Increase In Normalized Difference Vegetation Index Research Articles

Analysis of Spatial Differentiation of NDVI and Climate Factors on the Upper Limit of Montane Deciduous Broad-Leaved Forests in the East Monsoon Region of China

The vertical transition zone of mountain vegetation is characterized by high species diversity, and the width of the transition zone may serve as an indirect indicator of climate change. However, research into the differential characteristics of vegetation response to climate changes at the boundary of vertical transition zones has been limited. This study employs MODIS and climate data spanning 2001 to 2018 to investigate spatiotemporal trends in precipitation (PRE), temperature (TMP), radiation (RAD), and Normalized Difference Vegetation Index (NDVI) across nine montane deciduous broad-leaved forests in the eastern monsoon region of China. It explores the time-lag and -accumulation effects of climatic variables on NDVI, quantifying their relative contributions to both its short-term and interannual variations. Results show that, notably, with the Qinling-Daba Mountains as a demarcation, northern regions exhibit significant increases in RAD (0.874–2.047 W m−2/a), whereas southern regions demonstrate notable rises in TMP (0.59–0.73 °C/10a). Areas of lower annual PRE correspond to the most rapid increases in annual average NDVI (5.045 × 10−3/a). NDVI’s lag time and cumulative duration responses to TMP are the shortest (0 and 2~4 periods), while its correlation with RAD is the strongest (0.815–0.975), generally decreasing from higher to lower latitudes. TMP significantly affects NDVI variations, impacting both short-term and interannual trends, with PRE driving short-term fluctuations and RAD dictating long-term shifts. This research provides critical data and a theoretical framework that enhances our understanding of how regional vegetation’s vertical zonation responds to climate change, thereby making a substantial contribution to the study of mountain vegetation’s diverse adaptability to climatic variations.

Residential greenness and chronic obstructive pulmonary disease in a large cohort in southern China: Potential causal links, risk trajectories, and mediation pathways

IntroductionResidential greenness may influence COPD mortality, but the causal links, risk trajectories, and mediation pathways between them remain poorly understood. ObjectivesWe aim to comprehensively identify the potential causal links, characterize the dynamic progression of hospitalization or posthospital risk, and quantify mediation effects between greenness and COPD. MethodsThis study was conducted using a community-based cohort enrolling individuals aged ≥ 18 years in southern China from January 1, 2009 to December 31, 2015. Greenness was characterized by normalized difference vegetation index (NDVI) around participants’ residential addresses. We applied doubly robust Cox proportional hazards model, multi-state model, and multiple mediation method, to investigate the potential causal links, risk trajectories among baseline, COPD hospitalization, first readmission due to COPD or COPD-related complications, and all-cause death, as well as the multiple mediation pathways (particulate matter [PM], temperature, body mass index [BMI] and physical activity) connecting greenness exposure to COPD mortality. ResultsOur final analysis included 581,785 participants (52.52% female.average age: 48.36 [Standard Deviation (SD): 17.56]). Each interquartile range (IQR: 0.06) increase in NDVI was associated with a reduced COPD mortality risk, yielding a hazard ratio (HR) of 0.88 (95 % CI: 0.81, 0.96). Furthermore, we observed per IQR (0.04) increase in NDVI was inversely associated with the risk of multiple transitions (baseline − COPD hospitalization, baseline − death, and readmission − death risks), especially a declined risk of all-cause death after readmission (HR = 0.66 [95 %CI: 0.44, 0.99]). Within the observed association between greenness and COPD mortality, three mediators were identified, namely PM, temperature, and BMI (HR for the total indirect effect: 0.773 [95 % CI: 0.703, 0.851]), with PM showing the highest mediating effect. ConclusionsOur findings revealed greenness may be a beneficial factor for COPD morbidity, prognosis, and mortality. This protective effect is primarily attributed to the reduction in PM concentration.

