Satellite-derived Normalized Difference Vegetation Index Research Articles

Observed interannual variability and projected scenarios of drought in the Chorotega region, Costa Rica

The observation-based analysis of drought development in the Chorotega region showed that, despite the area being relatively small, agricultural drought exhibits high spatial variability across the region. However, the lack of net radiation data hinders the capacity to provide reliable estimates of evapotranspiration (ET), affecting the assessment of drought occurrence, since its propagation across the hydrological system is very sensitive to the ET estimation method. The coarse resolution of satellite-derived Normalized Difference Vegetation Index (NDVI) products and the lack of information on irrigation in agricultural areas limits the ability to properly establish a relationship between drought and vegetation response. Based on the observations, the most prominent precipitation deficits occur between September and October (–100 mm on average), showing that changes in the large-scale circulation are responsible for the impact of severe drought in the region. In agreement with previous studies, El Niño-Southern Oscillation (ENSO) is the main modulator of the drought severity, with the warm ENSO phase favoring an enhanced drought development and its influence being more significant between August and October, displaying correlations greater than –0.6. The climate change projections under RCP4.5 and RCP8.5 scenarios suggest the intensification of drought events in the Chorotega region at mid-century, with the Tempisque-Bebedero basin being the most affected area in terms of precipitation decrease and warming. The projected scenarios correspond to an increase of 1 oC for mean temperature and more of 2 oC for minimum and maximum temperature in the 2050 horizon, as well as a decrease of 400 to 800 mm for annual precipitation under both RCPs.

Improving the Estimation of Rice Crop Damage from Flooding Events Using Open-Source Satellite Data and UAV Image Data

Having an additional tool for swiftly determining the extent of flood damage to crops with confidence is beneficial. This study focuses on estimating rice crop damage caused by flooding in Candaba, Pampanga, using open-source satellite data. By analyzing the correlation between Normalized Difference Vegetation Index (NDVI) measurements from unmanned aerial vehicles (UAVs) and Sentinel-2 (S2) satellite data, a cost-effective and time-efficient alternative for agricultural monitoring is explored. This study comprises two stages: establishing a correlation between clear sky observations and NDVI measurements, and employing a combination of S2 NDVI and Synthetic Aperture Radar (SAR) NDVI to estimate crop damage. The integration of SAR and optical satellite data overcomes cloud cover challenges during typhoon events. The accuracy of standing crop estimation reached up to 99.2%, while crop damage estimation reached up to 99.7%. UAVs equipped with multispectral cameras prove effective for small-scale monitoring, while satellite imagery offers a valuable alternative for larger areas. The strong correlation between UAV and satellite-derived NDVI measurements highlights the significance of open-source satellite data in accurately estimating rice crop damage, providing a swift and reliable tool for assessing flood damage in agricultural monitoring.

Aboveground Biomass Estimation and Time Series Analyses in Mongolian Grasslands Utilizing PlanetScope Imagery

Mongolia, situated in central Asia and bordered by Russia to the north and China to the south, experiences a semi-arid climate across most of its territory. Grasslands are pivotal in Mongolia’s agricultural sustainability and food security, facing rapid changes in the last two decades that underscore the ongoing need for innovative approaches to assess vegetation conditions. This study aims to evaluate grassland biomass measurement and prediction through the analysis of high-resolution satellite data. By conducting a time series assessment of grazing-induced changes in vegetation dynamics at the long-term monitoring sites of the Botanic Garden and Research Institute, Mongolian Academy of Sciences, we seek to refine our understanding. The investigation covers biomass estimation across various Mongolian grassland landscapes, encompassing desert, steppe, and mountain regions. Spanning the grassland growing season from May 2020 to October 2023, the research leveraged diverse ground data types, including surface reflectance measurements, geographic coordinates for satellite data correction, and aboveground dry biomass. These components were instrumental in developing a biomass estimation model reliant on establishing correlations between the satellite-derived Normalized Difference Vegetation Index and biomass. The predicted biomass facilitated the time series map analysis and dynamic analysis. The PlanetScope surface reflectance correlates strongly at 0.97 with field measurements, indicating robust relations. Biomass and the Normalized Difference Vegetation Index show correlations of 0.82 for dry grassland, 0.80 for mountain grassland, and 0.65 for desert grassland, with a combined correlation coefficient of 0.62, revealing distinct characteristics across these grasslands. Time series dynamic analysis reveals rising biomass differences between grazed and ungrazed areas, suggesting potential grassland degradation. Variations in the slope coefficient of biomass differences among grassland types indicate differing degradation patterns, emphasizing the need for effective grazing management practices to sustain and conserve Mongolian grasslands. This highlights the potential of remote sensing in monitoring and managing grassland ecosystems.

