scholarly journals Impact of rural depopulation and climate change on vegetation, runoff and sediment load in the Gan River basin, China

2020 ◽  
Vol 51 (4) ◽  
pp. 768-780
Author(s):  
Lidong Huang ◽  
Aizhong Ye ◽  
Chongjun Tang ◽  
Qingyun Duan ◽  
Yahai Zhang
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Rural Population ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Variations ◽  
Farmland Abandonment ◽  
Causality Test ◽  
Rural Depopulation

Abstract Climate change and rural depopulation are changing the ecological and hydrological cycles in China. Data on the normalized difference vegetation index (NDVI), temperature, precipitation, streamflow, sediment and rural population are available for the Gan River basin from 1981 to 2017. We investigated the spatio-temporal variations in climate, human activity and vegetation mainly using the Mann–Kendall test and examined their relationship using the Granger causality test. The results showed that (1) the temperature markedly increased in all seasons; (2) the precipitation increased in summer and winter but decreased in spring and autumn; (3) overall, the NDVI increased markedly during 2005–2017, but showed seasonal differences, with decreases in summer and winter and increases in spring and autumn; (4) the annual sediment transport showed a significant decreasing trend and (5) a large number of the population shifted from rural to urban areas, resulting in a decrease in the rural population between 1998 and 2018. Rural depopulation has brought about farmland abandonment, conversion of farmland to forests, which was the factor driving the recovery of the vegetation and the decrease in sediment. The results of this study can provide support for climate change adaptation and sustainable development.

scholarly journals An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

2021 ◽  
Vol 13 (4) ◽  
pp. 766
Author(s):  
Yuanmao Zheng ◽  
Qiang Zhou ◽  
Yuanrong He ◽  
Cuiping Wang ◽  
Xiaorong Wang ◽  
...  
Keyword(s):  
Urban Development ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Development Planning ◽  
Urban Land ◽  
Sustainable Urban Development ◽  
Land Use Patterns ◽  
Water Index ◽  
Nighttime Light

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

scholarly journals Contributions of Vegetation Greening and Climate Change to Evapotranspiration Trend after Large-Scale Vegetation Restoration on the Loess Plateau, China

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1755
Author(s):  
Shuo Wang ◽  
Chenfeng Cui ◽  
Qin Dai
Keyword(s):  
Climate Change ◽  
Loess Plateau ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Potential Evapotranspiration ◽  
Development Trend ◽  
Future Trend ◽  
Natural Ecosystem ◽  
The Loess Plateau

Since the early 2000s, the vegetation cover of the Loess Plateau (LP) has increased significantly, which has been fully recorded. However, the effects on relevant eco-hydrological processes are still unclear. Here, we made an investigation on the changes of actual evapotranspiration (ETa) during 2000–2018 and connected them with vegetation greening and climate change in the LP, based on the remote sensing data with correlation and attribution analysis. Results identified that the average annual ETa on the LP exhibited an obvious increasing trend with the value of 9.11 mm yr−1, and the annual ETa trend was dominated by the changes of ETa in the third quarter (July, August, and September). The future trend of ETa was predicted by the Hurst exponent. Partial correlation analysis indicated that annual ETa variations in 87.8% regions of the LP were controlled by vegetation greening. Multiple regression analysis suggested that the relative contributions of potential evapotranspiration (ETp), precipitation, and normalized difference vegetation index (NDVI), to the trend of ETa were 5.7%, −26.3%, and 61.4%, separately. Vegetation greening has a close relationship with the Grain for Green (GFG) project and acts as an essential driver for the long-term development trend of water consumption on the LP. In this research, the potential conflicts of water demanding between the natural ecosystem and social-economic system in the LP were highlighted, which were caused by the fast vegetation expansion.

scholarly journals Phenological Analysis of Sub-Alpine Forest on Jeju Island, South Korea, Using Data Fusion of Landsat and MODIS Products

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 286
Author(s):  
Sang-Jin Park ◽  
Seung-Gyu Jeong ◽  
Yong Park ◽  
Sang-hyuk Kim ◽  
Dong-kun Lee ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Data Fusion ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Study Region ◽  
Modis Imagery ◽  
Increasing Temperature

Climate change poses a disproportionate risk to alpine ecosystems. Effective monitoring of forest phenological responses to climate change is critical for predicting and managing threats to alpine populations. Remote sensing can be used to monitor forest communities in dynamic landscapes for responses to climate change at the species level. Spatiotemporal fusion technology using remote sensing images is an effective way of detecting gradual phenological changes over time and seasonal responses to climate change. The spatial and temporal adaptive reflectance fusion model (STARFM) is a widely used data fusion algorithm for Landsat and MODIS imagery. This study aims to identify forest phenological characteristics and changes at the species–community level by fusing spatiotemporal data from Landsat and MODIS imagery. We fused 18 images from March to November for 2000, 2010, and 2019. (The resulting STARFM-fused images exhibited accuracies of RMSE = 0.0402 and R2 = 0.795. We found that the normalized difference vegetation index (NDVI) value increased with time, which suggests that increasing temperature due to climate change has affected the start of the growth season in the study region. From this study, we found that increasing temperature affects the phenology of these regions, and forest management strategies like monitoring phenology using remote sensing technique should evaluate the effects of climate change.