Determining the impacts of climate change and human activities on vegetation change on the Chinese Loess Plateau considering human-induced vegetation type change and time-lag effects of climate on vegetation growth

ABSTRACT Since the initiation of the Grain for Green Project (GFGP) in 1999, dramatic change in vegetation status on the Loess Plateau. Spatially, geographical detector was employed to detect dominant variables influencing the spatial arrangement of normalized difference vegetation index (NDVI). Temporally, lagged or accumulated monthly precipitation, temperature and standardized precipitation evapotranspiration indices (SPEIs) sensitive to the monthly NDVI were first detected for every individual pixel, and the correlation between the NDVI and meteorological elements with time-lag effects was established a random forest model of unchanged land cover, followed by attributing impacts of climatic alterations and human interventions through residual examination across changed land cover. The findings indicate that (1) precipitation, slope, and soil dominantly influence the spatial arrangement of the NDVI. (2) Precipitation in current the month and cumulative temperatures of the previous 1–2 months steadily affect vegetation growth significantly, the optimal accumulation time interval for SPEI around 2000 are 8 months and 4 months, respectively. (3) Increases in the average NDVI within woodland and meadow vegetation on the Loess Plateau were primarily driven by climate change before 2000, accounting for 76.2%, whereas after 2000 it was dominantly driven by human activities, accounting for 64.16%.

Estimation of blight and spot diseases severity in Ciherang and Ciliwung rice varieties based on vegetation index algorithms

Abstract. Bande LOS, Hasan A. 2024. Estimation of blight and spot diseases severity in Ciherang and Ciliwung rice varieties based on vegetation index algorithms. Biodiversitas 25: 1015-1021. Blight and spot diseases are often associated with rice plant, causing high disease severity and potentially reducing crop production. One effective disease management strategy is using resistant varieties and intensive disease monitoring through camera sensor technology and vegetation index-based image processing. Therefore, this study aimed to assess the severity of blight and spot diseases on two rice plant varieties based on vegetation indexes. Image recording was carried out on rice field and leaf samples of Ciherang and Ciliwung varieties. This was followed by image processing based on normalized difference vegetation index (NDVI) to determine the proportion of sick/healthy plants in the field and dark green color index (DGCI) to quantify disease severity. The results showed that the proportion of healthy plant in Ciliwung rice field was greater than in Ciherang as shown by NDVI. Based on DGCI, Ciliwung also had a relatively lower level of disease severity compared to Ciherang, although the difference was not statistically significant. Blight disease caused more severe damage to rice leaf than spot disease based on image processing results. Furthermore, a positive correlation was observed between the increase in DGCI and NDVI.

Greenness, Genetic Predisposition, and Tinnitus.

This study aimed to investigate the association between residential greenness and tinnitus and the potential interaction between greenness and genetic predisposition to tinnitus. The normalized difference vegetation index (NDVI) is used to measure residential greenness. The tinnitus is defined based on self-reported. In the cross-sectional analyses, logistic regression models are used for the baseline sample of the United Kingdom Biobank cohort. In the secondary analysis, a Cox proportional hazard model is used for a subsample of participants who completed the tinnitus questionnaire at follow-up. In the cross-sectional analysis including 106471 participants, higher residential greenness is associated with lower odds of tinnitus for each interquartile range increase in continuous NDVI, with an adjusted odds ratio of 0.97 (95% confidence interval: 0.95 to 0.99) for tinnitus. A similar association is observed in the longitudinal analysis, with an adjusted hazard ratio of 0.92 (95% confidence interval: 0.86 to 0.98) for the association of NDVI increased per interquartile range with incident tinnitus. Moreover, there is a significant interaction between greenness and genetic predisposition to tinnitus (P < 0.05). This study suggested that residential greenness is negatively associated with tinnitus. Greenness and genetic predisposition to tinnitus are found to have a significant interaction.

Abstract PR-009: Associations between PM2.5, vegetation density and childhood brain tumors: a case-control registry-based study from Texas 1995-2011

