Zhaoping Yang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Zhaoping Yang has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Fang Han
State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
1 shared publication Hui Shi
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi830011, China
1 shared publication- Hui Shi
College of Tourism, Xinjiang University of Finance and Economics, No. 449 Beijing Road, Urumqi 830012, China
1 shared publication Qin Liu
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi830011, China
1 shared publication- Qin Liu
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
1 shared publication - Xiaodong Chen
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
1 shared publication
Latest Publications
- Open Access
- 13 November 2019
- Published by MDPI AG in Sustainability
- Vol. 11 (22) , 6385
Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke
Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.
- 13 November 2019
- Published by MDPI AG in Sustainability
- Vol. 11 (22) , 6385
Open AccessEcological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke
Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.
- Open Access
- 29 July 2019
- Published by Walter de Gruyter GmbH in Open Geosciences
- Vol. 11 (1) , 327-340
Ecological risk assessment of geohazards in Natural World Heritage Sites: an empirical analysis of Bogda, Tianshan
Ecological risk assessment plays an important role in avoiding disasters and reducing losses. Natural world heritage site is the most precious natural assets on earth, yet few studies have assessed ecological risks from the perspective of world heritage conservation and management. A methodology for considering ecological threats and vulnerabilities and focusing on heritage value was introduced and discussed for the Bogda component of the Xinjiang Tianshan Natural World Heritage Site. Three important results are presented. (1) Criteria layers and ecological risk showed obvious spatial heterogeneity. Extremely high-risk and high-risk areas, accounting for 13.60% and 32.56%, respectively, were mainly gathered at Tianchi Lake and Bogda Glacier, whereas the extremely low-risk and low-risk areas, covering 1.33% and 17.51% of the site,were mainly distributed to the north and scattered around in the southwest montane region. (2) The level of risk was positively correlated with the type of risk, and as the level of risk increases, the types of risk increase. Only two risk types were observed in the extremely low-risk areas, whereas six risk types were observed in the high-risk areas and eight risk types were observed in the extremely high-risk areas. (3) From the perspective of risk probability and ecological damage, four risk management categories were proposed, and correlative strategies were proposed to reduce the possibility of ecological risk and to sustain or enhance heritage value.
- 29 July 2019
- Published by Walter de Gruyter GmbH in Open Geosciences
- Vol. 11 (1) , 327-340
Open AccessEcological risk assessment of geohazards in Natural World Heritage Sites: an empirical analysis of Bogda, Tianshan
Ecological risk assessment plays an important role in avoiding disasters and reducing losses. Natural world heritage site is the most precious natural assets on earth, yet few studies have assessed ecological risks from the perspective of world heritage conservation and management. A methodology for considering ecological threats and vulnerabilities and focusing on heritage value was introduced and discussed for the Bogda component of the Xinjiang Tianshan Natural World Heritage Site. Three important results are presented. (1) Criteria layers and ecological risk showed obvious spatial heterogeneity. Extremely high-risk and high-risk areas, accounting for 13.60% and 32.56%, respectively, were mainly gathered at Tianchi Lake and Bogda Glacier, whereas the extremely low-risk and low-risk areas, covering 1.33% and 17.51% of the site,were mainly distributed to the north and scattered around in the southwest montane region. (2) The level of risk was positively correlated with the type of risk, and as the level of risk increases, the types of risk increase. Only two risk types were observed in the extremely low-risk areas, whereas six risk types were observed in the high-risk areas and eight risk types were observed in the extremely high-risk areas. (3) From the perspective of risk probability and ecological damage, four risk management categories were proposed, and correlative strategies were proposed to reduce the possibility of ecological risk and to sustain or enhance heritage value.