Effects Of Normalized Difference Vegetation Index Research Articles

Gene-environment interaction in the association of residential greenness and 25(OH) vitamin D

There is increasing awareness for beneficial health effects of green space surrounding the home, but the underlying mechanisms are not yet fully understood and challenging to study given the correlation with other exposures. Here, the association of residential greenness and vitamin D including a gene-environment interaction is investigated. 25-hydroxyvitamin D (25(OH)D) was measured by electrochemiluminescence at ages 10 and 15 years in participants of two German birth cohorts GINIplus and LISA. Greenness was measured using the Landsat-derived Normalized Difference Vegetation Index (NDVI) in a 500 m buffer surrounding the home. Linear and logistic regression models were applied at both time points adjusted for several covariates (N10Y = 2,504, N15Y = 2,613). In additional analyses vitamin D-related genes, physical activity, time spent outdoors, supplements, and measurement season were investigated as potential confounders or effect modifiers. A 1.5-SD increase in NDVI was significantly associated with increased 25(OH)D values at ages 10 and 15 years (β10y = 2.41 nmol/l, p=<0.01; β15y = 2.03 nmol/l, p = 0.02). In stratified analyses, the associations were not seen in participants spending more than 5 h/day outside in summer, having a high physical activity level, taking supplements, or being examined during the winter season. In a subset (n = 1,732) with genetic data, a significant gene-environment interaction of NDVI with CYP2R1, an upstream gene in 25(OH)D synthesis, was observed at age 10 years. When investigating 25(OH)D sufficiency, defined as values above 50 nmol/l, a 1.5-SD increase in NDVI was associated with significantly higher odds of having sufficient 25 (OH)D levels at age 10 years (OR = 1.48, 1.19–1.83). In conclusion, robust associations between residential greenness and 25 (OH)D levels were observed in children and adolescents independent of other confounders and additionally supported by the presence of a gene-environment interaction. Effects of NDVI were stronger in those having lower vitamin D levels at age 10 years due to their covariate profile or genetically lower 25(OH)D synthesis.

Interaction between ecosystem service supply and urbanization in northern China

Rapid urbanization has profoundly changed ability of ecosystem to supply welfare and resulted a series of environmental issues, in turn, such results not only affected the economic growth, but also the quality of sustainable development. Therefore, deeply understanding the interaction between ecosystem service (ES) supply and urbanization is of great significance. As a case study of northern China, we attempt to build an effective framework to evaluate past and future states of the interaction between ES supply and urbanization from quantification spatiotemporal pattern of coupling coordination degree (CD), decoupling path exploration, driving factor analysis to grey prediction model construction. It tries to better improve the interaction between ES supply and urbanization, as well as provide some effective policies for local condition. Results showed that the synthesis coefficient of urbanization (URSC) and CD has been significantly improved from 1995 to 2020 at province scale, while the synthesis coefficient of ES supply (ESSC) and decoupling index score are fluctuating. All of indicators revealing differences between the west and east regions. The east region has the highest levels of ESSC, URSC, CD and decoupling index score during the last twenty-five years. The driving factors including annual precipitation (Precipitation), normalized difference vegetation index (NDVI), cropland area (Cropland), grassland area (Grassland), unused land area (Unused land) all have a spatiotemporal impact on the CD with divergent significances, among which the effect of NDVI is the most significant. Finally, the grey prediction model was applied to predict the ESSC, URSC, CD and decoupling index in the future. The findings reveal a growing state for ESSC and CD in province scale, while a decline state of URSC. Based on the aforementioned results, some scientific policies were proposed for different regions to improve sustainable development.

Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop: a case study from Punjab, India

Soil moisture is essential for water resources management, yet accurate information of soil moisture has been a challenge. The major goal was to parametrize the Modified Water Cloud Model (MWCM). The Sentinel-1A data of winter wheat crop was collected for two weeks. Concurrently, in-situ soil moisture data was collected using Time Domain Reflectometer (TDR). A parametric scheme was used for the retrieval of the VV polarization of Sentinel-1A. The effect of NDVI as a vegetation descriptors (V1 and V2) on total VV backscatter (σ 0) was analyzed. The calibration showed NDVI has the potential to influence Water Cloud Model (WCM) and vegetation descriptors; hence it is recommended to calibrate the MWCM. The coefficient of determination (R2 = 0.83) showed a good agreement between observed and estimated soil moisture. Therefore, this approach help improve soil moisture prediction, and can be applied to determine soil moisture more accurately for winter crops, grasses, and pasture lands.