Abstract Background: Air pollution has been reported to be associated with some childhood cancers, namely leukemias. Less is known about air pollution and childhood brain tumor risk. In adult cancers, increasing vegetation density, or greenness, has been inversely associated with cancer incidence and survival. The interplay between air pollution and greenness, which co-occur, in childhood cancer etiology is unclear. Therefore, we sought to estimate the association between prenatal and early life exposure to air pollution, greenness, and childhood cancer in Texas (1995-2011). Materials and Methods: We included 1,316 individuals with a childhood brain tumor diagnosed &amp;lt;17 years of age and 109,762 age- and sex-matched controls. We linked birth certificate residential address to census tract annual average particulate matter 2.5 µg/m³ (PM2.5) and Normalized Difference Vegetation Index (NDVI) to approximate prenatal and early life exposure to greenness and air pollution. We estimated odds ratios (OR) and 95% confidence intervals (95% CI) as the measure of association between PM2.5 and NDVI interquartile range (IQR) increases and brain tumors. Models were adjusted for birth year, sex, maternal race/ethnicity, and area-level socioeconomic status (Yost index). Results: The following brain tumor types were included: ependymoma (n=136), astrocytoma (n=619), medulloblastoma (n=187), PNET (n=57), ATRT (n=54), and other gliomas (n=263). Average birth year PM2.5 and NDVI exposure levels were similar in cases and controls, 11 µg/m³ and 0.4, respectively. Each IQR increase (2.6 µg/m³) in PM2.5 was associated with ependymoma (OR: 1.27, 95% CI: 1.01-1.60) when adjusting for control-derived quartiles of NDVI. Conversely, after adjusting for PM2.5 quartiles, each IQR increase in NDVI (0.13) was inversely associated with ependymoma in those diagnosed at 0-4 years of age (OR: 0.75, 95% CI: 0.56-0.97) and with medulloblastoma in those aged 0-16 years at diagnosis (OR: 0.75, 95% CI: 0.62-0.91). There was no evidence of statistical interaction between NDVI and PM2.5 (all Likelihood Ratio Test p-values&amp;gt;0.05) for any brain tumors. Conclusions: Increasing residential air pollution during prenatal and early life increased the risk of childhood ependymoma in Texas independent of greenness. Conversely, increasing greenness exposure in prenatal and early life decreased the risk of ependymoma and medulloblastoma independent of PM2.5. These findings highlight the complex relationship between air pollution and greenness in childhood cancer etiology. Citation Format: Lindsay Williams, David Haynes, Jeannette Sample, Laura McGuinn, Thanh Hoang, Philip Lupo, Michael Scheurer. Associations between PM2.5, vegetation density and childhood brain tumors: a case-control registry-based study from Texas 1995-2011 [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr PR-009.

Exploring spatiotemporal dynamics of NDVI and climate-driven responses in ecosystems: Insights for sustainable management and climate resilience

Understanding the intricate relationship between climate variables and the Normalized Difference Vegetation Index (NDVI) is essential for effective ecosystem management. This study focuses on the spatiotemporal dynamics of NDVI and its interaction with climate variables in the ecologically diverse Khyber Pakhtunkhwa (KPK) Province, Pakistan, from 2000 to 2022. The research methodology involves analyzing satellite images and meteorological datasets to examine NDVI and surface latent heat flux (SHF), total precipitation (TPP), temperature (T), soil temperature (ST), and total pressure (TP). KPK Province's ecological significance and complex climate-vegetation interactions drive the selection of this study area. The study uses multiple linear regression analysis to investigate how T, TPP, SHF, and TP influence NDVI. The Mann-Kendall test detects trends, with Sen's slope estimator quantifying trend magnitudes. Additionally, correlation coefficients provide insights into long-term changes and association strengths. The findings highlight a consistent upward trend in mean NDVI over the 23 years, revealing an overall increase in NDVI, particularly in vegetation-dense areas where it rose from 0.27 to 0.32. The research showed an annual growth rate of 0.84% in the entire area, with specific vegetated zones exhibiting a slightly lower rate of 0.80%. However, the average yearly increase in NDVI is higher in vegetation-specific zones (0.00237) compared to the whole area (0.00151). This increase in NDVI occurs alongside a statistically significant decrease in SHF and PPT, suggesting a complex adaptation of vegetation to changing climate conditions in the KPK Province. In contrast, SHF exhibits a statistically significant negative slope of −5.952e-06 (p < 0.05), indicating a pronounced downward trend. Similarly, Sen's slope estimate for precipitation demonstrates a significant negative trend of −0.0001 (p < 0.05), showing diminishing precipitation. The study uncovers intricate linkages between climate variables and vegetation dynamics within KPK Province. These insights have far-reaching implications, guiding decision-making in land management, conservation efforts, and global climate resilience strategies. Ultimately, the research underscores the critical role of data-driven approaches in shaping a greener and more sustainable future.