Alpine sparsely vegetated areas in the eastern Qilian Mountains shrank with climate warming in the past 30 years

2018 ◽  
Vol 42 (4) ◽  
pp. 415-430 ◽  
Author(s):  
Biao Zeng ◽  
Fuguang Zhang ◽  
Taibao Yang ◽  
Jiaguo Qi ◽  
Mihretab G Ghebrezgabher
Keyword(s):  
Climate Change ◽  
Climate Warming ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Qilian Mountains ◽  
Visual Interpretation ◽  
Hydrothermal Conditions ◽  
The Past ◽  
Distribution Ranges

Alpine sparsely vegetated areas (ASVAs) in mountains are sensitive to climate change and rarely studied. In this study, we focused on the response of ASVA distribution to climate change in the eastern Qilian Mountains (EQLM) from the 1990s to the 2010s. The ASVA distribution ranges in the EQLM during the past three decades were obtained from the Thematic Mapper remote sensing digital images by using the threshold of normalized difference vegetation index (NDVI) and artificial visual interpretation. Results indicated that the ASVA shrank gradually in the EQLM and lost its area by approximately 11.4% from the 1990s to the 2010s. The shrunken ASVA with markedly more area than the expanded one was mainly located at altitudes from 3700 m to 4300 m, which were comparatively lower than the average altitude of the ASVA distribution ranges. This condition led to the low ASVA boundaries in the EQLM moving upwards at a significant velocity of 22 m/decade at the regional scale. This vertical zonal process was modulated by topography-induced differences in local hydrothermal conditions. Thus, the ASVA shrank mainly in its lower parts with mild and sunny slopes. Annual maximum NDVI in the transition zone increased significantly and showed a stronger positive correlation with significantly increasing temperature than insignificant precipitation variations during 1990–2015. The ASVA shrinkage and up-shifting of its boundary were attributed to climate warming, which facilitated the upper part of alpine meadow in the EQLM by releasing the low temperature limitation on vegetation growth.

Comparing Effects of FOXO3A and Residing in Urban Areas on Longevity: A Gene-Environment Interaction Study

2021 ◽  
Author(s):  
John S Ji ◽  
Linxin Liu ◽  
Lijing Yan ◽  
Yi Zeng
Keyword(s):  
Protective Effect ◽  
Effect Size ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fine Particulate Matter ◽  
Environment Interaction ◽  
Nucleotide Polymorphisms ◽  
Gene Environment Interaction ◽  
Gene Environment

Abstract Forkhead box O3 (FOXO3A) is a candidate longevity gene. Urban residents are also positively associated with longer life expectancy. We conducted a gene-environment interaction to assess the synergistic effect of FOXO3A and urban/rural environments on mortality. We included 3085 older adults from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We used single nucleotide polymorphisms (SNPs) rs2253310, rs2802292, and rs4946936 to identify the FOXO3A gene and classified residential locations as "urban" and "rural." Given the open cohort design, we used the Cox-proportional hazard regression models to assess the mortality risk. We found the minor allele homozygotes of FOXO3A to have a protective effect on mortality [HR (95% CI) for rs4946936 TT vs. CC: 0.807 (0.653, 0.996); rs2802292 GG vs TT: 0.812 (0.67, 0.985); rs2253310 CC vs. GG: 0.808 (0.667, 0.978)]. Participants living in urban areas had a lower risk of mortality [HR of the urban vs. the rural: 0.854 (0.759, 0.962)]. The interaction between FOXO3A and urban and rural regions was statistically significant (pinteraction<0.01). Higher air pollution (fine particulate matter: PM2.5) and lower residential greenness (Normalized Difference Vegetation Index: NDVI) both contributed to higher mortality. After adjusting for NDVI and PM2.5, the protective effect size of FOXO3A SNPs was slightly attenuated while the protective effect size of living in an urban environment increased. The effect size of the beneficial effect of FOXO3 on mortality is roughly equivalent to that of living in urban areas. Our research findings indicate the effect of places of residence and genetic predisposition of longevity are intertwined.

scholarly journals Spatial analysis of damaged vegetation in the Mianyuan River basin after the Wenchuan Earthquake

2015 ◽  
Vol 3 (5) ◽  
pp. 3225-3250
Author(s):  
H. Z. Zhang ◽  
J. R. Fan ◽  
X. M. Wang ◽  
T. H. Chi ◽  
L. Peng
Keyword(s):  
Slope Stability ◽  
Wenchuan Earthquake ◽  
River Basin ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Probabilistic Approach ◽  
Model Development ◽  
Slope Aspect ◽  
2008 Wenchuan Earthquake ◽  
Elevation Model