A protective role of urban greenspace on the association between night-time heat and suicide in Seoul, South Korea

Suicide, a leading cause of death among the youth, has shown a positive association with high temperatures. However, few studies have explored the association between tropical nights and suicide and the potential role of greenness on this association. We investigated the association between suicide and two hot night indices: hot night duration (HNd) and hot night excess (HNe), representing heat duration and excess heat during night-time. We also explored whether the association was modified by urban greenspace, measured by satellite-derived normalized difference vegetation index (NDVI), across 25 districts in Seoul, South Korea from 2000 to 2020. Based on the multi-district daily time-series data, we performed a space-time-stratified case-crossover analysis with a distributed lag linear model with lags of up to 7 d for HNd and HNe, adjusting for daily mean temperature and relative humidity. We added an interaction term between the hot night index and NDVI to assess the effect modification of greenness. In total, 14 693 suicides were included in this study. The relative risk (RR) of suicide per a 10% increase in HNd was 1.059 (95% CI: 1.017–1.103) in low NDVI areas and 1.031 (95% CI: 0.988–1.075) in high NDVI areas. The RR per a 1 °C increase in HNe was 1.011 (95% CI: 0.998–1.024) and 1.005 (95% CI: 0.992–1.018) in low and high NDVI areas, respectively. Greenspaces have expanded over time in all districts of Seoul, and the risk of suicide for night-time heat decreased over time in both low and high NDVI areas. Our findings suggest that exposure to night-time heat is associated with an increased risk of suicide, but this risk may be mitigated by greater greenspaces in urban areas. Prioritizing development and maintenance of urban greenspaces will be a critical co-benefit strategy for promoting public mental health in changing climates.

Residential greenspace and blood lipids in an essential hypertension population: Mediation through PM2.5 and chemical constituents

Fine particulate matter (PM2.5) adversely affects blood lipids, while residential greenspace exposure may improve blood lipids levels. However, the association between exposure to residential greenspace and blood lipids has not been adequately studied, especially in vulnerable populations (e.g. people with essential hypertension). This study aimed to assess the association between residential greenspace exposure and blood lipids, and to clarify whether PM2.5 and chemical constituents was mediator of it. We used a period (May 2010 to December 2011) from the Chinese national hypertension project. The residential greenspace was estimated using satellite-derived normalized difference vegetation index (NDVI). The generalized additive mixed model (GAMM) was used to assess the association between exposure to residential greenspace and blood lipids, and the mediation model was used to examine whether there was a mediating effect of PM2.5 and chemical constituents on that association. The exposure to residential greenspace was negatively associated with the decreased risk of dyslipidemia, especially short-term exposure. For example, the odd ratioshort-term for dyslipidemia was 0.915 (95% CI：0.880 to 0.950). This association was strengthened by physical activity and participants living in the North. PM2.5 and chemical constituents were important mediators in this association, with the proportion of mediators ranging from −5.02% to 26.33%. The association between exposure to residential greenspace and dyslipidemia in this essential hypertensive population, especially participants living in the North and doing daily physical activity, was mediated by PM2.5 and chemical constituents.