Effects of fencing project on wind erosion reduction in Alpine grassland and its impact on the development of climbing dunes in southern Tibetan Plateau

AbstractAlpine grassland in the Tibetan Plateau (TP) of China is one of the most susceptible regions to wind erosion in recent decades. The fencing project, grassland enclosure using fencing, has been a common strategy for land degradation counteraction in the TP. However, the wind erosion reduction effects of fencing project remain largely unclear, especially in the regions lacking continuous observations such as Southern TP. In this study, a sand source area with fencing protection (fencing land, a mainly eroded grazing grassland before being fenced) and a near‐source climbing dune were selected to illustrate the effect of fencing project on wind erosion using 137Cs and 210Pbex tracing techniques. An adjacent perennial grazing land was selected for comparison. The results showed that the wind erosion rate in sand source area was 17.18 t·ha−1·year−1 before the implementation of project, while that was −6.67 t·ha−1·year−1 since fencing. The wind erosion rates in perennial grazing land were 24.91 t·ha−1·year−1 for 20 years ago to 1963 and 24.33 t·ha−1·year−1 for almost 20 years. The normalized difference vegetation index (NDVI) of sand source area increased from 0.098 before fencing to 0.137 after fencing; the latter was 1.63 times higher than that of grazing land during the same period. After the implementation of fencing project in sand source area, it was found that the sand supply to the climbing dune was mainly reduced, thus stabilizing it and promoting NDVI increase, especially in the middle‐lower part of the climbing dune. These results would benefit the evaluation of grassland restoration effectiveness in the TP.

Residential surrounding greenness and the incidence of childhood asthma: Findings from a population-based cohort in Ontario, Canada

Several epidemiological studies have investigated the possible role that living in areas with greater amounts of greenspace has on the incidence of childhood asthma. These findings have been inconsistent, and few studies explored the relevance of timing of exposure. We investigated the role of residential surrounding greenness on the risk of incident asthma using a population-based retrospective cohort study. We included 982,131 singleton births in Ontario, Canada between 2006 and 2013. Two measures of greenness, the Normalized Difference Vegetation Index (NDVI) and the Green View Index (GVI), were assigned to the residential histories of these infants from pregnancy through to 12 years of age. Longitudinally-based diagnoses of asthma were determined by using provincial administrative health data. The extended Cox hazards model was used to characterize associations between greenness measures and asthma (up to age 12 years) while adjusting for several risk factors. In a fully adjusted model, that included a term for traffic-related air pollution (NO2), we found no association between an interquartile range increase (0.08) of the NDVI during childhood and asthma incidence (HR = 0.99; 95 % CI = 0.99–1.01). In contrast, we found that an 0.08 increase in NDVI during childhood reduced the risk of asthma in children 7–12 years of age by 14 % (HR = 0.86, 95 % CI:0.79–0.95). Seasonal differences in the association between greenness and asthma were noted. Our findings suggest that residential proximity to greenness reduces the risk of asthma in children aged 7–12.

Dominance of soil moisture over aridity in explaining vegetation greenness across global drylands

Drylands are one of the most sensitive areas to climate change. Despite being characterized by water scarcity and low precipitation, drylands support a wide range of green biodiversity and nearly 40 % of the global population. However, the climate change impacts on dryland characteristics and vegetation dynamics are debatable as the reasons remain poorly understood. Here, we use hydro-meteorological variables from ERA5 reanalysis and GIMMS-NDVI to analyze the changes in dryland aridity and vegetation greenness in the eight selected global dryland regions. The total dryland area (excluding hyperarid) has increased by 12 %, while arid, semiarid, and dry sub-humid areas have increased by 10.5 %, 8 %, and 25 %, respectively. We find a significant increase in aridity in drylands across the globe, except for South Asia. A decrease (increase) in precipitation is the major driver for a significant increase (decrease) in dryland aridity, with a notable contribution from climate warming. Despite decreasing trends in precipitation, vegetation greenness has significantly increased in most dryland regions due to increased soil moisture. Cropland expansion in Europe, Asia, and Australia resulted in the maximum increase in NDVI (Normalized Difference Vegetation Index) in dryland regions. The highest increase, with a ΔNDVI of 0.075, was observed in South Asia. The enhanced vegetation greenness observed is attributed to the expansion of croplands in recent decades, which has increased soil moisture. Overall, we show that monitoring soil moisture variability can provide a more robust explanation for vegetation greenness in the global drylands than aridity change. Moreover, human interventions of climatic alteration through land use change practices, such as cropland expansion, cannot be ignored while explaining the ecosystem dynamics of the drylands.

