Principal component analysis

Greenacre, Michael; Groenen, Patrick J. F.; Hastie, Trevor; D’Enza, Alfonso Iodice; Markos, Angelos; Tuzhilina, Elena

doi:10.1038/s43586-022-00184-w

Cited by 152 publications

(79 citation statements)

References 125 publications

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“…The PCA is a multivariate statistical method that reduces the dimensionality of large data sets. The number of principal components (PCs) corresponds to the number of variables used in the PCA analysis (Greenacre et al., 2022). In this section, seven variables were used for PCA analysis, including clay, sand, bulk density, moisture content, resistivity and EC of soil and water samples.…”

Section: Resultsmentioning

confidence: 99%

Soil resistivity measurements to evaluate subsoil salinity in rice production systems in the Vietnam Mekong Delta

Nguyen,

Germer,

Duong

et al. 2023

Near Surface Geophysics

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Rice is a staple crop in the Vietnam Mekong Delta (VMD) in which more than half of Vietnam's rice is produced. However, rice production in the VMD is threatened by increasing saltwater intrusion due to land subsidence and climate change induced sea level rise. Saltwater intrusion into lowland areas through the canal system or capillary rise of saline water from near surface saline water tables may result in salt accumulation in the topsoil. Therefore, it is important to disentangle the two effects and their relative importance to implement appropriate strategies for water and salinity management for adapting rice production systems of the VMD to climate change. Here, we report on the possibility of using geoelectrical methods to evaluate the potential threat of subsoil salinity to rice production. To evaluate the level of subsoil salinity, we measured soil electrical resistivity using an ARES II to a depth of 40 m in a case study comprising five locations in the VMD. Electrical resistivity measurements were calibrated to soil types, which were identified through evaluating 1 m core sections obtained by drilling down to 40 m depth. The relationship between drilling data and soil resistivity was determined by applying clustering and principal component analysis. Resistivity values smaller than 3 Ω m were clearly identified as indicative for a saline water table. The results show a direct link between the depth of the saline water table and the proximity to the sea, but not to the rice production system (single, double, or triple cropping). This study proved for the first time the applicability of the electrical resistivity tomography method for identifying groundwater tables and evaluating subsoil salinity on an agricultural field scale in the VMD.

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Section: Resultsmentioning

confidence: 99%

Soil resistivity measurements to evaluate subsoil salinity in rice production systems in the Vietnam Mekong Delta

Nguyen,

Germer,

Duong

et al. 2023

Near Surface Geophysics

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“…To further understand the extent to which each FM service contributed to satisfaction with overall service quality, a principal component analysis (PCA) was conducted. According to Greenacre et al (2020), PCA offers an opportunity to approximate an original data set using a linear combination of the main variables that highly affect the variance of all the variables. To test whether the sample size fits PCA, the Kaiser–Meyer–Olkin measure of sampling adequacy (KMO) and Bartlett’s test of sphericity (BTS) were computed.…”

Section: Resultsmentioning

confidence: 99%

A post-occupancy evaluation of in-house facilities management service quality and user satisfaction in multi-tenanted office buildings in Ghana

Tannor

Appau

Attakora‐Amaniampong

2023

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Purpose The purpose of this study is to explore user satisfaction with in-house facility management (FM) services in multi-tenanted office buildings in Accra, Ghana using a post-occupancy evaluation (POE) approach. Design/methodology/approach The study assessed user satisfaction with FM service quality by using a POE of their perceptions about the attitude and courtesy of the FM personnel, the reliability of the FM services they provide, the responsiveness and the competence of the service providers. The study used walk-throughs and questionnaire surveys as the POE methods. One hundred and twenty-one users from 22 multi-tenanted office buildings, who have actively used the FM services for at least a year, were purposively sampled. The data was collected via a survey using a structured questionnaire. The data was analysed using descriptive statistics and principal component analysis in version 25 of statistical package for the social sciences. Findings The study revealed that users were dissatisfied with the quality of in-house FM services across all 15 services The results also showed that users’ satisfaction with the services is not affected by the differences in their age, gender, educational level, job role and number of years in the buildings. The results further demonstrated that the most critical factors that resulted in users’ dissatisfaction were electric facilities, building fabric maintenance, emergency coordination, waste management and the decoration of the buildings during festive seasons. Originality/value To the best of the authors’ knowledge, the present study based on POE to assess user satisfaction with FM services for multi-tenant office buildings has, presumably, not been tackled before in Ghana. The results of the study are very essential to the owners of the buildings and facility managers in decision-making concerning the delivery of FM services. Building industry-wise, the results demonstrate the need for in-house FM managers in multi-tenanted office buildings in Ghana to adopt FM service delivery methods that increase user satisfaction. The results also call for further research into user satisfaction with outsourced FM services in multi-tenanted office buildings and further research on the use of the in-house strategy on other types of buildings to ascertain whether the dissatisfaction with FM is due to other factors such as the choice of FM strategy, the property type etc.

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“…The first principal component explains the most variance and subsequent components capture decreasing amounts of variance. Retaining only a subset of the principal components can reduce the data's dimensionality while preserving the most critical patterns and relationships (Greenacre et al, 2022;Jolliffe & Cadima, 2016;Wold et al, 1987). Table 3 shows the results of the PCA analysis, which presents the seven main principal components arranged in the columns labeled from PC1 to PC7.…”

Section: Re Sults and Discussionmentioning

confidence: 99%

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

Billa,

Santos,

Negri

2023

Transactions in GIS

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Rainfall is one of the primary triggers for many geological and hydrological natural disasters. While the geological events are related to mass movements in land collapse due to waterlogging, the hydrological ones are usually assigned to runoff or flooding. Studies in the literature propose predicting mass movement events as a function of accumulated rainfall levels recorded at distinct periods. According to these approaches, a two‐dimensional rainfall levels feature space is segmented into the occurrence and non‐occurrence decision regions by an empirical critical curve (CC). Although this scheme may easily be extended to other purposes and applications, studies in the literature need to discuss its use for flooding prediction. In light of this motivation, the present study is unfolded in (1) verifying that defining CCs in the rainfall levels feature space is a practical approach for flooding prediction and (2) analyzing how geospatial components interact with rainfall levels and flooding prediction. A database containing the rainfall levels recorded for flooding and non‐flooding events in São Paulo city, Brazil, regarding the period 2015–2016, was considered in this study. The results indicate good accuracy for flooding prediction using only partial rain, which can be improved by adding physical characteristics of the flooding locations, demonstrating a direct correlation with spatial interactions, and rainfall levels.

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Principal component analysis

Cited by 152 publications

References 125 publications

Soil resistivity measurements to evaluate subsoil salinity in rice production systems in the Vietnam Mekong Delta

Soil resistivity measurements to evaluate subsoil salinity in rice production systems in the Vietnam Mekong Delta

A post-occupancy evaluation of in-house facilities management service quality and user satisfaction in multi-tenanted office buildings in Ghana

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

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