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Geographies, Volume 1, Issue 2 (September 2021) – 4 articles

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Article
Analysis of the Impact of Positional Accuracy When Using a Block of Pixels for Thematic Accuracy Assessment
Geographies 2021, 1(2), 143-165; https://0-doi-org.brum.beds.ac.uk/10.3390/geographies1020009 (registering DOI) - 18 Sep 2021
Abstract
Pixels, blocks (i.e., grouping of pixels), and polygons are the fundamental choices for use as assessment units for validating per-pixel image classification. Previous research conducted by the authors of this paper focused on the analysis of the impact of positional accuracy when using [...] Read more.
Pixels, blocks (i.e., grouping of pixels), and polygons are the fundamental choices for use as assessment units for validating per-pixel image classification. Previous research conducted by the authors of this paper focused on the analysis of the impact of positional accuracy when using a single pixel for thematic accuracy assessment. The research described here provided a similar analysis, but the blocks of contiguous pixels were chosen as the assessment unit for thematic validation. The goal of this analysis was to assess the impact of positional errors on the thematic assessment. Factors including the size of a block, labeling threshold, landscape characteristics, spatial scale, and classification schemes were also considered. The results demonstrated that using blocks as an assessment unit reduced the thematic errors caused by positional errors to under 10% for most global land-cover mapping projects and most remote-sensing applications achieving a half-pixel registration. The larger the block size, the more the positional error was reduced. However, there are practical limitations to the size of the block. More classes in a classification scheme and higher heterogeneity increased the positional effect. The choice of labeling threshold depends on the spatial scale and landscape characteristics to balance the number of abandoned units and positional impact. This research suggests using the block of pixels as an assessment unit in the thematic accuracy assessment in future applications. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2021)
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Article
Accessibility Indicators for the Geographical Assessment of Transport Planning in a Latin American Metropolitan Area
Geographies 2021, 1(2), 124-142; https://0-doi-org.brum.beds.ac.uk/10.3390/geographies1020008 - 02 Sep 2021
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Abstract
Accessibility represents a key element in strengthening developed regions in terms of investment in transportation infrastructure. Accessibility is also an equity indicator to measure the ease with which a specific location achieves desired outcomes as well as the spillover effect; traditionally, these effects [...] Read more.
Accessibility represents a key element in strengthening developed regions in terms of investment in transportation infrastructure. Accessibility is also an equity indicator to measure the ease with which a specific location achieves desired outcomes as well as the spillover effect; traditionally, these effects have been analyzed with econometric and engineering techniques, rather than from the perspective of geographical studies. The purpose of this research is to measure the spillover effects and the territorial cohesion of Infrastructure Regional Planning (PRI) for the Latin American metropolitan area of Concepción (MAC), Chile. To meet this purpose, locational and network efficiency indicators of spatial accessibility were calculated using network analysis in GIS. The results showed that the improvements differ according to the accessibility indicator employed; however, they generally showed benefits in consolidated urban centers and corridors near investment and industrial areas. In contrast, more distant and rural areas presented limited and irregular benefits. Full article
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Article
Who and Why? Understanding Rural Out-Migration in Uganda
Geographies 2021, 1(2), 104-123; https://0-doi-org.brum.beds.ac.uk/10.3390/geographies1020007 - 25 Aug 2021
Viewed by 348
Abstract
Rural–urban migration in developing countries is considered to be a key process for sustainable development in the coming decades. On the one hand, rural–urban migration can contribute to the socioeconomic development of a country. On the other hand, it also leads to labor [...] Read more.
Rural–urban migration in developing countries is considered to be a key process for sustainable development in the coming decades. On the one hand, rural–urban migration can contribute to the socioeconomic development of a country. On the other hand, it also leads to labor transfer, brain-drain in rural areas, and overcrowded cities where planning is lagging behind. In order to get a better insight into the mechanisms of rural–urban migration in developing countries, this paper analyzes motivations for rural–urban migration from the perspective of rural households in Uganda. A total of 1015 rural households located in southwestern Uganda were surveyed in 2019. A total of 48 percent of these households reported having at least one out-migrant. By means of logistic regression modeling, the likelihood for rural out-migration was assessed using household- and community-level socioeconomic characteristics as predictors. The results show that most out-migrants are from relatively wealthy households with a higher-than-average education level. Typically, these households are located in villages that are well connected with urban centers. Poor households in remote locations send significantly fewer migrants because of their limited access to migration information and poor transport networks. From these findings, the following policy recommendations are made: Firstly, efforts should be made to extend basic social services, including quality education, towards rural areas. Secondly, in order to reduce socially disruptive long-distance migration and the eventual overcrowding and sprawls of major cities, government investments should be oriented towards the upgrading of secondary towns, which can offer rural out-migrants rewarding employment and business opportunities. Full article
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Article
Modeling Insolation, Multi-Spectral Imagery and LiDAR Point-Cloud Metrics to Predict Plant Diversity in a Temperate Montane Forest
Geographies 2021, 1(2), 79-103; https://0-doi-org.brum.beds.ac.uk/10.3390/geographies1020006 - 23 Aug 2021
Viewed by 366
Abstract
Incident solar radiation (insolation) passing through the forest canopy to the ground surface is either absorbed or scattered. This phenomenon, known as radiation attenuation, is measured using the extinction coefficient (K). The amount of radiation reaching the ground surface of a given site [...] Read more.
Incident solar radiation (insolation) passing through the forest canopy to the ground surface is either absorbed or scattered. This phenomenon, known as radiation attenuation, is measured using the extinction coefficient (K). The amount of radiation reaching the ground surface of a given site is effectively controlled by the canopy’s surface and structure, determining its suitability for plant species. Menhinick’s and Simpson’s biodiversity indexes were selected as spatially explicit response variables for the regression equation using canopy structure metrics as predictors. Independent variables include modeled area solar radiation, LiDAR-derived canopy height, effective leaf area index data derived from multi-spectral imagery and canopy strata metrics derived from LiDAR point-cloud data. The results support the hypothesis that (1) canopy surface and strata variability may be associated with understory species diversity due to radiation attenuation and the resultant habitat partitioning and that, (2) such a model can predict both this relationship and biodiversity clustering. The study data yielded significant correlations between predictor and response variables and were used to produce a multiple–linear model comprising canopy relief, the texture of heights, and vegetation density to predict understory plant diversity. When analyzed for spatial autocorrelation, the predicted biodiversity data exhibited non-random spatial continuity. Full article
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