Residential surrounding greenness is not associated with incident breast cancer in young women in Ontario, Canada

ObjectivesEnvironmental exposures play an important role in the development of breast cancer. The incidence of breast cancer is increasing in young women, and its etiology differs from that of older women. Epidemiological studies have provided mixed evidence about whether proximity to urban greenness reduces the risk of breast cancer, but few studies have evaluated this risk in younger women.MethodsWe investigated associations between residentially-based measures of greenness and breast cancer among participants of the Ontario Environmental Health Study (OEHS). The OEHS was a case–control study of Ontario women, 18–45 years of age, who provided questionnaire data between 2013 and 2015. The study included 465 cases diagnosed with a pathologically confirmed primary diagnosis of breast cancer, and 242 population-based controls. Residentially-based measures of greenness, the Normalized Difference Vegetation Index (NDVI) and tree coverage percentage, at 100-, 250-, 500-, and 1,000-m buffers, were assigned to the residential histories of the women. Odds ratios and their 95% confidence intervals (CIs) were estimated using logistic regression, adjusted for potential confounders including traffic-related air pollution [nitrogen dioxide (NO2)].ResultsWe found no evidence that an increase in NDVI or tree coverage were significantly associated with breast cancer. The adjusted odds ratio of breast cancer in relation to an interquartile range increase (IQR) in the NDVI (500-m buffer) was 0.86 (95% CI = 0.59–1.13). Similarly, the odds ratio of breast cancer among those in the highest quartile of tree coverage (500-m buffer) relative to the lowest was 1.11 (95% CI = 0.59–2.07). Risk estimates for both measures of greenness did not vary substantially across different buffer distances. Exposure to NO2 was an important confounder in these associations.ConclusionsOur findings do not support the hypothesis that residential greenness reduces the risk of breast cancer among young women, while highlighting the importance of adjusting for air pollution.

Does urban greenness reduce loneliness and social isolation among Canadians? A cross-sectional study of middle-aged and older adults of the Canadian Longitudinal Study on Aging (CLSA).

Urban greenness has been shown to confer many health benefits including reduced risks of chronic disease, depression, anxiety, and, in a limited number of studies, loneliness. In this first Canadian study on this topic, we investigated associations between residential surrounding greenness and loneliness and social isolation among older adults. This cross-sectional analysis of the Canadian Longitudinal Study on Aging included 26,811 urban participants between 45 and 86 years of age. The Normalized Difference Vegetation Index (NDVI), a measure of greenness, was assigned to participants' residential addresses using a buffer distance of 500 m. We evaluated associations between the NDVI and (i) self-reported loneliness using the Center for Epidemiological Studies Depression Scale, (ii) whether participants reported "feeling lonely living in the local area", and (iii) social isolation. Logistic regression models were used to characterize associations between greenness and loneliness/social isolation while adjusting for individual socio-economic and health behaviours. Overall, 10.8% of participants perceived being lonely, while 6.5% reported "feeling lonely in their local area". Furthermore, 16.2% of participants were characterized as being socially isolated. In adjusted models, we observed no statistically significant difference (odds ratio (OR) = 0.99; 95% confidence interval (CI) 0.93-1.04) in self-reported loneliness in relation to an interquartile range (IQR) increase of NDVI (0.06). However, for the same change in greenness, there was a 15% (OR = 0.85; 95% CI 0.72-0.99) reduced risk for participants who strongly agreed with "feeling lonely living in the local area". For social isolation, for an IQR increase in the NDVI, we observed a 7% (OR = 0.93; 95% CI 0.88-0.97) reduction in prevalence. Our findings suggest that urban greenness plays a role in reducing loneliness and social isolation among Canadian urbanites.

Maternal greenness exposure and preterm birth in Brazil: A nationwide birth cohort study

In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%–2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

Arctic tundra shrubification can obscure increasing levels of soil erosion in NDVI assessments of land cover derived from satellite imagery

