scholarly journals Ecological Vulnerability of Tourism Scenic Spots: Based on Remote Sensing Ecological Index

2021 ◽  
Author(s):  
Hui Shi ◽  
Tiange Shi ◽  
Qin Liu ◽  
Zhi Wang
Keyword(s):  
Remote Sensing ◽  
Ecological Index ◽  
Ecological Vulnerability

scholarly journals A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region

2021 ◽  
Vol 129 ◽  
pp. 107955
Author(s):  
Hongwei Wu ◽  
Bing Guo ◽  
Junfu Fan ◽  
Fei Yang ◽  
Baomin Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Vulnerability Index ◽  
Ecological Vulnerability

scholarly journals Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data

2019 ◽  
Vol 11 (15) ◽  
pp. 4160 ◽  
Author(s):  
Qin Liu ◽  
Tiange Shi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
River Basin ◽  
Hot Spot ◽  
Remote Sensing Data ◽  
Cold Spot ◽  
Strengthening Effect ◽  
Land Use Type ◽  
Sensing Data ◽  
Ecological Vulnerability

Ecological vulnerability assessment increases the knowledge of ecological status and contributes to formulating local plans of sustainable development. A methodology based on remote sensing data and spatial principal component analysis was introduced to discuss ecological vulnerability in the Toutun River Basin (TRB). Exploratory spatial data analysis and a geo-detector were employed to evaluate the spatial and temporal distribution characteristics of ecological vulnerability and detect the driving factors. Four results were presented: (1) During 2003 and 2017, the average values of humidity, greenness, and heat in TRB increased by 49.71%, 11.63%, and 6.51% respectively, and the average values of dryness decreased by 165.24%. However, the extreme differences in greenness, dryness, and heat tended to be obvious. (2) The study area was mainly dominated by a high and extreme vulnerability grade, and the ecological vulnerability grades showed the distribution pattern that the northern desert area was more vulnerable than the central artificial oasis, and the central artificial oasis was more vulnerable than the southern mountainous area. (3) Ecological vulnerability in TRB showed significant spatial autocorrelation characteristics, and the trend was enhanced. The spatial distribution of hot/cold spots presented the characteristics of “hot spot—cold spot—secondary hot spot—cold spot” from north to south. (4) The explanatory power of each factor of ecological vulnerability was temperature (0.5955) > land use (0.5701) > precipitation (0.5289) > elevation (0.4879) > slope (0.3660) > administrative division (0.1541). The interactions of any two factors showed a non-linear strengthening effect, among which, land use type ∩ elevation (0.7899), land use type ∩ precipitation (0.7867), and land use type ∩ temperature (0.7791) were the significant interaction for ecological vulnerability. Overall, remote sensing data contribute to realizing a quick and objective evaluation of ecological vulnerability and provide valuable information for decision making concerning ecology management and region development.

scholarly journals Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

2021 ◽  
Vol 10 (7) ◽  
pp. 475
Author(s):  
Ting Zhang ◽  
Ruiqing Yang ◽  
Yibo Yang ◽  
Long Li ◽  
Longqian Chen
Keyword(s):  
Remote Sensing ◽  
Quality Assessment ◽  
Urban Expansion ◽  
Assessment Method ◽  
Landsat Images ◽  
Ecological Index ◽  
Environment Quality ◽  
Quality Assessment Method ◽  
The Impact

The remote-sensing ecological index (RSEI), which is built with greenness, moisture, dryness, and heat, has become increasingly recognized for its use in urban eco-environment quality assessment. To improve the reliability of such assessment, we propose a new RSEI-based urban eco-environment quality assessment method where the impact of RSEI indicators on the eco-environment quality and the seasonal change of RSEI are examined and considered. The northern Chinese municipal city of Tianjin was selected as a case study to test the proposed method. Landsat images acquired in spring, summer, autumn, and winter were obtained and processed for three different years (1992, 2005, and 2018) for a multitemporal analysis. Results from the case study show that both the contributions of RSEI indicators to eco-environment quality and RSEI values vary with the season and that such seasonal variability should be considered by normalizing indicator measures differently and using more representative remote-sensing images, respectively. The assessed eco-environment quality of Tianjin was, overall, improving owing to governmental environmental protection measures, but the damage caused by rapid urban expansion and sea reclamation in the Binhai New Area still needs to be noted. It is concluded that our proposed urban eco-environment quality assessment method is viable and can provide a reliable assessment result that helps gain a more accurate understanding of the evolution of the urban eco-environment quality over seasons and years.

Evaluation of ecological changes based on a remote sensing ecological index in a Manas Lake wetland, Xinjiang

2019 ◽  
Vol 39 (8) ◽  
Author(s):  
王丽春 WANG Lichun ◽  
焦黎 JIAO Li ◽  
来风兵 LAI Fengbing ◽  
张乃明 ZHANG Naiming
Keyword(s):  
Remote Sensing ◽  
Ecological Index ◽  
Ecological Changes

scholarly journals A Multi-Criteria Evaluation of the Urban Ecological Environment in Shanghai Based on Remote Sensing

2021 ◽  
Vol 10 (10) ◽  
pp. 688
Author(s):  
Yuxiang Yan ◽  
Xianwen Yu ◽  
Fengyang Long ◽  
Yanfeng Dong
Keyword(s):  
Remote Sensing ◽  
Evaluation Method ◽  
Projection Pursuit ◽  
Detection Methods ◽  
Ecological Environment ◽  
Ecological Index ◽  
Environment Quality ◽  
Shanghai City ◽  
Projection Pursuit Model ◽  
The Impact

The urban ecological environment is related to human health and is one of the most concerned issues nowadays. Hence, it is essential to detect and then evaluate the urban ecological environment. However, the conventional manual detection methods have many limitations, such as the high cost of labor, time, and capital. The aim of this paper is to evaluate the urban ecological environment more conveniently and reasonably, thus this paper proposed an ecological environment evaluation method based on remote sensing and a projection pursuit model. Firstly, a series of criteria for the urban ecological environment in Shanghai City are obtained through remote sensing technology. Then, the ecological environment is comprehensively evaluated using the projection pursuit model. Lastly, the ecological environment changes of Shanghai City are analyzed. The results show that the average remote sensing ecological index of Shanghai in 2020 increased obviously compared with that in 2016. In addition, Jinshan District, Songjiang District, and Qingpu District have higher ecological environment quality, while Hongkou District, Jingan District, and Huangpu District have lower ecological environment quality. In addition, the ecological environment of all districts has a significant positive spatial autocorrelation. These findings suggest that the ecological environment of Shanghai has improved overall in the past five years. In addition, Hongkou District, Jingan District, and Huangpu District should put more effort into improving the ecological environment in future, and the improvement of ecological environment should consider the impact of surrounding districts. Moreover, the proposed weight setting method is more reasonable, and the proposed evaluation method is convenient and practical.

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