Exposure to Neighborhood Walkability and Residential Greenness and Incident Fracture

Emerging studies have suggested that environmental factors are associated with fracture. However, little is known about the association of neighborhood walkability and residential greenness with fracture. To investigate the association of long-term exposure to walkability and greenness with incident fracture and explore the potential interaction effect. This cohort study recruited participants aged 40 years or older in Ningbo, China from June 2015 to January 2018. Participants were observed for outcomes through February 2023, with data analysis conducted in March 2023. Neighborhood walkability was measured by a modified walkability calculation method according to a walk score tool. Residential greenness was assessed by satellite-derived normalized difference vegetation index (NDVI) within a 1000-m buffer. Incident fracture was ascertained according to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes via the Yinzhou Health Information System. Cox proportional hazards models were fit, with age as time scale to estimate the associations of walkability and greenness with fracture. Potential effect modification was explored by covariates, as well as the interactive effect of walkability and greenness. A total of 23 940 participants were included in this study with 13 735 being female (57.4%). The mean (SD) age at baseline was 63.4 (9.4) years. During a follow-up period of 134 638 person-years, 3322 incident fractures were documented. In the full adjusted model, every IQR increment in neighborhood walkability and residential greenness was associated with a hazard ratio (HR) of 0.88 (95% CI, 0.83-0.92) and 0.84 (95% CI, 0.80-0.89), respectively, for fracture. Furthermore, the association of greenness and fracture was greater with an increase in walkability. The HR (Q4 vs Q1) for greenness was 0.62 (95% CI, 0.46-0.82) in neighborhoods with the highest quartile of walkability. This population cohort study suggested that long-term exposure to neighborhood walkability and residential greenness were both associated with lower risk of incident fracture. The benefits of greenness increased in more walkable areas.

Associations between residential greenness and air pollution and the incident metabolic syndrome in a Thai worker cohort.

Increasing air pollution and decreasing exposure to greenness may contribute to the metabolic syndrome (MetS). We examined associations between long-term exposure to residential greenness and air pollution and MetS incidence in the Bangkok Metropolitan Region, Thailand. Data from 1369 employees (aged 52-71years) from the Electricity Generating Authority of Thailand cohort from 2002 to 2017 were analyzed. The greenness level within 500m of each participant's residence was measured using the satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The kriging approach was used to generate the average concentration of each air pollutant (PM10, CO, SO2, NO2, and O3) at the sub-district level. The average long-term exposure to air pollution and greenness for each participant was calculated over the same period of person-time. Cox proportional hazards models were used to analyze the greenness-air pollution-MetS associations. The adjusted hazard ratio of MetS was 1.42 (95% confidence interval (CI): 1.32, 1.53), 1.22 (95% CI: 1.15, 1.30), and 2.0 (95% CI: 1.82, 2.20), per interquartile range increase in PM10 (9.5μg/m3), SO2 (0.9ppb), and CO (0.3ppm), respectively. We found no clear association between NDVI or EVI and the incidence of MetS. On the contrary, the incident MetS was positively associated with NDVI and EVI for participants exposed to PM10 at concentrations more than 50μg/m3. In summary, the incidence of MetS was positively associated with long-term exposure to air pollution. In areas with high levels of air pollution, green spaces may not benefit health outcomes.

Association of greenness surrounding school with aggression among adolescents: A multi-site study in China