Monitoring soil erosion in the Arctic tundra is complicated by the highly fragmentated nature of the landscape and the limited spatial resolution of even high-resolution satellite data. The expansion of shrubs across the Arctic has led to substantial changes in vegetation composition that alter the spectral reflectance and directly affect vegetation indices such as the normalized difference vegetation index (NDVI), which is widely applied for environmental monitoring. This change can mask soil erosion if datasets with too coarse spatial resolutions are used, as increases in NDVI driven by shrub expansion can obscure concurrent increases in barren land cover. Here we created land cover maps from a multispectral uncrewed aerial vehicle (UAV) and land cover survey and assessed satellite imagery from PlanetScope, Sentinel-2 and Landsat-8 for several areas in north-eastern Iceland. Additionally, we used a novel application of the Shannon evenness index (SHEI) to evaluate levels of pixel mixing. Our results show that shrub expansion can lead to spectral confusion, which can obscure soil erosion processes and emphasize the importance of considering spatial resolution when monitoring highly fragmented landscapes. We demonstrate that remote sensing data with a resolution < 3 m greatly improves the amount of information captured in an Icelandic tundra environment. The spatial resolution of Landsat data (30 m) is inadequate for environmental monitoring in our study area. We found that the best platform for monitoring tundra land cover is Sentinel-2 when used in combination with multispectral UAV acquisitions for validation. Our study has the potential to improve environmental monitoring capabilities by introducing the use of SHEI to assess pixel mixing and determine optimal spatial resolutions. This approach combined with comparing remote sensing imagery of different spatial and time scales significantly advances our comprehension of land cover changes, including greening and soil degradation, in the Arctic tundra.

The spatio‐temporal influences of habitat heterogeneity on the community structure of avian feeding guilds in human‐dominated landscapes of the East African miombo woodlands

AbstractHabitat heterogeneity plays a vital ecological role in influencing community ecology dynamics. We evaluated the relationship between habitat heterogeneity and land‐use cover with avian community structure in the human‐dominated landscape of the Katavi‐Rukwa ecosystem in Tanzania. We used the fixed‐radius point count method to record birds in different habitats. We calculated the relative abundances and the Shannon‐Wiener diversity index of bird guilds across habitats as well as the Normalised Difference Vegetation Index (NDVI) and estimated land‐use cover of the study area from Landsat 8 images. We grouped birds into five major guilds: Insectivore, Granivore, Omnivore, Carnivore and Nectarivore. Among the guilds, Insectivores, Omnivores, Nectarivores and Carnivores were positively correlated with an increase in NDVI, while Granivores were negatively correlated with an increase in NDVI. Among the habitats, woodland had high species diversity whereas riverine had low species diversity. Our findings highlight the importance of habitat heterogeneity in biodiversity conservation in human‐dominated landscapes, and we suggest implementing conservation in these landscapes.

Exploring NDVI change patterns across the Tibetan Plateau at the hillslope scale using geomorphons

ABSTRACTWithin the Tibetan Plateau (TP), grassland degradation is of great concern, and there is a need to better understand the spatial variability and landscape patterns in grassland degradation across the TP. This study explores potential patterns in grassland degradation, estimated using Landsat-derived normalized difference vegetation index (NDVI) growing season change products generated by a prior study. Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM)-derived geomorphons, topographic slope and the topographic position index (TPI) were used to explore grassland degradation and assess whether changes in growing season NDVI are associated with specific grasslands or landforms. An increase in NDVI within the TP was observed especially during the 1990 to 2018 and 2000 to 2018 time periods. Higher growing season median NDVI change values were found for the Southeast Tibet Shrublands and Meadows (SETSM) and TP Alpine Shrublands and Meadows (TPASM) grasslands in comparison to the other grassland types analysed, suggesting a more pronounced greening trend in the eastern portion of the plateau in comparison to the western portion. Small differences in NDVI change were observed for different geomorphon-based landforms, while topographic slope and TPI showed only modest correlations with NDVI change for all time periods and grassland types. More localized patterns of grassland degradation were masked by the widespread greening trends. Further analysis of only pixels that experienced a decreasing NDVI magnitude of less than or equal to −0.1 also generally suggested more change in the SETSM and TPASM. While this study generally supports the use of geomorphons as an analysis and aggregating unit for studying change patterns at the hillslope scale, more research is required to fully grasp the dynamics of landscape change at the hillslope scale in the TP.

