Urban Greenness Research Articles

Assessing the influence of urban greenness and green stormwater infrastructure on hydrology from satellite remote sensing

Green stormwater infrastructure (GSI), which includes features like rain gardens, constructed wetlands, or urban tree canopy, is now widely recognized as a means to reduce urban runoff impacts and meet municipal water quality permit requirements. Many co-benefits of GSI are related to increased vegetative cover, which can be measured with satellite imagery via spectral indices such as the Normalized Difference Vegetation Index (NDVI). In urban landscapes, there remain critical gaps in understanding how urban greenness and GSI influence hydrology. Here, we quantify these relationships to assess the feasibility of tracking the effectiveness of urban greening for improving downstream hydrologic conditions. We combined hydrologic data from the United States Geological Survey (USGS) gauges with an NDVI time series (1985–2019) derived from Landsat satellite imagery, and synthesis of GSI implementation data from a set of 372 urbanized watersheds across the United States. We used a multivariate panel modeling approach to account for spatial and time varying factors (rainfall, temperature, urban cover expansion) in an effort to isolate the relationships of interest. After accounting for expansion of urban boundaries, only 32 watersheds (9%) showed significant greenness trends, a majority of which were reductions. Urban greenness had significant influences on downstream flow responses, so that on average, a 10% greenness increase showed a corresponding reduction of total flow (−3.8%), flow variance (−7.7%), peak flows (−4.7%), high flows (−7.6%), flashiness (−2.2%), and high flow frequency (−1.5%); and a corresponding increase in baseflow (4.3%). For a subset of these watersheds for which GSI data were available (n = 48), the level of GSI implementation showed a significant, but weak influence on urban greenness with a 20% increase in BMP density corresponding to a greenness increase of 0.9%. The study results may support valuation and verification of GSI co-benefits in urbanized landscapes at the watershed scale.

Increased urban greenness associated with improved mental health among middle-aged and older adults of the Canadian Longitudinal Study on Aging (CLSA)

ObjectivesSome studies suggest that residential surrounding greenness is associated with improved mental health. Few of these studies have focussed on middle-aged and older adults, explored the modifying effects of social determinants of health, or accounted for the extent to which individuals interact with their neighbourhood environments. MethodsWe analysed cross-sectional data collected from 26,811 urban participants of the Canadian Longitudinal Study of Aging who were between 45 and 86 years of age. Participants provided details on socioeconomic characteristics, health behaviours, and their frequency of neighbourhood interactions. The Normalized Difference Vegetation Index (NDVI), a measure of greenness, was assigned to participants’ residential addresses at a buffer distance of 500 m. Four self-reported measures of mental health were considered: The Center for Epidemiologic Studies Depression Scale (CES-D-10; short scale), past diagnosis of clinical depression, perceptions of mental health, and the Satisfaction with Life Scale (SWLS). Regression models were used to describe associations between greenness and these outcomes, and spline models were fit to characterize the exposure-response function between greenness and CES-D-10 scores. Stratified analyses evaluated whether associations varied by sociodemographic status. ResultsIn adjusted models, we observed a 5% (Odds Ratio (OR) = 0.95; 95% CI = 0.90, 0.99) reduced odds of depressive symptoms in relation to an interquartile range increase of NDVI (0.06) within a 500 m buffer of the participant's residence. Similarly, we found an inverse association with a self-reported clinical diagnosis of depression (OR = 0.97; 95% CI = 0.92–1.01). Increases in surrounding greenness were associated with improved perceptions of mental health, and the SWLS. Our spline analyses found that beneficial effects between greenness and the CES-D-10 were strongest among those of lower income. ConclusionsThese findings suggest that residential greenness has mental health benefits, and that interventions to increase urban greenness can help reduce social inequalities in mental health.

