Application of NDVI in Environmental Justice, Health and Inequality Studies – Potential and Limitations in Urban Environments

Jürgens, Carsten; Meyer-Heß, M. Fabian

doi:10.20944/preprints202008.0499.v1

Cited by 5 publications

(9 citation statements)

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“…Due to absorption processes, especially in the red part of the electromagnetic spectrum, it was associated with the leaf chlorophyll content. In near-infrared part of the electromagnetic spectrum, there is a very strong reflection that corresponds to multiple reflections in the leaf inner cell structure due to the cells' water content [32].…”

Section: Methodsmentioning

confidence: 99%

“…If the value of the NDVI is greater than others, this indicates that vegetation coverage is better [33]. The more the NDVI value tends to þ1, the more it is related to vegetation cover and its vigor [32]. The value ranging between -1 to þ1 of the NDVI has a different presentation on its land use.…”

Section: Methodsmentioning

confidence: 99%

“…In urban contexts, vegetation surfaces are very important for the well-being and health of the urban population. The NDVI is often correlated with socioeconomic and/or sociodemographic data to demonstrate the inequality in environmental settings that themselves influence individual health and questions of environmental justice [32].…”

Section: High Dense Classmentioning

confidence: 99%

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Mapping and assessment of vegetation cover change and species variation in Medan, North Sumatra

Zaitunah

Samsuri

Sahara

2021

Heliyon

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Vegetation existence contributes to environmental quality in urban areas. The increase in population and development of cities has led to land conversion with lesser vegetated areas. Information on land cover change is needed, especially for urban regional planning with green open space consideration. The research aims to analyze urban vegetation cover and its changes in two sub-districts of Medan between the years 1999 and 2019. Normalized difference vegetation index (NDVI) and change analysis were conducted in the research. The diversity of plants within these areas was observed. The results showed changes in vegetation cover areas in the mentioned years. In 1999, most areas were under a highly dense vegetation class, while in 2019, they were under a lowdensity vegetation class. This finding indicates a decrease in vegetation cover as a result of increasing built-up areas. Within the vegetation cover, it was found many tree species and agricultural plants. Those vegetations existed in some areas: city parks, house yards, gardens, agricultural fields, etc. A special emphasis should be placed on riverside areas with less vegetation in order to provide a higher level of protection, particularly in the event of a flood. To increase the vegetated areas and maintain the environmental quality, optimizing the land by replanting in the area with no or less vegetation should be done.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Mapping and assessment of vegetation cover change and species variation in Medan, North Sumatra

Zaitunah

Samsuri

Sahara

2021

Heliyon

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Section: Data Processingmentioning

confidence: 99%

“…Images with more than 80% clouds were excluded from further analyses. Following the cloud mask, we calculated spectral indices, namely the Normalized Difference Vegetation Index (NDVI) [44,45] and the Normalized Difference Water Index (NDWI) [46], as well as Tasseled cap wetness, greenness and brightness (Table 1) [47]. We implemented a pixel-based compositing approach before the classification procedure and calculated temporal metrics [48][49][50][51] (e.g., 10th, 25th, 50th, 75th, 80th and 90th percentiles of annual time series, as well as a minima and maxima for both annual and growing season time series), which resulted in composites for each target year.…”

Section: Data Processingmentioning

confidence: 99%

Monitoring of Urban Sprawl and Densification Processes in Western Germany in the Light of SDG Indicator 11.3.1 Based on an Automated Retrospective Classification Approach

et al. 2021

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By 2050, two-third of the world’s population will live in cities. In this study, we develop a framework for analyzing urban growth-related imperviousness in North Rhine-Westphalia (NRW) from the 1980s to date using Landsat data. For the baseline 2017-time step, official geodata was extracted to generate labelled data for ten classes, including three classes representing low, middle, and high level of imperviousness. We used the output of the 2017 classification and information based on radiometric bi-temporal change detection for retrospective classification. Besides spectral bands, we calculated several indices and various temporal composites, which were used as an input for Random Forest classification. The results provide information on three imperviousness classes with accuracies exceeding 75%. According to our results, the imperviousness areas grew continuously from 1985 to 2017, with a high imperviousness area growth of more than 167,000 ha, comprising around 30% increase. The information on the expansion of urban areas was integrated with population dynamics data to estimate the progress towards SDG 11. With the intensity analysis and the integration of population data, the spatial heterogeneity of urban expansion and population growth was analysed, showing that the urban expansion rates considerably excelled population growth rates in some regions in NRW. The study highlights the applicability of earth observation data for accurately quantifying spatio-temporal urban dynamics for sustainable urbanization and targeted planning.

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Green Space, Physical Activity, and Complete Mental Health: Evidence from the Canadian Longitudinal Study on Aging

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Bioecological theory (Bronfenbrenner, 1979) suggests that local green space and physical activity may be associated with complete mental health outcomes; however, evidence is mixed.Mixed findings may be attributable to the different operationalizations of variables and/or covariates that have been used. The current study used specification curve analysis to assess the robustness of associations between green space, physical activity, and complete mental health among middle-aged and older adults. Data came from the Canadian Longitudinal Study on Aging and the Canadian Urban Environmental Health Research Consortium (n = 28,635). Green space and physical activity did not interact in most instances. Main effects of green space were mixed (49.71 -75.26%), and median effect sizes were small (β = -0.016, 0.025). Main effects of physical activity were robust (89.47 -97.22%), and median effect sizes were small (β = -0.036, 0.036). Results highlight that specification decisions influence the strength of associations between variables.

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Application of NDVI in Environmental Justice, Health and Inequality Studies – Potential and Limitations in Urban Environments

Cited by 5 publications

References 0 publications

Mapping and assessment of vegetation cover change and species variation in Medan, North Sumatra

Mapping and assessment of vegetation cover change and species variation in Medan, North Sumatra

Monitoring of Urban Sprawl and Densification Processes in Western Germany in the Light of SDG Indicator 11.3.1 Based on an Automated Retrospective Classification Approach

Green Space, Physical Activity, and Complete Mental Health: Evidence from the Canadian Longitudinal Study on Aging

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