Lower Noise Annoyance Associated with GIS-Derived Greenspace: Pathways through Perceived Greenspace and Residential Noise.

Growing amounts of evidence support an association between self-reported greenspace near the home and lower noise annoyance; however, objectively defined greenspace has rarely been considered. In the present study, we tested the association between objective measures of greenspace and noise annoyance, with a focus on underpinning pathways through noise level and perceived greenspace. We sampled 720 students aged 18 to 35 years from the city of Plovdiv, Bulgaria. Objective greenspace was defined by several Geographic Information System (GIS)-derived metrics: Normalized Difference Vegetation Index (NDVI), tree cover density, percentage of green space in circular buffers of 100, 300 and 500 m, and the Euclidean distance to the nearest structured green space. Perceived greenspace was defined by the mean of responses to five items asking about its quantity, accessibility, visibility, usage, and quality. We assessed noise annoyance due to transportation and other neighborhood noise sources and daytime noise level (Lday) at the residence. Tests of the parallel mediation models showed that higher NDVI and percentage of green space in all buffers were associated with lower noise annoyance, whereas for higher tree cover this association was observed only in the 100 m buffer zone. In addition, the effects of NDVI and percentage of green space were mediated by higher perceived greenspace and lower Lday. In the case of tree cover, only perceived greenspace was a mediator. Our findings suggest that the potential for greenspace to reduce noise annoyance extends beyond noise abatement. Applying a combination of GIS-derived and perceptual measures should enable researchers to better tap individuals’ experience of residential greenspace and noise.

Urban Residential Greenness and Adiposity: A Longitudinal Cohort Study in Stockholm County

Background/Aim: This longitudinal cohort study, using objectively measured exposure and outcomes, aims to explore the association between residential green space and body fat distribution, potentially mediated via psycho-endocrine mechanisms. Methods: Based on the Stockholm Diabetes Prevention Program (SDPP), this study included 5 355 subjects from Stockholm County aged 35-56 years at recruitment in 1992-1994, and followed up 2002-2006. We defined surrounding greenness as a time-weighted average of satellite-based Normalized Difference Vegetation Index (NDVI) at 30 m×30 m resolution during 1990-2015 in buffers of 100 m, 250 m, and 500 m around participants’ place of residence. Multiple linear regressions with adjustment for potential confounders at individual and contextual level, including behavioural, socio-economic and environmental factors (traffic-related air pollution and noise), were used to estimate the change in BMI, waist circumference and waist-hip ratio. Results: Waist circumference increased on average by 0.51 cm/year in this population, and time-weighted NDVI in 500 m buffers ranged 0.2-0.7. Higher levels of surrounding greenness were associated with reduced increase in waist circumference, with 0.78 cm less increase in waist circumference per year for one unit difference in NDVI, (95% CI 0.16-1.41). This is equivalent to an average annual increase of 0.60 cm among the 10 percent least exposed to greenness, compared to 0.43 cm among the 10 percent most exposed. A modest but yet statistically significant association was observed for the waist-hip ratio, but no significant association was found between NDVI and change in BMI. Using the 100 m and 250 m buffers generated less clear associations than for 500 m. Conclusions: Our findings suggest a beneficial impact of surrounding greenness on waist circumference and waist-hip ratio. The absence of a statistically significant relationship between NDVI and BMI suggests that the effect of NDVI may be mediated by the cortisol-induced differences in body fat distribution.

Relating temperature trends to the normalized difference vegetation index in Las Vegas

This research examines the relation between temperature trends and vegetation change in Las Vegas. A temperature time series is modeled as a superposition of a linear trend and an annual cycle. The model is used to estimate the multi-annual temperature rate of change, which is related to changes in vegetation cover. The change in vegetation cover is estimated using an annual average normalized difference vegetation index (NDVI). The model reveals a general trend of decreasing temperature in Las Vegas from 2000 to 2010. This decrease is less than 0.2 Kelvin per year (K/yr) in older housing developments; however, areas developed during the past decade (North Las Vegas and Southern Highlands) exhibit a decrease of greater than 0.2 K/yr. This temperature change has a correlation of −0.655 with changes in the annual average NDVI. Results reveal that in an arid environment, new housing developments that have an increase in vegetation have a cooling affect. The long-term trend reveals a warming trend. This research provides a useful insight into the effect of NDVI on temperature trends in Las Vegas.