Understanding the Pathways to the Healthy Aging Framework: Empirical Evidence and Future Directions

Despite a large body of literature documenting the association between individual characteristics and financial literacy, our understanding of the impact of macro-environmental conditions on individual financial literacy remains limited, particularly in later life. Drawing from a micro-macro perspective on the social environment and individual processes, we examined the extent to which three state-level contextual characteristics were associated with individual later-life financial literacy in the United States: tertiary educational attainment, poverty prevalence, and Internet penetration. We utilized data from the 2019 Understanding America Study (UAS) for adults aged 50 years or older to assess financial literacy (n=2,930), and data from the American Community Survey to evaluate contextual conditions. The UAS is a nationally representative survey panel supported by the Social Security Administration and the National Institute on Aging. Cross-sectional multilevel regression models were used to examine the hypothesized effects. We found that state-level poverty prevalence was negatively associated with individual financial literacy while state-level Internet penetration was positively associated with individual financial literacy, over and above individual characteristics known to impact financial literacy. No association was found between state-level educational attainment and individual financial literacy after controlling for respondents’ own education. Findings suggest that the social environment may condition financial literacy in later life through exposure to opportunities that promote knowledge acquisition. Interventions to enhance later-life financial literacy may benefit from targeted approaches that take into account the environmental characteristics of their locations of residence.

ОЦЕНКА УРОВНЯ ОЗЕЛЕНЕНИЯ ГОРОДА БИРОБИДЖАНА С ПРИМЕНЕНИЕМ МУЛЬТИСПЕКТРАЛЬНЫХ ДАННЫХ

The urban greenness distribution between functional areas of a medium-size city Birobidzhan was assessed. To this end, normalized difference vegetation index (NDVI) values were calculated based on Sentinel 2 multispectral imaging. Birobidzhan is characterized by a large scatter of NDVI values (from –0.5 to +1). Areas with high levels of greenery are prevalent. They are found in different types of functional zones, but are specific mainly to natural recreational, agricultural, and individual build-up zones as well as to special areas. The spatial distribution of green infrastructure is highly contrast. The downtown part as well as the industrial and storage zones feature a combination of built-up areas with dense woody vegetation, which is often represented by fragments of preserved natural vegetation. In addition, a feature of the contrast is that low level of tree greenness is characteristic for the built-up districts of the city. Thus, in the city of Birobidzhan, ecological functions are largely performed by the natural vegetation present in the natural recreational zones on 70% of the city's area.

Impact of residential greenness on myocardial infarction in the population with diabetes: A sex-dependent association?

Living in urban areas with abundant greenness might provide health benefits in general population. Literature suggests that sex/gender plays a role in the association between greenness and health outcomes. But the impact of greenness in populations with moderate to high cardiovascular risk, such as persons with diabetes, is still unknown. Our aim was to evaluate the relationship between urban greenness and myocardial infarction incidence in persons with type 2 diabetes in Barcelona (Catalonia, Spain), and seek potential gender/sex differences in this association.This retrospective cohort study is based on data from the System for the Development of Research in Primary Care (SIDIAP database). We used Cox models to estimate if a 0.01 increase in Normalized Difference Vegetation Index (NDVI) at census tract level was associated to reduced risk of developing a myocardial infarction. Models were adjusted by demographic and clinical characteristics at individual level, and by environmental and socioeconomic variables at census tract level. Amongst 41,463 persons with diabetes and 154,803.85 person-years of follow-up, we observed 449 incident cases of acute myocardial infarction. For each 0.01 increment in NDVI the risk of developing a myocardial infarction decreased by 6% (Hazard Ratio, HR = 0.94; 95%CI, 0.89–0.99) in the population with diabetes. When stratifying by sex, we observed a significant association only in men (HR = 0.91; 95%CI, 0.86–0.97).People with diabetes living in urban greener areas might benefit from reduced cardiovascular risk, specially men. We observed sex/gender disparities, which could be related to different exposures and activities performed in green spaces between men and women. Further studies are needed to confirm sex/gender disparities between greenness exposure and cardiovascular outcomes. Our findings contribute to improve the health of people with diabetes who should be recommended to spent time and exercise in green areas.

Urban greenness and survival in lung cancer patients: A registry-based cohort study in Beijing