Abstract. The 2008 Wenchuan earthquake destroyed large areas of vegetation. Presently, these areas of damaged vegetation are at various stages of recovery. In this study, we present a probabilistic approach for slope stability analysis that quantitatively relates data on earthquake-damaged vegetation with slope stability in a given river basin. The Mianyuan River basin was selected for model development, and earthquake-damaged vegetation and post-earthquake recovery conditions were identified via the normalized difference vegetation index (NDVI), from multi-temporal (2001–2014) remote sensing images. DSAL (digital elevation model, slope, aspect, and lithology) spatial zonation was applied to characterize the survival environments of vegetation, which were used to discern the relationships between successful vegetation regrowth and environmental conditions. Finally, the slope stability susceptibility model was trained through multivariate analysis of earthquake-damaged vegetation and its controlling factors (i.e. topographic environments and material properties). Application to the Subao River basin validated the proposed model, showing that most of the damaged vegetation areas have high susceptibility levels (88.1% > susceptibility level 3, and 61.5% > level 4). Our modelling approach may also be valuable for use in other regions prone to landslide hazards.

scholarly journals Explicitly Identifying the Desertification Change in CMREC Area Based on Multisource Remote Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3170
Author(s):  
Zemeng Fan ◽  
Saibo Li ◽  
Haiyan Fang
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Net Primary Productivity ◽  
Regression Tree ◽  
Google Earth ◽  
Classification And Regression Tree ◽  
Support Vector ◽  
Driving Mechanisms

Explicitly identifying the desertification changes and causes has been a hot issue of eco-environment sustainable development in the China–Mongolia–Russia Economic Corridor (CMREC) area. In this paper, the desertification change patterns between 2000 and 2015 were identified by operating the classification and regression tree (CART) method with multisource remote sensing datasets on Google Earth Engine (GEE), which has the higher overall accuracy (85%) than three other methods, namely support vector machine (SVM), random forest (RF) and Albedo-normalized difference vegetation index (NDVI) models. A contribution index of climate change and human activities on desertification was introduced to quantitatively explicate the driving mechanisms of desertification change based on the temporal datasets and net primary productivity (NPP). The results show that the area of slight desertification land had increased from 719,700 km2 to 948,000 km2 between 2000 and 2015. The area of severe desertification land decreased from 82,400 km2 to 71,200 km2. The area of desertification increased by 9.68%, in which 69.68% was mainly caused by human activities. Climate change and human activities accounted for 68.8% and 27.36%, respectively, in the area of desertification restoration. In general, the degree of desertification showed a decreasing trend, and climate change was the major driving factor in the CMREC area between 2000 and 2015.

scholarly journals Revealing the Fingerprint of Climate Change in Interannual NDVI Variability among Biomes in Inner Mongolia, China

2020 ◽  
Vol 12 (8) ◽  
pp. 1332 ◽  
Author(s):  
Linghui Guo ◽  
Liyuan Zuo ◽  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Yongling Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Lag ◽  
Growing Season ◽  
Climate Fluctuations ◽  
Temperature And Precipitation ◽  
Lag Effect

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982–2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.

scholarly journals Effect of Residential Greenness and Nearby Parks on Respiratory and Allergic Diseases among Middle School Adolescents in a Chinese City

2019 ◽  
Vol 16 (6) ◽  
pp. 991 ◽  
Author(s):  
Linyan Li ◽  
Jaime Hart ◽  
Brent Coull ◽  
Shi-jie Cao ◽  
John Spengler ◽  
...  
Keyword(s):  
Middle School ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Health Effect ◽  
Allergic Diseases ◽  
Developed Countries ◽  
School Students ◽  
Urban Forms ◽  
Chinese City

Research on the health impacts of green environments has mainly been conducted in developed countries. Differences in the urban forms between China and Western countries make it essential to understand the role of greenspace in Chinese settings. From 2014 to 2015, middle school students (n = 5643) in Suzhou, China were enrolled in a study on the health effect of residential greenness. The normalized difference vegetation index (NDVI) and distance to the nearest park were calculated for each home address. Logistic regression was performed to test associations between exposure and self-reported doctor diagnoses of asthma, pneumonia, rhinitis, and eczema, adjusting for important confounders. No statistically significant associations were observed for any seasonal NDVI-based measures. However, the proximity of the participants’ residences to the closest park showed an inverse relationship to reported symptoms. The odds ratios for the furthest quartile compared to the closest quartile based on the distance to the nearest park were 0.58 (95% CI: 0.35, 0.99), 0.70 (95% CI: 0.50, 0.96), 0.92 (95% CI: 0.74, 1.15), 0.97 (95% CI: 0.76, 1.24), 0.86 (95% CI: 0.68, 1.10) for current asthma, ever asthma, ever pneumonia, ever rhinitis, and ever eczema, respectively. These findings focused on a single Chinese city and suggest that exposure to natural vegetation in urban areas may affect health through various pathways.

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