Study on the changes in concentration of air pollutants and influencing factors in road green spaces in Nanjing City during autumn and winter

Based on low-altitude remote sensing of UAV and field monitoring on three roads in Nanjing, this study used the normalized difference vegetation index (NDVI) one-dimensional linear regression analysis, correlation analysis to explore the relationship between different influencing factors and concentration changes of different pollutants in autumn and winter. The results showed that: 1. The use of UAV low-altitude remote sensing to collect vegetation data at road scale coould reflect the change characteristics of road vegetation in autumn and winter, especially the proportion of deciduous plants: among three roads, the ratio of deciduous plants to road sections showed that Mengdu Street < Mufu South Road < Jiyin Avenue; 2. Seasonal variation had a significant effect on temperature. In autumn, the concentration of NO2 in Jiyin Avenue and Mufu South Road exceeded the standard limit of 24 h average level 2 concentration, which meant the air pollution was relatively serious. 3. The increase of NDVI could reduce the concentration of atmospheric pollutants. Also, the study found that humidity had the greatest correlation with PM2.5 and PM10, temperature had the greatest correlation with NO2 and air pressure had the greatest correlation with O3. In addition, the four pollutants had positive correlation with each other.

Temperate grassland vegetation restoration influenced by grazing exclusion and climate change

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003–0.0319 year−1. The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration.

Temporal and Spatial Variations in the Normalized Difference Vegetation Index in Shanxi Section of the Yellow River Basin and Coal Mines and Their Response to Climatic Factors

Investigating the spatiotemporal variations in the Normalized Difference Vegetation Index (NDVI) in the Shanxi section of the Yellow River Basin and its coal mining areas holds significant importance for dynamic vegetation monitoring and mining area management. This study employs MODIS NDVI data and combines various analytical methods, including trend analysis and coefficient of variation analysis, to reveal the characteristics of NDVI spatiotemporal variations and their response to climatic factors in the study area. The results indicate the following: (1) The overall NDVI in the Shanxi section of the Yellow River Basin exhibits a growth trend with an annual growth rate of 1.82% and a 36% increase. Among the mining areas, the NDVI increase is most prominent in the Hebaopian mining area with a 100% growth, while the QinYuan mining area shows the lowest increase at 21%; (2) The NDVI in the Shanxi section of the Yellow River Basin displays high fluctuations, with areas of moderate and high fluctuations accounting for 54.39% of the total. The Hebaopian mining area has a substantial portion of high-fluctuation areas at 38.85%; (3) According to the Hurst index analysis, future vegetation changes in the Shanxi section of the Yellow River Basin are uncertain, with approximately 9.77% of areas expected to continue improving; (4) The variations in the NDVI and climatic factors across the Shanxi section of the Yellow River Basin display spatial heterogeneity. The NDVI exhibits a positive correlation with both temperature and precipitation, with the correlation with precipitation being more pronounced than that with temperature. Precipitation exerts a more significant influence on the NDVI than temperature. These findings not only provide scientific guidance for vegetation restoration and area management in the Shanxi section of the Yellow River Basin and its mining areas but also serve as a scientific basis for decision making regarding vegetation management under the influence of climate change and human activities.

Critical windows of greenness exposure during preconception and gestational periods in association with birthweight outcomes

Few studies have examined the association between greenness exposure and birth outcomes. This study aims to identify critical exposure time windows during preconception and pregnancy for the association between greenness exposure and birth weight. A cohort of 13 890 pregnant women and newborns in Shanghai, China from 2016–2019 were included in the study. We assessed greenness exposure using Normalized Difference Vegetation Index (NDVI) during the preconception and gestational periods, and evaluated the association with term birthweight, birthweight z-score, small-for-gestational age, and large-for-gestational age using linear and logistic regressions adjusting for key maternal and newborn covariates. Ambient temperature, relative humidity, ambient levels of fine particles (PM2.5) and nitrogen dioxide (NO2) assessed during the same period were adjusted for as sensitivity analyses. Furthermore, we explored the potential different effects by urbanicity and park accessibility through stratified analysis. We found that higher greenness exposure at the second trimester of pregnancy and averaged exposure during the entire pregnancy were associated with higher birthweight and birthweight Z-score. Specifically, a 0.1 unit increase in second trimester averaged NDVI value was associated with an increase in birthweight of 10.2 g (95% CI: 1.8–18.5 g) and in birthweight Z-score of 0.024 (0.003–0.045). A 0.1 unit increase in an averaged NDVI during the entire pregnancy was associated with 10.1 g (95% CI: 1.0–19.2 g) increase in birthweight and 0.025 (0.001–0.048) increase in birthweight Z-score. Moreover, the associations were larger in effect size among urban residents than suburban residents and among residents without park accessibility within 500 m compared to those with park accessibility within 500 m. Our findings suggest that increased greenness exposure, particularly during the second trimester, may be beneficial to birth weight in a metropolitan area.