BackgroundPrevious studies have reported inverse associations between urban greenness and mortality. However, findings regarding contemporaneous and cumulative average greenness exposure are inconsistent. A potential explanation is the weak effects of greenness among the general population. This study assessed the associations between contemporaneous and cumulative average greenness exposure and survival in lung cancer patients. MethodsAn open cohort consisting of lung cancer patients enrolled from 1 January 2001 was studied. The cohort was followed up until 31 December 2018. We evaluated contemporaneous and cumulative greenness exposure using the normalized difference vegetation index (NDVI) within a 250 m buffer of each patient’s geocoded residential address. The association between NDVI and mortality was evaluated using both time-fixed and time-varying Cox models. Their difference was compared either. ResultsIn time-fixed Cox models, a 0.1-unit increment in contemporaneous and cumulative average NDVI was associated with 17% (95% confidence interval [CI], 15–18%) and 7% (95% CI, 5–8%) reductions in mortality rate, respectively. Time-varying Cox models consistently revealed significant associations, but their magnitudes were lower, at 2% (95% CI, 1–3%) for both contemporaneous and cumulative average NDVI. Compared to the time-fixed models, the time-varying ones exhibited better fit for the proportional hazard assumption in Cox regressions with more conservative results. ConclusionUrban greenness is positively associated with an increased chance of survival in lung cancer patients. Compared to time-fixed Cox models, the results of time-varying Cox models were more conservative. This study confirms the beneficial health effects of urban greenness, which may facilitate the improvement of public health by urban green space planning.

Contrasting urban greenness across cities with varying trends in above-normal weather events

Effective urban management demands global empirical research findings. The work aims to determine whether green areas are more significant in cities where above-normal wet events have plateaued. This work compares the green surface cover characteristics of the entire city and identified zones of 54 cities representing cities worldwide. These cities experience varying amounts of above-normal weather conditions. This article classifies the cities in the data set into two groups: Group 1 – frequency of extreme wet weather events has plateaued, and Group 2 – frequency of extreme weather events are increasing or decreasing at higher rates. Next, the work uses structural features of co-located spatial networks, roads and terrain, to identify zones. Finally, high-resolution satellite imagery quantified urban green spaces in the city and identified zones of the two city groups using geospatial and machine learning methods for 2000 and 2020. The data is compared for two groups to understand the pattern of green spaces in cities. Empirical analysis results recognise a higher greenness index in the zones and the entire city amongst the cities of Group1. The pattern in the temporal change in the greenness index of the zones is helpful to formulate a priority plan for locating inter-linked green spaces in urban areas paving the way for Nature-based Solutions. The findings can guide planners and policy-makers to identify and prioritise locations to incorporate a robust green infrastructure network to build resilient cities by 'nature bringing a solution’, the essential concept of Nature-based Solutions.

Assessing Urban Greenness Fragmentation and Analysis of Its Associated Factors: A Case Study in Wuhan Metropolitan Area, China

Green vegetation plays a vital role in urban ecosystem services. Rapid urbanization often tends to induce urban vegetation cover fragmentation (UVCF) in cities and suburbs. Mapping the changes in the structure (aggregation) and abundance of urban vegetation cover helps to make improved policies for sustainable urban development. In this paper, a new distance-based landscape indicator to UVCF, Frag, was proposed first. Unlike many other landscape indicators, Frag measures UVCF by considering simultaneously both the structure and abundance of vegetation cover at local scales, and thus provides a more comprehensive perspective in understanding the spatial distribution patterns in urban greenness cover. As a case study, the urban greenness fragmentation indicated by Frag was demonstrated in Wuhan metropolitan area (WMA), China in 2015 and 2020. Support vector machine (SVM) was then designed to examine the impact on the Frag changes from the associated factors, including urbanization and terrain characteristics (elevation and slope). The Frag changes were mapped at different scales and modeled by SVM from the selected factors, which reasonably explained the Frag changes. Sensitivity analysis for the SVM model revealed that urbanization showed the most dominant factor for the Frag changes, followed by terrain elevation and slope. We conclude that Frag is an effective scale-dependent indicator to UVCF that can reflect changes in the structure and abundance of urban vegetation cover, and that modeling the impact of the associated factors on UVCF via the Frag indicator can provide essential information for urban planners.

The equigenic effect of greenness on the association between education with life expectancy and mortality in 28 large Latin American cities.

