Effects of China’s ecological restoration on economic development based on Night-Time Light and NDVI data

Li, Qiang; Shi, Xinzheng; Wu, Qing

doi:10.1007/s11356-021-15595-7

Cited by 7 publications

(5 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the study, NLI has the greatest explanatory power for the trend of vegetation cover change (q = 0.422, Table 4). There are a few studies that combine NLI with NDVI, indicating that urbanization has a negative impact on vegetation coverage or the ecological environment by increasing NLI [30,68,69]. There is a significant negative correlation between vegetation coverage and NLI values.…”

Section: Influence Of Factor Interaction On Ndvimentioning

confidence: 99%

NDVI-Based Vegetation Dynamics and Their Responses to Climate Change and Human Activities from 2000 to 2020 in Miaoling Karst Mountain Area, SW China

Yang

et al. 2023

Land

View full text Add to dashboard Cite

Understanding spatiotemporal shifts in vegetation and their climatic and anthropogenic regulatory factors can offer a crucial theoretical basis for environmental conservation and restoration. In this article, the normalized difference vegetation index (NDVI) of the Miaoling area from 2000 to 2020 is studied using a trend analysis and the Mann–Kendall mutation test (MK test) to review the vegetation’s dynamic changes. Our study uses the Hurst index, a partial correlation analysis, and a geographic detector to investigate the contributions of climate change and human activities to regional vegetation changes and their drivers. We found that Miaoling’s annual average NDVI was between 0.66 and 0.83 in 2000–2020, with a mean of 0.766. The overall trend was slow upward (0.0009/year), and 53.82% of the region continued to grow and gradually increased from west to east in the spatial domain, among which the karst regional NDVI distribution area and its growth rate were higher than those of non-karst sites. Based on correlations between climatic factors and NDVI, precipitation seasonality (coefficient of variation, CV) had the strongest correlation (positive correlation) with NDVI, while vapor pressure deficit (VPD) had a negative correlation with NDVI. In the interaction, human activities played a dominant role in the influence of NDVI on the vegetation of Miaoling. The night light index had the most explanatory power on the NDVI (q = 0.422), and the interaction between anthropogenic factors and other factors dominated its explanatory power. This study has academic and practical importance for the management, protection, and sustainable development of karst basins.

show abstract

Section: Influence Of Factor Interaction On Ndvimentioning

confidence: 99%

NDVI-Based Vegetation Dynamics and Their Responses to Climate Change and Human Activities from 2000 to 2020 in Miaoling Karst Mountain Area, SW China

Yang

et al. 2023

Land

View full text Add to dashboard Cite

show abstract

“…However, this can also lead to an increased volume of domestic garbage which would occupy a large amount of land, pollute soil, air and water bodies, and destroy the ecological environment; the untimely removal and transportation of domestic garbage would have an impact on resident health and lead to disease [51,52]. Ecological restoration and management are conducive to environmental protection and high-quality economic development [53]. Annually, China invests many financial resources in ecological restoration, hoping to continuously explore and innovate in ecological restoration and create a suitable ecological environment for its population.…”

Section: Variable Descriptionmentioning

confidence: 99%

Air Quality and Residents’ Health in China: An Empirical Analysis Based on Spatial Simultaneous Equations

2022

Applied Sciences

View full text Add to dashboard Cite

Large-scale air pollution has an impact on the health and travel of residents in China. First, this article uses the gravity model and finds that China’s air quality presents a typical spatial correlation network. The network structure has changed from complex to simple, indicating that China’s air quality is gradually improving. Second, this paper uses spatial simultaneous equations to study the effect of air quality on residents’ health. The results show that an increase in the air quality index of local and surrounding provinces will have a significant impact on the health of residents. The absolute and relative air quality affects the lives of residents. The decline in the health of residents from the previous period will prompt the government to adopt various pollution reduction policies, which will improve air quality in the current period. Based on the empirical research conclusions, this article makes policy recommendations.

show abstract

“…In recent years, the improvement in photonics has witnessed significant progress in sensitivity on the space-borne optical sensor, and remote sensing at night-time has become more feasible than decades ago. Additionally, such tools are widely used in evaluating regional economic development [12][13][14], population distribution [15][16][17], power consumption [18,19], carbon dioxide emissions [20], military conflicts [21], urban scale [22][23][24], PM2.5 concentration [25,26], snow cover [27] and epidemic impact [28,29] detection.…”

Section: Introductionmentioning

confidence: 99%

Disaster-Caused Power Outage Detection at Night Using VIIRS DNB Images

Cui

Qiu

Wang³

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Rapid disaster assessment is critical for public security and rescue. As a secondary disaster of large-scale meteorological disasters, power outages cause severe outcomes and thus need to be monitored efficiently and without being costly. Power outage detection from space-borne remote sensing imagery offers a broader coverage and is more temporally sensitive than ground-based surveys are. However, it is challenging to determine the affected area accurately and quantitatively evaluate its severity. Therefore, a new method is proposed to solve the above problems by building a power outage detection model (PODM) and drawing a power outage spatial distribution map (POSDM). This paper takes the winter storm Uri, of 2021, as the meteorological disaster background and Harris County, Texas, which was seriously affected, as the research object. The proposed method utilises the cloud-free VIIRS DNB nadir and close nadir images (<60 degrees) collected during the 3 months before and 15 days after Uri. The core idea beneath the proposed method is to compare the radiance difference in the affected area before and after the disaster, and a large difference in radiance indicates the happening of power outages. The raw radiance of night light measurement is first corrected to remove lunar and atmospheric effects to improve accuracy. Then, the maximum and minimum pixels in the target area of the image are considered outliers and iteratively eliminated until the standard deviation change before and after elimination is less than 1% to finalize the outlier removals. The case study results in Harris show that the PODM detects 28% of outages (including traffic area) compared to 17% of outages (living area only) reported by ground truth data, indicating general agreement with the proposed method.

show abstract

Effects of China’s ecological restoration on economic development based on Night-Time Light and NDVI data

Cited by 7 publications

References 58 publications

NDVI-Based Vegetation Dynamics and Their Responses to Climate Change and Human Activities from 2000 to 2020 in Miaoling Karst Mountain Area, SW China

NDVI-Based Vegetation Dynamics and Their Responses to Climate Change and Human Activities from 2000 to 2020 in Miaoling Karst Mountain Area, SW China

Air Quality and Residents’ Health in China: An Empirical Analysis Based on Spatial Simultaneous Equations

Disaster-Caused Power Outage Detection at Night Using VIIRS DNB Images

Contact Info

Product

Resources

About