Remote Sensing and Urban Green Infrastructure

Chen, Yanhua; Sanesi, Giovanni; Li, Xun; Chen, Wendy Y.

doi:10.1002/9781119625865.ch20

Cited by 3 publications

(2 citation statements)

References 110 publications

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“…Examples include urban gardens, parks, forests, and wildlife reserves as well as systems that involve engineered components, like green roofs, bioswales, and rain gardens. Both types provide many urban ecosystem services, such as reducing heat island effects and mitigating stormwater runoff (Chen et al, 2021). Figure 1 illustrates the fundamental biotic and abiotic components of street‐level engineered green infrastructure contributing to these benefits.…”

Section: Introductionmentioning

confidence: 99%

Planting design influences green infrastructure performance: Plant species identity and complementarity in rain gardens

Bruner

Palmer

Griffin

et al. 2023

Ecological Applications

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Green infrastructure's capacity to mitigate urban environmental problems, like heat island effects and excessive stormwater runoff, is partially governed by its plant community. Traditionally, green infrastructure design has focused on engineered aspects, such as substrate and drainage, rather than on the properties of its living components. Since the functioning of these plant assemblages is controlled by ecophysiological processes that differ by species, the identity and relative abundance of the species used will influence green infrastructure performance. We used trait‐based modeling to derive principles for the effective composition of green infrastructure plant assemblages, parameterizing our model using the vegetation and ecophysiological traits of the species within New York City rain gardens. Focusing on two plant traits that influence rain garden performance, leaf surface temperature and stomatal conductance, we simulated the cumulative temperature and transpiration for plant communities of differing species composition and diversity. The outcomes of the model demonstrate that plant species composition, species identity, selection effects, and interspecific complementarity increase green infrastructure performance in much the way biodiversity affects ecosystem functioning in natural systems. More diverse assemblages resulted in more consistent transpiration and surface temperatures, with the former showing a positive, saturating curve as diversity increased. While the dominant factors governing individual species leaf temperature were abiotic, transpiration was more influential at the community level, suggesting that plants within diverse communities may be cooler in aggregate than any individual species on its own. This implies green infrastructure should employ a variety of vegetation; particularly plants with different statures and physical attributes, such as low‐growing ground covers, erect herbaceous perennials, and shrubs.

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Section: Introductionmentioning

confidence: 99%

Planting design influences green infrastructure performance: Plant species identity and complementarity in rain gardens

Bruner

Palmer

Griffin

et al. 2023

Ecological Applications

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“…The data quality map is critical and beneficial for further analysis to build a higher quality information system for social purposes, such as promoting health [24]. Furthermore, data quality is vital for machine learning, GIS, and social remote sensing (remote sensing complemented by social studies) to complete the health information system [25]. The problem that needs to be solved to gain good data quality relates to the person who performs the data entry [26].…”

Section: Introductionmentioning

confidence: 99%

Posyandu Application for Monitoring Children Under-Five: A 3-Year Data Quality Map in Indonesia

Rinawan

Faza

Susanti

et al. 2022

IJGI

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Posyandu is an Indonesian mother-child health, community-based healthcare. The provision of the Posyandu data quality map is crucial for analyzing results but is limited. This research aimed to (a) demonstrate data quality analysis on its completeness, accuracy, and consistency and (b) map the data quality in Indonesia for evaluation and improvement. An observational study was conducted using the Posyandu application. We observed data in Indonesia from 2019 to 2021. Data completeness was identified using children’s visits/year. Data accuracy was analyzed using WHO anthropometry z-score and implausible z-score values analyzing the outliers. Cronbach’s α of variables was used to know data consistency. STATA 15.1 SE and QGIS 3.10 was used to analyze and map the quality. Data completeness and accuracy in three years show a good start for the pilot project area, continued with declines in pandemic time, while some other areas demonstrated a small start, then slightly increased. The overall consistency decreased through the study period. A good report on data completeness can occur initially in a pilot project area, followed by others. Data accuracy and consistency can decrease during the pandemic. The app can be promising when synchronized with the government health information system.

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Developing a mapping procedure for urban forests using online map services and Sentinel-2A images

Jeong,

Park

2023

Urban Forestry & Urban Greening

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Remote Sensing and Urban Green Infrastructure

Cited by 3 publications

References 110 publications

Planting design influences green infrastructure performance: Plant species identity and complementarity in rain gardens

Planting design influences green infrastructure performance: Plant species identity and complementarity in rain gardens

Posyandu Application for Monitoring Children Under-Five: A 3-Year Data Quality Map in Indonesia

Developing a mapping procedure for urban forests using online map services and Sentinel-2A images

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