BackgroundRecent studies highlight the equigenic potential of greenspaces by showing narrower socioeconomic health inequalities in greener areas. However, results to date have been inconsistent and derived from high-income countries. We examined whether urban greenness modifies the associations between area-level education, as a proxy for socioeconomic status, and life expectancy and cause-specific mortality in Latin American cities.MethodsWe included 28 large cities, >137 million inhabitants, in nine Latin American countries, comprising 671 sub-city units, for 2012–2016. Socioeconomic status was assessed through a composite index of sub-city level education, and greenness was calculated using the normalized difference vegetation index. We fitted multilevel models with sub-city units nested in cities, with life expectancy or log(mortality) as the outcome.FindingsWe observed a social gradient, with higher levels of education associated with higher life expectancy and lower cause-specific mortality. There was weak evidence supporting the equigenesis hypothesis as greenness differentially modified the association between education and mortality outcomes. We observed an equigenic effect, with doubling magnitudes in the violence-related mortality reduction by education in areas with low greenness compared to medium-high greenness areas among men (16% [95% CI 12%–20%] vs 8% [95% CI 4%–11%] per 1 SD increase in area-level education). However, in contradiction to the equigenesis hypothesis, the magnitude in cardiovascular diseases (CVD) mortality reduction by education was stronger in areas with medium-high greenness compared to areas with low greenness (6% [95% CI 4%–7%] vs 1% [95% CI -1%–3%] and 5% [95% CI 3%–7%] vs 1% [95% CI -1%–3%] per 1 SD increase in area-level education, in women and men, respectively). Similarly, each 1-SD increase in greenness widened the educational inequality in life expectancy by 0.15 years and 0.20 years, in women and men, respectively. The equigenic effect was not observed in violence-related mortality among women and in mortality due to communicable diseases, maternal, neonatal and nutritional conditions (CMNN).InterpretationOur results confirm socioeconomic health inequalities in Latin American cities and show that the equigenic properties of greenspace vary by health outcome. Although mixed, our findings suggest that future greening policies should account for local social and economic conditions to ensure that greenspaces provide health benefits for all, and do not further exacerbate existing health inequalities in the region.FundingWellcome Trust (Grant, 205177/Z/16/Z).

Rapid Mapping and Annual Dynamic Evaluation of Quality of Urban Green Spaces on Google Earth Engine

In order to achieve the United Nations 2030 Sustainable Development Goals (SDGs) related to green spaces, monitoring dynamic urban green spaces (UGSs) in cities around the world is crucial. Continuous dynamic UGS mapping is challenged by large computation, time consumption, and energy consumption requirements. Therefore, a fast and automated workflow is needed to produce a high-precision UGS map. In this study, we proposed an automatic workflow to produce up-to-date UGS maps using Otsu’s algorithm, a Random Forest (RF) classifier, and the migrating training samples method in the Google Earth Engine (GEE) platform. We took the central urban area of Beijing, China, as the study area to validate this method, and we rapidly obtained an annual UGS map of the central urban area of Beijing from 2016 to 2020. The accuracy assessment results showed that the average overall accuracy (OA) and kappa coefficient (KC) were 96.47% and 94.25%, respectively. Additionally, we used six indicators to measure quality and temporal changes in the UGS spatial distribution between 2016 and 2020. In particular, we evaluated the quality of UGS using the urban greenness index (UGI) and Shannon’s diversity index (SHDI) at the pixel level. The experimental results indicate the following: (1) The UGSs in the center of Beijing increased by 48.62 km2 from 2016 to 2020, and the increase was mainly focused in Chaoyang, Fengtai, and Shijingshan Districts. (2) The average proportion of relatively high and above levels (UGI > 0.5) in six districts increased by 2.71% in the study area from 2016 to 2020, and this proportion peaked at 36.04% in 2018. However, our result revealed that the increase was non-linear during this assessment period. (3) Although there was no significant increase or decrease in SHDI values in the study area, the distribution of the SHDI displayed a noticeable fluctuation in the northwest, southwest, and northeast regions of the study area between 2016 and 2020. Furthermore, we discussed and analyzed the influence of population on the spatial distribution of UGSs. We found that three of the five cold spots were located in the east and southeast of Haidian District. Therefore, the proposed workflow could provide rapid mapping and dynamic evaluation of the quality of UGS.

A negative association between prevalence of diabetes and urban residential area greenness detected in nationwide assessment of urban Bangladesh

Residential area greenness may influence diabetes, but limited studies have explored this relationship in developing countries. This study assessed the association between residential area greenness and diabetes among urban adults in Bangladesh. The mediation effect of the body mass index (BMI) was also assessed. A total of 2367 adults aged ≥ 35 years were extracted from a nationally representative survey. Diabetes was characterised as fasting plasma glucose level be ≥ 7.0 mmol/L or taking prescribed medications to reduce blood sugar level. Residential area greenness was estimated by enhanced vegetation index. Binary logistic regression models were employed to estimate the association between residential area greenness and diabetes adjusting for sociodemographic factors. Mediation analysis was performed to assess whether BMI mediated the association between greenness and diabetes. Greater area greenness was associated with lower odds of diabetes (adjusted odds ratio 0.805, 95% confidence interval 0.693–0.935, p = 0.0052). BMI significantly mediated 36.4% of the estimated association between greenness and diabetes. Presence of areas of greenness adjacent to living area tends to be associated with lower diabetes prevalence. Findings emphasised the importance of preserving the local environment to tackle the growing diabetes prevalence in Bangladesh.