Association of greenness surrounding school with aggression among adolescents was not well understood. This study aimed to investigate the associations of greenness surrounding school with adolescents' total and sub-types of aggression and explore potential mediators underlying these associations. A multi-site study of 15,301 adolescents aged 11–20 years were recruited through a multistage, random cluster sampling across 5 representative provinces in mainland China. Satellite-derived Normalized Difference Vegetation Index (NDVI) values within circular buffers of 100 m, 500 m, and 1000 m surrounding school were used to indicate the adolescents' greenness exposure. We used the Chinese version of Buss and Warren's Aggression Questionnaire to assess total and sub-types of aggression. Daily concentrations of PM2.5, and NO2 were obtained from the China High Air Pollutants datasets. Per IQR increment of NDVI 100 m and 500 m surrounding school was associated with lower odds of total aggression; odds ratio [OR] with 95% CI was 0.958 (0.926–0.990) for the 100 m buffer and 0.963 (0.932–0.996) for the 500 m buffer, respectively. Similar associations can be observed in two sub-types of aggression, including verbal (NDVI 100 m: 0.960 (0.925–0.995); NDVI500m: 0.964 (0.930–0.999)) and indirect aggression (NDVI 100 m: 0.956 (0.924–0.990); NDVI500m: 0.953 (0.921–0.986)). There were no sex and age differences in the associations of school surrounding greenness with aggression, except that the beneficial associations of greenness exposure with total aggression (0.933(0.895–0.975) vs.1.005(0.956–1.056)), physical aggression (0.971(0.925–1.019) vs.1.098(1.043–1.156)), and hostility (0.942(0.901–0.986) vs.1.016(0.965–1.069)) were greater among participants aged ≥16 years than those aged<16 years. PM2.5 (proportion mediated estimates: 0.21; 95% CI: 0.08, 0.94) and NO2 (−0.78, 95% CI: −3.22, −0.37) mediated the association of NDVI 500 m surrounding school with total aggression. Our data indicated that exposure to greenness in school surroundings was associated with reduced aggression, particularly in verbal and indirect aggression. The presence of PM2.5 and NO2 partially mediated these associations.

Associations between Green Space Surrounding Kindergartens and Hyperactivity Behaviors among Chinese Preschool Children

Background: Attention deficit hyperactivity disorder (ADHD) affects approximately 2–7% of children worldwide and has become a global public health concern. The health effects of green space on ADHD in young children are unclear. We investigated associations between school-surrounding greenness and hyperactivity behaviors in preschool children. Methods: We performed a cross-sectional analysis using data of 66,678 preschool children (mean age: 3.53 years) from an on-going cohort in Shenzhen, China. The greenness surrounding kindergartens was measured using satellite-derived Normalized Difference Vegetation Index (NDVI) values at buffers of 250 m, 500 m, and 1000 m. Children’s hyperactivity behaviors were measured using the validated Conners’ Parent Rating Scale-Revised. We used generalized linear mixed models to assess the associations of greenness exposure with hyperactivity behaviors with adjustment for a variety of covariates. Results: Exposure to higher school-surrounding greenness was associated with lower prevalence of hyperactivity behaviors. In fully adjusted models, the odds ratio of hyperactivity behaviors in relation to an IQR (0.1) increase in NDVI at the 250 m buffer was 0.91 [confidence interval (CI): 0.84,0.98]. Consistent results were observed for greenness at the 500 m and 1000 m buffers. The negative association between greenness and hyperactivity behaviors was more pronounced in boys than in girls. Conclusions: Our findings suggest that higher levels of school-surrounding green spaces are associated with a lower risk of hyperactivity behaviors in preschool children.

Relationship between Greenness and Health Indicators in Urban Patients with Heart Failure

The environment has a significant impact on a person’s general well-being. Distance to green space has been found to be an important factor influencing health. Urban green spaces enhance people’s quality of life and physical and mental health. According to recent research, living near green space may reduce one’s risk of developing cancer, cardiovascular and respiratory diseases, as well as other harmful health issues. In this study, the health data was collected in 2007– 2009 in Kaunas, Lithuania. The study participants (144) randomly were divided into two groups, control, and trained groups. Long-term aerobic physical training was applied to the exposure group. General clinical, echocardiography, and spiroergometry parameters were evaluated for the study participants. Greenness was estimated from satellite-derived normalized difference vegetation index (NDVI) in zones with radii of 1 km, 1.5 km, and 2 km surrounding the participants’ residences. To assess the effect of greenness on the effects of rehabilitation, changes in health indicators during a period of 6 months in the groups of low/high greenness environment were presented separately for participants in control and training group. For this purpose, the paired t-test was used. For changes in patient characteristics, the effect of greenness within a radius of 1.5 km was stronger, also the effect within a radius of 1 km was similar. It was discovered that in the trained group, people who lived in high greenness experienced the best increases in the distance walked over the course of six minutes (6 MWT) and a decrease in the mean heart rate. Spiroergometry indication improvements were notable and more pronounced for residents of high greenness areas. After 6 months, a decrease in echocardiographic indicators was found when living in low greenness. Living in low greenness was found to raise diastolic blood pressure and reduce 6 MWT in the control group. Only the control group’s ejection fraction was non-significant alterations in the low greenness environment. It can be concluded that greater greenness, according to NDVI, may lead to better rehabilitation outcomes for heart failure patients undergoing an aerobic exercise training program.

