<i><b>GeoDa</b></i>: An Introduction to Spatial Data Analysis

Anselin, Luc; Syabri, Ibnu; Kho, Youngihn

doi:10.1111/j.0016-7363.2005.00671.x

Cited by 2,142 publications

(1,264 citation statements)

References 43 publications

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“…It is based on the Local Moran's I statistic (Anselin et al 2006). The relative density of unhealthy food outlets (as per the RFEI) and area socioeconomic deprivation level of each census area unit were compared to those from neighbouring CAUs.…”

Section: Spatial and Statistical Analysismentioning

confidence: 99%

Food swamps by area socioeconomic deprivation in New Zealand: a national study

Sushil

Vandevijvere

Exeter

et al. 2017

Int J Public Health

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Objectives A nationwide spatial analysis of community retail food environments in relation to area socioeconomic deprivation was conducted in New Zealand.Methods Addresses from about 20,000 registered food outlets were retrieved from all 66 Councils. Outlets were classified, geocoded and (spatially) validated. The analysis included 4087 convenience, 4316 fast food/takeaway and 1271 supermarket and fruit/vegetable outlets and excluded outlets not considered 'healthy' or 'unhealthy'. The population-weighted density of different outlet types in Census areas and the proximity to different outlet types from Meshblock centres were calculated and associations with area socioeconomic deprivation assessed. Spatial scan statistics was used to identify food swamp areas with a significantly higher relative density of unhealthy outlets than other areas. Results A significantly positive association was observed between area deprivation and density of all retailers. A significantly negative association was observed between area deprivation and proximity to all retailers. Nationwide, 722 Census areas were identified as food swamps. Conclusions Access to food retailers is significantly higher in more deprived areas than in less deprived areas. Restricting unhealthy outlets in areas with a high relative density of those outlets is recommended.

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Section: Spatial and Statistical Analysismentioning

confidence: 99%

Food swamps by area socioeconomic deprivation in New Zealand: a national study

Sushil

Vandevijvere

Exeter

et al. 2017

Int J Public Health

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“…The ratio of burned area was calculated using the total forest area provided by IGE (2012a). The GeoDa software was used to obtain the spatial statistics of the dependent variables (Anselin et al, 2006;GeoDa, 2014). In order to create the final database, and conduct the estimation process, the Stata 10.1 software was used (Stata, 2010).…”

Section: Datamentioning

confidence: 99%

Modelling spatial patterns and temporal trends of wildfires in Galicia (NW Spain)

Pernas¹,

Loureiro²

2015

For. syst.

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Aim of study: The goal of this paper is to analyse the importance of the main contributing factors to the occurrence of wildfires.Area of study: We employ data from the region of Galicia during 2001-2010; although the similarities shared between this area and other rural areas may allow extrapolation of the present results.Material and Methods: The spatial dependence is analysed by using the Moran's I and LISA statistics. We also conduct an econometric analysis modelling both, the number of fires and the relative size of afflicted woodland area as dependent variables, which depend on the climatic, land cover variables, and socio-economic characteristics of the affected areas. Fixed effects and random effect models are estimated in order to control for the heterogeneity between the Forest Districts in Galicia.Main results: Moran's I and LISA statistics show that there is spatial dependence in the occurrence of Galician wildfires. Econometrics models show that climatology, socioeconomic variables, and temporal trends are also important to study both, the number of wildfires and the burned-forest ratio.Research highlights: We conclude that in addition to direct forest actions, other agricultural or social public plans, can help to reduce wildfires in rural areas or wildland-urban areas. Based on these conclusions, a number of guidelines are provided that may foster the development of better forest management policies in order to reduce the occurrence of wildfires.

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“…Using the resulting maps (agriculture and forest centred maps for counties that were destinations for live plant imports) we estimated hotspots for potential invasion in those two plant ecosystems. To perform this procedure we used the software GeoDa (Anselin et al 2006) and computed the Moran's I to detect clusters of counties with high volume of imports. Moran's I is a local indicator of spatial association (Anselin 1995), and in our case, it detected which counties were the destinations of significantly higher volume of live plant imports than the mean volume for the entire contiguous U.S. (Fortin and Dale 2005).…”

Section: Methodsmentioning

confidence: 99%

Understanding trade pathways to target biosecurity surveillance

Colunga-Garcia¹,

Haack²,

Magarey³

et al. 2013

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Increasing trends in global trade make it extremely difficult to prevent the entry of all potential invasive species (IS). Establishing early detection strategies thus becomes an important part of the continuum used to reduce the introduction of invasive species. One part necessary to ensure the success of these strategies is the determination of priority survey areas based on invasion pressure. We used a pathway-centred conceptual model of pest invasion to address these questions: what role does global trade play in invasion pressure of plant ecosystems and how could an understanding of this role be used to enhance early detection strategies? We concluded that the relative level of invasion pressure for destination ecosystems can be influenced by the intensity of pathway usage (import volume and frequency), the number and type of pathways with a similar destination, and the number of different ecological regions that serve as the source for imports to the same destination. As these factors increase, pressure typically intensifies because of increasing a) propagule pressure, b) likelihood of transporting pests with higher intrinsic invasion potential, and c) likelihood of transporting pests into ecosystems with higher invasibility. We used maritime containerized imports of live plants into the contiguous U.S. as a case study to illustrate the practical implications of the model to determine hotspot areas of relative invasion pressure for agricultural and forest ecosystems (two ecosystems with high potential invasibility). Our results illustrated the importance of how a pathway-centred model could be used to highlight potential target areas for early detection strategies for IS. Many of the hotspots in agricultural and forest ecosystems were within major U.S. metropolitan areas. Invasion ecologists can utilize pathway-centred conceptual models to a) better understand the role of human-mediated pathways in pest establishment, b) enhance current methodologies for IS risk analysis, and c) develop strategies for IS early detection-rapid response programs.

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GeoDa: An Introduction to Spatial Data Analysis

Cited by 2,142 publications

References 43 publications

Food swamps by area socioeconomic deprivation in New Zealand: a national study

Food swamps by area socioeconomic deprivation in New Zealand: a national study

Modelling spatial patterns and temporal trends of wildfires in Galicia (NW Spain)

Understanding trade pathways to target biosecurity surveillance

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