The Relationship Between City “Greenness” and Homicide in the US: Evidence Over a 30-Year Period

Residents in US cities are exposed to high levels of stress and violent crime. At the same time, a number of cities have put forward “greening” efforts which may promote nature’s calming effects and reduce stressful stimuli. Previous research has shown that greening may lower aggressive behaviors and violent crime. In this study we examined, for the first time, the longitudinal effects over a 30-year period of average city greenness on homicide rates across 290 major cities in the US, using multilevel linear growth curve modeling. Overall, homicide rates in US cities decreased over this time-period (52.1–33.5 per 100,000 population) while the average greenness increased slightly (0.41–0.43 NDVI). Change in average city greenness was negatively associated with homicide, controlling for a range of variables (β = −.30, p-value = .02). The results of this study suggest that efforts to increase urban greenness may have small but significant violence-reduction benefits.

Urban greenness and hypertension among Ghanaian adults

ABSTRACT There is a lack of studies in sub-Saharan African countries, specifically Ghana, demonstrating the relationship between greenness and hypertension. We use Greenness (Enhanced Vegetation Index, EVI) data to examine its association on hypertension among Ghanaian adults in urban areas. Participants with higher exposure to greenness was significantly associated with lower odds of hypertension OR: 0.63 (95% CI:0.41–0.95) than participants with low levels of greenness exposure. Our findings recommend a positive attitudinal change toward the preservation of green spaces as well as the allocation and prioritization of green spaces by policymakers in areas rapidly undergoing urbanization.

Association between Low Urban Neighborhood Greenness and Hypertensive Disorders of Pregnancy.

Urban neighborhood greenness is associated with greater cardiovascular health in the general population, and with better pregnancy and neonatal outcomes. Hypertension in pregnancy is a leading cause of maternal mortality and long-term cardiovascular morbidity and mortality in women. We sought to examine the association between greenness and hypertensive disorders of pregnancy. This study is a secondary analysis of a prospective cohort study of 1,943 women who received prenatal care from December 2013 to December 2016 at a single, urban, and tertiary academic medical center in Philadelphia, PA. Greenness measure was quantified via residential tree canopy cover within circumferential buffers of 100- and 500-meter radii around participants' homes. Associations between greenness and hypertensive disorders of pregnancy (defined as gestational hypertension or preeclampsia) were estimated by using multilevel logistic regression accounting for maternal sociodemographic information (race-ethnicity, insurance status, and age) medical history (diabetes, body mass index, smoking history, and parity), neighborhood deprivation index, and including 1,225 Philadelphia residents for whom key exposure and outcome data were available. At baseline, the participants' mean (SD) age was 27.5 (5.9) years, (range: 14-44 years). The majority of participants were non-Hispanic Black (857, 70.2%). Participants with less residential tree canopy cover were significantly more likely to have hypertensive disorders of pregnancy. The multivariable-adjusted odds ratio of hypertensive disorders of pregnancy among participants with less than 10% compared with those with greater than 30% tree canopy cover was 2.14 (95% confidence interval [CI]: 1.11-4.15) within 100-meter buffer. In our cohort, greenness was associated with lower hypertensive disorders of pregnancy odds. Our findings add to evidence that greenness may confer health benefits and warrant further investigations in identifying whether there is a causal pathway through which greenness may be protective against hypertensive disorders of pregnancy. · Low residential tree canopy is associated with increased risk of hypertensive disorders of pregnancy. · 100-meter buffers are most sensitive in identifying associations between tree canopy and HDP risk. · The role of greenness against hypertensive disorders of pregnancy should be further studied experimentally.