Regulation of NDVI and ET negative responses to increased atmospheric vapor pressure deficit by water availability in global drylands

Atmospheric vapor pressure deficit (VPD, indicative of atmospheric water conditions) has been identified as a major driver of global vegetation dynamics. Drylands, including deserts, temperate grasslands, savannas, and dry forests, are more sensitive to water conditions and affect carbon, nitrogen, and water cycles. However, our knowledge is limited on the way increasing VPD affects vegetation growth and evapotranspiration (ET) in global drylands. In this study, we used long-term satellite datasets combined with multiple statistical analyses to examine the relationship between the satellite-derived normalized difference vegetation index (NDVI), a proxy for vegetation growth, and ET to VPD across global drylands. We found that significant decreases in NDVI and ET predominantly influenced the NDVI (RVPD − NDVI) and ET (RVPD − ET) responses to VPD in both the savannas and dry forests of South American, African, and Australian savannas and dry forests, as well as in temperate grasslands (e.g., Eurasian steppes and American prairies). Notably, more than 60% of global drylands exhibited significantly negative RVPD − NDVI and RVPD − ET values. In contrast, the percentage of significantly negative RVPD − NDVI and RVPD − ET decreased to &amp;lt;10% in cold drylands (&amp;gt;60° N). In predominantly warm drylands (60° N~60° S), negative VPD effects were significantly and positively regulated by soil water availability, as determined by multiple linear regression models. However, these significant regulatory effects were not observed in cold drylands. Moving-window analyses further revealed that temporal changes in RVPD − NDVI and RVPD − ET were positively correlated with changes in the Standardized Precipitation Evapotranspiration Index (SPEI). In warm drylands, areas with increasing RVPD − NDVI and RVPD − ET over time showed an increasing trend in the SPEI, whereas areas with a decreasing SPEI showed a negative trend in RVPD − NDVI and RVPD − ET values over time. Given the increasing atmospheric dryness due to climate change, this study highlighted the importance of re-evaluating the representation of the role of water availability in driving the response of the carbon-water cycle to increased VPD across global drylands.

Estimating the effect of water shortage on olive trees by the combination of meteorological and Sentinel-2 data

ABSTRACT Relative soil water content (RSWC) is widely used to characterize the impact of water stress (WS) on vegetation. In bi-layer ecosystems, such as olive groves, this impact must be primarily estimated for the tree component, which, having greater rooting depth, responds more slowly to WS than understory grass. This complicates the application of methods for RSWC prediction, which must be properly adapted to consider the deeper soil layer influential on olive trees. The current study investigates the modification of a recently proposed RSWC simulation method based on a combination of meteorological and satellite-derived normalized difference vegetation index (NDVI) data. The application of the method to an olive grove in Central Italy requires the estimation of both weather and NDVI contributions affecting solely olive trees, which is carried out through the use of appropriate data processing techniques. The RSWC estimates obtained reasonably reproduce the ground RSWC observations referred to the 1 m soil layer, which are representative of the WS affecting olive trees (r2 = 0.795, RMSE = 0.15 and MBE = −0.09). The limits and prospects of this method are finally discussed with particular reference to the possible integration of the RSWC estimates within more complex ecosystem models.

