Home gardening in Singapore: A feasibility study on the utilization of the vertical space of retrofitted high-rise public housing apartment buildings to increase urban vegetable self-sufficiency

Song, Shuang; Cheong, Jia Chin; Lee, Joel S.H.; Tan, Jonathan K.N.; Chiam, Zhongyu; Arora, Srishti; Png, Karl J.Q.; Seow, Johanah W.C.; Leong, Felicia W.S.; Biljecki, Filip; Tablada, Abel; Tan, Hugh Tiang Wah

doi:10.1016/j.ufug.2022.127755

Cited by 12 publications

(3 citation statements)

References 59 publications

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“…Many people have switched to gardening as their new hobby during the COVID-19 pandemic [89][90][91][92][93][94][95][96][97][98], including Filipinos. The main objective of this study was to determine the preference of plantitas and plantitos for the succulent attributes presented and to perform cluster segments based on the similarities of their answers.…”

Section: Discussionmentioning

confidence: 99%

Plantitas/Plantitos Preference Analysis on Succulents Attributes and Its Market Segmentation: Integrating Conjoint Analysis and K-means Clustering for Gardening Marketing Strategy

et al. 2022

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Many people have switched to gardening as their new hobby during the COVID-19 pandemic, including Filipinos. With its increasing popularity, Filipinos called the new hobbyists “plantitas” and “plantitos” instead of the old-fashioned term “plant people”. Among different plants, succulents are one of the most popular for plant lovers as they can thrive with even minimal care, making them suitable to be an indoor/outdoor plant. This study aims to determine the various preferences of plantitas and plantitos based on succulent attributes using a conjoint analysis approach, and to discover the market segments using a k-means clustering approach. The attributes presented in this study are the types of succulents, succulent variegation, price, size of the succulent (in terms of diameter), size of the pot, pot material, and payment method. The conjoint analysis results indicated that the price was the attribute that significantly affected consumer buying behavior, followed by the diameter size of the succulent. On the other hand, the k-means cluster analysis identified three customer segments based on the buying frequency of customers, namely high-value customers, core-value customers, and lower-value customers. A marketing strategy for succulent sellers was proposed based on these segmentations, particularly on how to gain and attract more customers. This study is one of the first studies that analyzed the preferences related to succulent attributes. Finally, the conjoint analysis approach and k-means clustering in this study can be utilized to analyze succulent preferences worldwide.

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Section: Discussionmentioning

confidence: 99%

Plantitas/Plantitos Preference Analysis on Succulents Attributes and Its Market Segmentation: Integrating Conjoint Analysis and K-means Clustering for Gardening Marketing Strategy

et al. 2022

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“…The increasing awareness of open data initiatives for building smarter cities (Neves et al, 2020) has brought about a ‘digital turn’ into urban studies (Ash et al, 2018). Thanks to the abundant data now available, modern urban analytics seeks advanced technologies, and dedicated models and algorithms, to support better city governance with detailed analysis to aid urban planning processes that tackle socio-economic and environmental problems (Lei et al, 2023b; Wang and Biljecki, 2022; Liu and Biljecki, 2022; Song et al, 2022; Yossef Ravid and Aharon-Gutman, 2022; Kang et al, 2019; Carra and Barthelemy, 2019; Yeh, 1988).…”

Section: Introductionmentioning

confidence: 99%

Explainable spatially explicit geospatial artificial intelligence in urban analytics

Liu,

Zhang,

Biljecki

2023

Environment and Planning B: Urban Analytics and City Science

Self Cite

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Geospatial artificial intelligence (GeoAI) is proliferating in urban analytics, where graph neural networks (GNNs) have become one of the most popular methods in recent years. However, along with the success of GNNs, the black box nature of AI models has led to various concerns (e.g. algorithmic bias and model misuse) regarding their adoption in urban analytics, particularly when studying socio-economics where high transparency is a crucial component of social justice. Therefore, the desire for increased model explainability and interpretability has attracted increasing research interest. This article proposes an explainable spatially explicit GeoAI-based analytical method that combines a graph convolutional network (GCN) and a graph-based explainable AI (XAI) method, called GNNExplainer. Here, we showcase the ability of our proposed method in two studies within urban analytics: traffic volume prediction and population estimation in the tasks of a node classification and a graph classification, respectively. For these tasks, we used Street View Imagery (SVI), a trending data source in urban analytics. We extracted semantic information from the images and assigned them as features of urban roads. The GCN first provided reasonable predictions related to these tasks by encoding roads as nodes and their connectivities and networks as graphs. The GNNExplainer then offered insights into how certain predictions are made. Through such a process, practical insights and conclusions can be derived from the urban phenomena studied here. In this paper we also set out a path for developing XAI in future urban studies.

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“…Researchers have endeavored to explore the sustainable characteristics of vertical farming as a resilient solution for addressing food security concerns. Notable examples include a case study conducted in Singapore [4], Shanghai [5] and Naples, Italy [6] and so on.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Energy Efficiency and Carbon Footprint of Small-Scale Distributed and Centralized Vertical Farming Systems

Wang,

Zhou,

et al. 2023

Preprint

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This paper discusses the potential of small-scale distributed vertical farming in buildings to be a more sustainable and energy-efficient alternative to largescale centralized vertical farming. While vertical farming has the potential to revolutionize urban agriculture by providing fresh produce year-round and reducing transportation emissions, the energy consumption required to power the lighting systems can be significant, particularly in centralized systems. The study compares the energy consumption and growth of pak choi cabbage plants between centralized and distributed vertical farming systems while adopting a traditional cultivation process as a reference. The data from the experiment are used to simulate the carbon emissions generated by vertical farms. The paper concludes that distributed vertical farming offers higher energy efficiency, with a potential 60% reduction in energy consumption and a 30% decrease in carbon footprint relative to large-scale integrated vertical farms. Yielding over twice the crop output compared to conventional agriculture, this approach may serve as a potential solution to address global food challenges.

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Home gardening in Singapore: A feasibility study on the utilization of the vertical space of retrofitted high-rise public housing apartment buildings to increase urban vegetable self-sufficiency

Cited by 12 publications

References 59 publications

Plantitas/Plantitos Preference Analysis on Succulents Attributes and Its Market Segmentation: Integrating Conjoint Analysis and K-means Clustering for Gardening Marketing Strategy

Plantitas/Plantitos Preference Analysis on Succulents Attributes and Its Market Segmentation: Integrating Conjoint Analysis and K-means Clustering for Gardening Marketing Strategy

Explainable spatially explicit geospatial artificial intelligence in urban analytics

Evaluating the Energy Efficiency and Carbon Footprint of Small-Scale Distributed and Centralized Vertical Farming Systems

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