEQ would be ameliorated persistently in the future. Differences in the distribution and variation trend of VEQ occurred in disparate ecosystems. The VEQ of broadleaved forest was the best, while that of shrubs and arctic grassland ecosystem was the worst. The VEQ characteristics were different in disparate climate zones, with the best VEQ in the tropical monsoon climate zone and the worst in the plateau mountain climate zone. Except for desert vegetation and paddy field-dominated vegetation, VEQ of other ecosystems were significantly negatively correlated with altitude. Generally, moderate precipitation and temperature were favorable to improve VEQ in China. VEQ during the peak growing season was negatively correlated with temperature and positively correlated with precipitation, and the influence of precipitation on VEQ was stronger than that of temperature. Our results can be used to enact relevant management measures and policies.

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“…Therefore, there have been numerous studies on this area, including on the evolution characteristics of its landscape patterns [33], its ecological carrying capacity and sustainable development [34], and its grassland vegetation community [35]. In addition, several ecological risk analyses [36] and ecological environmental assessments [37] have also been performed on the ecosystem. However, these studies did not provide a systematic assessment of ecosystem health at the WNH of Bayanbulak from the perspective of ecological health.…”

Section: Introductionmentioning

confidence: 99%

Ecosystem Health Assessment of World Natural Heritage Sites Based on Remote Sensing and Field Sampling Verification: Bayanbulak as Case Study

et al. 2020

Self Cite

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Monitoring the ecosystem health for world natural heritage sites is essential for protecting them and benefits the formulation of more targeted protection policies. This study used Bayanbulak world natural heritage site as a case, established a framework for assessing the ecosystem health through remote sensing based on the parameters of ecosystem vigour, organization, resilience, and services. Then, we verified the obtained results through field sampling. The results show that the ecosystem health in the overall study area had declined over time, however, the health within the property zone remained at high levels and stable. The area proportion of low health was low and primarily distributed in the buffer zone. Thus, in general, the ecosystem in the study area was healthy. Besides, the ecosystem health exhibited distinct spatial agglomeration characteristics, and the degree of agglomeration enhanced over time. In addition, the field vegetation samplings were consistent with the changes in the ecosystem health levels, therefore, the result of RS monitoring of ecosystem health were credible. Thus, this study provides a scientific basis for heritage managers to formulate suitable ecological protection policies and should aid further research on the ecological monitoring of heritage sites.

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Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

Cited by 29 publications

References 65 publications

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI

Spatiotemporal Pattern of Vegetation Ecology Quality and Its Response to Climate Change between 2000–2017 in China

Ecosystem Health Assessment of World Natural Heritage Sites Based on Remote Sensing and Field Sampling Verification: Bayanbulak as Case Study

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