Association between urban greenness and sleep measures in Canadian adults: Findings from the Canadian Longitudinal Study of Aging

BACKGROUND AND AIM: A series of epidemiological studies have found that urban greenness may confer several health benefits, including improved sleep quality. In this study we explore the association between greenness and sleep quality among middle-age adults in a national Canadian cohort. METHODS: We conducted a cross-sectional analysis of 30,089 urban dwelling participants, 45 to 69 years of age, of the Canadian Longitudinal Study of Aging. We investigated the relationship between urban greenness (NDVI) and the three sleep measures – sleep quality satisfaction, sleep duration, and difficulty falling asleep. We included individual data on levels of physical activity, health status, and connection to their local neighbourhood, as well as contextual measures including air pollution, favourability of the neighbourhood for active living, and socioeconomic status. We conducted multinomial logistic regression to derive adjusted odds ratios and their 95% confidence intervals to describe associations between greenness at sleep measures. RESULTS:The analytic cohort included 27,276 participants, the majority of who were married or common-law, well educated, self-identified as white, and were born in Canada, which is in agreement with the demographic profile of the full CLSA cohort. Greenness exposure was higher among participants who were married/common-law, higher income and education, ethnically white, better general and mental health, never smokers, and a stronger connection to their neighbourhood. Multinomial logistic regression models adjusted for a set of a priori covariates according to each sleep outcome, based on socio-demographic characteristics, lifestyle factors, chronic disease, connection to neighbourhood, and stress. Multinomial logit models revealed greenness had a protective effect on sleep quality satisfaction and difficulty falling asleep (OR1); however, results were not statistically significant. CONCLUSIONS:Creating new green areas, as well as protecting and restoring current spaces, could have beneficial impacts on the sleep behaviour of middle-to-older aged adults residing in urban areas. KEYWORDS: Sleep, green space, NDVI, cross-sectional study, Canada, adults

Urban Greenness and Mental health among participants of the Canadian Longitudinal Study of Aging (CLSA)

BACKGROUND AND AIM: In Canada, an estimated 6.7 million people suffer from mental health disorders in any given year. An increasing number of recent studies have suggested links between greenspaces and improved health. Few Canadian studies, however, have examined greenness-mental health relationships. METHODS: We used cross-sectional data from the Canadian Longitudinal Study on Aging (CLSA) to characterize associations between greenness and prevalent mental health outcomes. Our analyses are based on 26,765 adults, 45 to 85 years of age, who lived in urban areas. The Normalized Difference Vegetation Index was used as a residential measure of greenness and we modelled exposures based on a series of buffer intervals (250m, 500m, 1000m). Four self-reported measures of mental health were assessed, and these included: i) the Center for Epidemiologic Studies Depression Scale (CES-D-10; short scale), ii) Perceptions of Mental health on the Likert scale, iii) Perceptions of General health on the Likert scale iv), and the Satisfaction With Life Scale (SWLS). We used multivariable logistic regression models to characterize associations between greenness and mental health. The resulting odds ratios, and their 95% confidence intervals, were adjusted for several important risk factors. RESULTS:Overall, 5.6% of the participants reported fair/poor mental health, 9.3% fair/poor general health, 12.2% were dissatisfied on the SWLS, and 15.9% reported moderate/serious depression. Greenness at 500m around the residential postal code was inversely associated with all four measures of mental health. Specifically, interquartile range increases in greenness significantly reduced the odds of moderate/serious depression by 12% [OR=0.88, (95% CI=0.83-0.93)], the odds of dissatisfaction by 13% [OR=0.87, (95% CI=0.81-0.92)], the odds of fair/poor mental health by 19% [OR=0.81, (95% CI=0.74-0.88)], and the odds of fair/poor general health by 10% [OR = 0.90, (95% CI =0.83-0.98)]. CONCLUSIONS:Our findings suggest that urban greenness confers mental health benefits, and provide some support for local initiatives to green neighbourhoods as a means to improve population health. KEYWORDS: Mental health, Depression, Adults, Greenness, CLSA

Quantifying Urban Vegetation Dynamics from a Process Perspective Using Temporally Dense Landsat Imagery