Environmental greenspace, subjective well-being, and all-cause mortality in elderly Chinese: Association and mediation study in a prospective cohort

BackgroundSubjective well-being (SWB) measures mental health and happiness. Greenspace can have a positive impact on mental health, and higher SWB is associated with lower all-cause mortality. We conducted a mediation analysis on greenspace and all-cause mortality through improving SWB, in a prospective cohort of Chinese older adults. MethodsWe included older adults over 65 from the 2008–2014 Chinese Longitudinal Healthy Longevity Survey (CLHLS). We used satellite-derived normalized difference vegetation index (NDVI) to measure greenspaces and calculated SWB measured by eight items. Three main statistical approaches were used. First, we used generalized estimating equations (GEE) and Cox proportional hazard models to examine NDVI-SWB and SWB-mortality relationships. Second, we conducted a causal mediation analysis to investigate the mediating effect of greenspace on all-cause mortality through SWB. Third, we conducted subgroup analyses to discover effect modification. FindingsAmong 13,133 participants, the mean SWB score and NDVI in 2008 were 28·9 (SD 4·34) and 0·41 (SD 0·14), respectively. We found SWB partially mediated the relationship between residential greenspace and mortality in the adjusted model (average causal mediation effect = 0·11, p = 0·04; average direct effect = 1·96, p < 0·001; total effect = 2·07, p < 0·001) with varying proportions in subgroups. The protective influence was more evident for people with impaired cognitive function, living in rural areas and towns, and with lower income. InterpretationWe found a positive association between greenspace, SWB, and mortality. Greenness in the living environment confers better mental health and promotes longevity in the elderly population.

Uncertainties in the adaptation of alpine pastures to climate change based on remote sensing products and modelling

Over the last century, the management of pastoral systems has undergone major changes to meet the livelihood needs of alpine communities. Faced with the changes induced by recent global warming, the ecological status of many pastoral systems has seriously deteriorated in the western alpine region. We assessed changes in pasture dynamics by integrating information from remote-sensing products and two process-based models, i.e. the grassland-specific, biogeochemical growth model PaSim and the generic crop-growth model DayCent. Meteorological observations and satellite-derived Normalised Difference Vegetation Index (NDVI) trajectories of three pasture macro-types (high, medium and low productivity classes) in two study areas - Parc National des Écrins (PNE) in France and Parco Nazionale Gran Paradiso (PNGP) in Italy - were used as a basis for the model calibration work. The performance of the models was satisfactory in reproducing pasture production dynamics (R2 = 0.52 to 0.83). Projected changes in alpine pastures due to climate-change impacts and adaptation strategies indicate that: i) the length of the growing season is expected to increase between 15 and 40 days, resulting in changes in the timing and amount of biomass production, ii) summer water stress could limit pasture productivity; iii) earlier onset of grazing could enhance pasture productivity; iv) higher livestock densities could increase the rate of biomass regrowth, but major uncertainties in modelling processes need to be considered; and v) the carbon sequestration potential of pastures could decrease under limited water availability and warming.

Assessment of Urban Heat Islands (UHIs) Using SatelliteDerived Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) in Three Metropolitan Cities of Nepal

Urban Heat Islands (UHIs) are urban areas that are relatively warmer than nearby rural areas due to the presence of infrastructures, such as buildings, roads, and associated development. This study explored the UHIs in Nepal's three largest metropolitan cities, i.e., Pokhara, Bharatpur, and Nepalgunj. Using freely available data, we explored LST dynamics between 2000 and 2019 and how changes in NDVI affect LST and their relationship with UHI. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day product (MOD11A2) to evaluate LST and the MODIS-derived NDVI 16-day product (MOD13Q1) to quantify land surface characteristics. Using a simple linear regression technique, we explored the relationship between LST and NDVI. The results indicated that LSTs for the urban areas are consistently greater than LSTs for the nearby rural areas, and an inverse relation between LST and NDVI was obtained. The results from Pokhara and Bharatpur showed that increasing LST resulting from declining NDVI is responsible for UHIs. However, the results from Nepalgunj suggested that factors other than NDVI are responsible for variation in LST. These results indicate a need for systematic mapping, planning, and managing open and green areas in large cities. This research also highlights the scope of applying UHI conceptual models to rapidly developing urban areas in different locations of Nepal for better planning and management of open spaces.