Estimation of NDVI Images Using Geostatistical Methods

The objective of this article is to examine the effect of NDVI (Normalized Difference Vegetation Index) images estimation using four geostatistical algorithms: Ordinary Kriging (OK), Universal Kriging (UK), Indicator Kriging (IK), and Sequential Indicator Simulation (SIS). Using the undersampled NDVI data obtained from a NOAA/AVHRR image, both estimates and variances from the three Kriging methods are obtained. It is found out that the images of estimates from Ordinary Kriging and Universal Kriging can both successfully restore the overall trend of the original image, but the image of estimates from Indicator Kriging is not good enough. It has also been found out that the images of variances from Ordinary Kriging and Universal Kriging only reflect the sampling configuration because they are independent of the local data values. However, owing to the fact that variances from Indicator Kriging are conditional on the local data values, they show the errors of estimates perfectly, and the values of variances from Indicator Kriging are consistent with the uncertainty of the original NDVI data. Using the undersampled data of NDVI, the multiple realizations from SIS exhibit strong variability, and the mean image from multiple realizations has a clear smoothing effect, with a low exactness. However, the image of variances from multiple realizations can successfully show the distribution of data uncertainty.

Temporal Variations in the Usefulness of Normalized Difference Vegetation Index as a Predictor for &lt;I&gt;Ixodes ricinus&lt;/I&gt; (Acari: Ixodidae) in a &lt;I&gt;Borrelia lusitaniae&lt;/I&gt; Focus in Tuscany, Central Italy

Host-seeking ticks were collected during monthly dragging sessions from November 2004 through October 2006 in Tuscany, central Italy. Normalized difference vegetation index (NDVI), which was calculated from Landsat ETM+ 7 remote sensing data recorded in August 2001, was significantly correlated with numbers of host-seeking immature Ixodes ricinus L. (Acari: Ixodidae) during periods of relatively low rainfall such as summer 2005 (Spearman's p = 0.78, P < 0.001 for nymphs in July) and to a lower extent in spring-summer 2006. In spring 2005, when rainfall was relatively high, the correlation was weak and not statistically significant. Generalized estimating equations (GEEs), taking into account repeated sampling of the same dragging sites, were used to model the effects of NDVI and season on counts of host-seeking I. ricinus nymphs. Seasonal variations of the effect of NDVI yielded a significant NDVI-by-season interaction in the first year of the study (November 2004-October 2005), but not in the second year (November 2005-October 2006) when there was a 2.5-fold increase of the number of nymphs per 100-m dragging for every 0.1 unit increase in NDVI (95% confidence interval = 1.6, 3.0). Risk maps that were obtained based on GEE results confirmed that the predicted number of I. ricinus nymphs per 100 m was relatively homogeneous through the study area during the 2005 spring peak of activity. Conversely, in 2006, the predicted abundance of nymphs was greater in moist bottomland habitat (characterized by high NDVI) than in dry, typically Mediterranean, upland habitat.

Comparative study of potential evapotranspiration and interception evaporation by land cover over Mekong basin

AbstractPotential evapotranspiration is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P‐M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this article, the Shuttleworth–Wallace (S‐W) model is implemented to estimate the potential evapotranspiration from soil moisture (PET) and the potential evaporation from interception (PET0) directly in a form that recognizes vegetation diversity and temporal development without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme (IGBP) land cover classification. The spatial and temporal variation of the leaf area index (LAI) of vegetation is derived from the composite National Oceanic and Atmospheric Administration ‐ Advanced Very High Resolution Radiometer (NOAA‐AVHRR) normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit (CRU) database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S‐W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins.A comparison is made between the FAO‐56 method and the S‐W model when applied to the Mekong River basin for the period 1981–2000. The resulting estimates of RET and PET and their association with vegetation types and LAI are examined over the whole basin both annual and monthly and at five specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S‐W model not only reflects the change in climate but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET, and/or climatic variables, applying these relationships will likely result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of the vegetation. It is concluded that use of the implementation of the S‐W model described in this study results in a physically sound estimate of PET, which accounts for changing land surface conditions. Copyright © 2008 John Wiley &amp; Sons, Ltd.