Urban vegetation can be highly dynamic due to the complexity of different anthropogenic drivers. Quantifying such dynamics is crucially important as it is a prerequisite to understanding its social and ecological consequences. Previous studies have mostly focused on the urban vegetation dynamics through monotonic trends analysis in certain intervals, but not considered the process which provides important insights for urban vegetation management. Here, we developed an approach that integrates trends with dynamic analysis to measure the vegetation dynamics from the process perspective based on the time-series Landsat imagery and applied it in Shenzhen, a coastal megacity in southern China, as an example. Our results indicated that Shenzhen was turning green from 2000–2020, even though a large-scale urban expansion occurred during this period. Approximately half of the city (49.5%) showed consistent trends in greening, most of which were located in the areas within the ecological protection baseline. We also found that 35.3% of the Shenzhen city experienced at least a one-time change in urban greenness that was mostly caused by changes in land cover types (e.g., vegetation to developed land). Interestingly, 61.5% of these lands showed trends in greening in the recent change period and most of them were distributed in build-up areas. Our approach that integrates trends analysis and dynamic process reveals information that cannot be discovered by monotonic trends analysis alone, and such information can provide insights for urban vegetation planning and management.

Changes of Urban Greenness Based on Sentinel Data and Landsat Data

With the rapid growth of the global economy, environmental resources have also been severely consumed and destroyed. With the rapid growth of China’s economy, domestic environmental pollution and environmental damage have become increasingly serious. In order to understand the changes in the urban greenness of Chinese cities, the changes in the urban greenness of coastal cities in China in the past five years have been explored by using Landsat satellite remote sensing image data from multiple periods since 1973. The reason for choosing coastal cities as the research objects is that the coastal cities have relatively developed economy and have certain demonstrative significance for both themselves and the development of inland cities. This article first popularizes the domestic urban environmental conditions and knowledge of remote sensing technology, and then analyzes the process of obtaining urban greenness sentinel data and Landsat data of coastal cities from remote sensing data, and finally analyzes the urban greenness of coastal cities in the past 5 years. The increase change and the average increase change are analyzed and compared, and corresponding conclusions are given based on the analysis results.

Can’t see the wood for the trees? An assessment of street view- and satellite-derived greenness measures in relation to mental health

Greenness in the urban living environment is inconsistently associated with mental health. Satellite-derived measures of greenness may inadequately characterize how people encounter greenness visually on site, but systematic comparisons are lacking. We aimed 1) to compare associations between remotely sensed and street view (SV) greenness, and 2) to examine whether these greenness metrics are differently associated with mental health outcomes. We used cross-sectional depressive and anxiety symptoms data on adults in Amsterdam, the Netherlands. We employed a convolutional neural network to segment greenness in SV panoramas. Greenness was measured top-down by normalized difference vegetation indices (NDVI) from 1 m resolution orthophotos (OP) and 30 m resolution Landsat-8 (LS) imagery per postal code, and 100 and 300 m concentric and street-network buffers at the home address. Correlation analyses assessed associations across greenness measures. Covariate-adjusted regressions (e.g., noise, air pollution, deprivation) were conducted to assess associations between each greenness metric and mental health outcomes. Correlations between greenness metrics were significantly positive and moderately high. SV greenness was less sensitive across scales and residential contexts than OP and LS greenness. There was no statistically significant evidence that people with less urban residential greenness had higher depression or anxiety scores than those exposed to higher levels. Nor did different greenness measures, scales, or residential context definitions alter our null associations. This suggests that even though SV and remotely sensed measures capture different aspects of greenness, these differences across exposure metrics did not translate into an association with mental health outcomes.

Urban Green Spaces, Greenness Exposure and Species Richness in Residential Environments and Relations with Physical Activity and BMI in Portuguese Adolescents.

Environmental factors play an important role in obesity-related behaviors. Evidence indicates significant associations between weight and urban green spaces in adults, but it is not clear whether this relationship applies to adolescents. Therefore, our aim was to determine the associations between urban green spaces, greenness exposure and species richness in residential environments with physical activity and body mass index. Sixty-two adolescents between 12 and 18 years of age answered a self-administered questionnaire, providing information on height, weight, age, sex and home address. Data on socioeconomic deprivation were obtained from the European Index of Deprivation for Small Portuguese Areas. Physical activity levels were assessed using accelerometers. Urban green space counts and the normalized difference vegetation index values were measured using buffers along the roads with distances of 300, 500, 1000 and 1500 m from each participant’s residence. To quantify the species richness, the species richness index was used. Linear regression models were fitted to analyze whether urban green spaces, exposure to green spaces and species richness counts for each distance were associated with physical activity and self-reported body mass index. We did not find significant associations between the independent variables and the probability of overweight or obesity. The relationship between environmental variables, adolescents’ physical activity and body weight seems to be complex and further studies may contribute to better understanding of the topic.