Warming diminishes the stability of primary productivity in global grass- and forb-dominated ecosystems

Global warming has induced increases in productivity in open, grass- and forb-dominated (OGFD) ecosystems. However, little attention has been given to the temporal stability of productivity responses to global warming. We show that the stability of productivity in OGFD ecosystems decreased significantly over the past 40 years. Using the satellite-derived normalized difference vegetation index (NDVI) data from the Global Inventory Modelling and Mapping Studies (GIMMS) group, we analyzed global patterns of the stability in productivity among OGFD ecosystems. We found that the global mean stability of NDVI-based productivity estimates significantly decreased from 1982 to 2015. Comparing different trends, we found that stability decreased by 36%, and increased by 27% of the total area of OGFD ecosystems. The stability of productivity in OGFD ecosystems decreased in the northern hemisphere, especially in the Mongolian plateau and Eurasian steppe. In contrast, stability increased significantly in the southern hemisphere. Increases in both mean annual temperature and annual temperature variability were correlated with decreases in the stability of productivity in the northern hemisphere. Although the productivity of OGFD ecosystems has generally increased with warming, the stability of production has decreased. OGFD ecosystems, particularly northern hemisphere systems with low baseline productivity may be vulnerable to the loss of grazing potential and grazing consistency in the warmer future. These observations highlight the need for adaptation strategies for animal husbandry to respond to variability in productivity and reduce the negative impact of climate change on grazed ecosystems.

Combining remote sensing-derived management zones and an auto-calibrated crop simulation model to determine optimal nitrogen fertilizer rates

CONTEXTCotton is an economically important crop in Australia that requires high resource application, particularly that of nitrogen (N) fertilizers. Determining optimal N fertilizer rates that reach both economic and environmental objectives is a key challenge in cotton systems because of the inherent within-field variability and relatively low N fertilizer use efficiency (NFUE). OBJECTIVEThis study aimed to model optimal N fertilizer rates by accounting for within-field variability through management zone (MZ) delineation across a cotton field in Queensland, Australia. METHODSMZs were delineated using satellite-derived normalized difference vegetation index (NDVI) and the crop simulation model, Decision Support System for Agrotechnology Transfer (DSSAT), was automatically calibrated with a grid-search optimization algorithm and validated across two cotton seasons. A total of 336 different N fertilizer scenarios were subsequently evaluated at pre-planting and top-dressing to observe the effect on profit margin and NFUE. RESULTS AND CONCLUSIONSThe MZ delineation analysis determined that within-field variability could be best represented by two MZs, one of which displaying subsoil constraints due to high carbonate concentrations. The use of the auto-calibration algorithm led to a successful validation of the model with a Wilmott d-index of agreement ranging between 0.75 (soil nitrate) and 0.96 (aboveground biomass and plant N), respectively. The subsequent N scenario simulations indicated that by reducing N fertilizer rates by 80 and 30 kg N ha−1 across the two MZs, respectively, compared to the current industry average, profits could be maximized through maintaining yields while reducing N inputs. SIGNIFICANCEOverall, these results demonstrate the potential of combining remote sensing-derived MZs and crop model auto-calibration techniques to support the cotton industry in achieving improved resource efficiency and profit margins.

Association of residential greenness with incident chronic obstructive pulmonary disease: A prospective cohort study in the UK Biobank

BackgroundResidential greenness has been linked to respiratory mortality, but its long-term effect on incident chronic obstructive pulmonary disease (COPD) has rarely been investigated. MethodsThis prospective cohort study was based on over 350 000 participants aged 38–70 of the UK Biobank, followed from 2006 to 2010 baseline to 2021. COPD cases were ascertained through linkages to health administrative datasets. Residential greenness was measured by satellite-derived normalized difference vegetation index (NDVI) within the 500- and 1 000-m buffer. Effects of greenness on COPD incidence were assessed using Cox proportional hazards models. We also explored mediation by physical activity, particular matter <2.5 μm in aerodynamic diameter (PM2.5) and nitrogen oxides (NOx). Restricted cubic spline models were fit to assess exposure–response relationships. ResultsA total of 363 212 individuals (mean [SD] age, 56.2 [8.1] years; 193 181 [53.2 %] women] were included in the analyses. 8 261 COPD cases occurred over 4 287 926 person-years of follow-up. We observed 8% lower COPD risk per IQR increase in NDVI in the 500-m buffer (95% CI: 0.89, 0.95). The association between greenness in the 500-m buffer and COPD were partially mediated by physical activity (1.0%, 95% CI: 0.2%, 1.8%), PM2.5 (21.0%, 95% CI: 3.7%, 38.4%) and NOx (17.0%, 95% CI: 2.8%, 31.2%). Similar results were observed for NDVI within 1 000-m buffer. ConclusionsLong-term exposure to residential greenness was associated with lower risk of COPD incidence among UK adults. Our findings provide a rationale for greening policies as part of respiratory health promotion efforts.

Residential greenspace and childhood asthma: An intra-city study

Interest in assessing the effects of exposure to greenspace on human health has been increasing due to rapid urbanization, and rising trends of physical inactivity and air pollution. However, findings on the link between greenspace and child respiratory health, especially asthma, are inconsistent. We investigated the association between greenspace surrounding residential addresses and asthma in children. A city-wide cross-sectional study was conducted, involving 16,605 children aged 3–12 years, in Shanghai, China. Data on asthma symptoms and covariates were collected from validated self-reported questionnaires. Residential greenspace was measured using satellite-derived normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Information on ambient temperature and particulate matter with dynamic diameter <1 μm (PM1) and 2.5 μm (PM2.5) was also collected from satellite data. Logistic regression models were performed to assess the associations of greenspace exposure with childhood asthma as well as the effect modification by covariates. The prevalence of current asthma in children was 4.8 % in this study. An interquartile range increase in mean NDVI from 2016 to 2018 was associated with decreased odds of asthma in 2019 at 500 m, and 250 m resolutions (0.82, 95 % confidence interval (CI): 0.74 to 0.93; and 0.82, 95 % CI: 0.72 to 0.94, respectively) after adjustment for covariates. The greenspace-asthma association was modified by ambient temperature and residential area. Sensitivity analyses using various models and EVI exposure showed the robustness of the results. In conclusion, higher individual-level exposure to greenspace was associated with decreased odds of asthma in children, and the association appeared to be modified by different environmental and socio-demographic factors. These findings provide additional evidence for promoting urban greenness to protect children's health and well-being.

Assessing the effects of ultraviolet radiation, residential greenness and air pollution on vitamin D levels: A longitudinal cohort study in China

Vitamin D metabolism is essential in aging and can be affected by multiple environmental factors. However, most studies conducted single exposure analyses. We aim to assess the individual and combined effects of ultraviolet (UV) radiation, residential greenness, fine particulate matter (PM2.5), and ozone (O3) on vitamin D levels in a national cohort study of older adults in China. We used the 2012 and 2014 Chinese Longitudinal Healthy Longevity Survey data, and measured the environmental exposure in the same year. We interpolated the UV radiation from monitoring stations, measured residential greenness through satellite-derived Normalized Difference Vegetation Index (NDVI), modeled PM2.5 with satellite data, and estimated O3 using machine learning. We dichotomized serum 25-hydroxy vitamin D (25(OH)D), the primary circulating form of vitamin D, into non-deficiency (≥50 nmol/L) and deficiency (<50 nmol/L) categories. We used the generalized estimating equation for analysis, adjusted for sociodemographic information, lifestyle, physical condition, and season of blood draw, and calculated joint odds ratios based on the Cumulative Risk Index. We also explored the interaction between interested exposures, modification of participants’ characteristics, and potential mediation. We included 1,336 participants, with a mean age of 83 at baseline. In single exposure models, the odds ratios of vitamin D deficiency (VDD) for per interquartile range increase in UV radiation, NDVI, PM2.5, and O3 and decrease were 0.39 (95 % CI:0.33,0.46), 0.90 (0.81,1.00), 1.65 (1.53,1.78), 1.67 (1.46,1.92), respectively. UV radiation mediated nearly 48 % and 78 % of the relationship between VDD and PM2.5 and O3, respectively. The association between UV radiation and VDD was stronger in females than men (OR: 2.25 vs 1.22). UV radiation, residential greenness can protect against VDD, while, PM2.5 and O3 increase the risk of VDD. UV radiation partly mediated the association between air pollution and VDD.