1,721,013 research outputs found
Where and whom you collect weightings from matters…” Capturing wellbeing priorities within a vulnerable context: a case study of Volta Delta, Ghana
No full textWellbeing is a crucial policy outcome within sustainable development, yet it can be measured and conceptualised in various ways. Methodological decisions, such as how different components are weighted, can influence wellbeing classification. Many studies utilise equal weighting, assuming each component is equally important; however, does this reflect communities’ lived experiences? This study outlines a multidimensional basic needs deprivation measure constructed from the Deltas, Vulnerability and Climate Change: Migration and Adaptation (DECCMA) survey dataset in Volta Delta, Ghana. Participatory focus groups, interviews and weighting exercises with communities and District Planning Officers (DPOs) explore different subgroups’ wellbeing priorities. Comparative analysis examines the weights provided across genders, decision-making levels and livelihoods; including farming, fishing and peri-urban groups. Objective survey data is also combined with various subjective weights to explore the sensitivity of the overall deprivation rate and its spatial distribution. Significant weight differences are found between livelihoods, with farming and fishing communities weighting “employment”, “bank access”, and “cooperative membership” higher, whereas peri-urban communities apply a greater weight to “healthcare access”. Differences between decision-making levels are also noted. Community members weight “employment” higher, while DPOs assign a larger score to “cooperative membership”. In contrast, consistent weights emerge across genders. Furthermore, applying community livelihood weights produces lower deprivation rates across most communities compared to DPO or equal nested weights. Overall, significant differences between subgroups’ weights and the sensitivity of wellbeing measurement to weighting selection illustrate the importance of not only collecting local weights, but also where and whom you collect weightings from matters
Opposing objective and subjective wellbeing outcomes within an environmentally vulnerable delta: a case study of Volta Delta, Ghana
No full textIntroduction: despite a growing interest in the measurement and conceptualization of wellbeing, the integration within sustainability research, and the understanding of how different wellbeing outcomes relate, is limited. Many studies focus on singular, often objectively measured, outcomes, without acknowledging the breadth of available measures. This approach can result in crucial subjective information, which can be explored to understand actors’ behaviors and responses, being omitted from research and policy. This study explores objective and subjective wellbeing outcomes, and how they relate, within an environmentally vulnerable context. Wellbeing and environmental services are intrinsically interlinked, therefore, appropriate policy solutions are required to address human needs and pressures on supporting ecosystems.Methods: this paper uses binary logistic regression modelling, and qualitative participatory rural appraisal methods, to understand the environmental conditions, including climatic hazards and landscape characteristics, associated with households experiencing different objective/subjective wellbeing outcomes within Volta Delta, Ghana.Results: the mixed method approach highlights a differing relationship between inland agricultural areas impacted by drought and erosion, and coastal/riverine, peri-urban landscapes exposed to flooding and salinization. Agricultural areas associate with “poor but happy” outcomes, whereas peri-urban landscapes associate with being “non-poor but unhappy.” Drawing on existing literature, and both quantitative and qualitative results, these varying outcomes are hypothesized to be driven by differences in livelihood vulnerability, relative comparisons to others, responses to climatic hazards, and individualistic/collective wellbeing conceptualizations.Discussion: our study concludes that environmental conditions influence objective and subjective wellbeing through different mechanisms. Sustainable development research should incorporate both objective and subjective measures when implementing and monitoring policy to more comprehensibly capture, and improve, wellbeing in environmentally vulnerable locations
Predicting socioeconomic conditions from satellite sensor data in rural developing countries: a case study using female literacy in Assam, India
No full textSocial data from census and household surveys provide key information for monitoring the status of populations, but the data utility can be limited by temporal gaps between surveys. Recent studies have pointed to the potential for remotely sensed satellite sensor data to be used as proxies for social data. Such an approach could provide valuable information for the monitoring of populations between enumeration periods. Field observations in Assam, north-east India suggested that socioeconomic conditions could be related to patterns in the type and abundance of local land cover dynamics prompting the development of a more formal approach. This research tested if environmental data derived from remotely sensed satellite sensor data could be used to predict a socioeconomic outcome using a generalised autoregressive error (GARerr) model. The proportion of female literacy from the 2001 Indian National Census was used as an indicator of socioeconomic conditions. A significant positive correlation was found with woodland and a significant negative correlation with winter cropland (i.e., additional cropping beyond the normal cropping season). The dependence of female literacy on distance to nearest road was very small. The GARerr model reduced residual spatial autocorrelation and revealed that the logistic regression model over-estimated the significance of the explanatory covariates. The results are promising, while also revealing the complexities of population–environment interactions in rural, developing world contexts. Further research should explore the prediction of socioeconomic conditions using fine spatial resolution satellite sensor data and methods that can account for such complexities.<br/
Exploring the links between census and environment using remotely sensed satellite sensor imagery
No full textRelationships are often found between socio-economic variables and environmental factors for relatively small study regions. This research forms an exploratory data analysis using logistic regression to explore the (non-causal) relationships between socio-economic variables from a national census (female literacy and involvement in economic alternatives to agricultural work) and environmental metrics extracted from Earth observation (EO) data. The relationships observed often supported those found in the literature and field observations. The research highlighted the limited but potentially valuable use of EO data for monitoring socio-economic conditions which may be used to target development assistance in the future.<br/
Social capital typologies and sustainable development: spatial patterns in the central and southern regions of Malawi
No full textBonding, bridging and linking social capital can be a useful mechanism to promote sustainable development in low-income countries. Social capital typologies vary spatially, with the rural poor having a specific combination. Similarly, bonding, bridging and linking social capital’s association with sustainable development is also likely to differ spatially across a country, but there is limited research in low-income countries. This study aims to improve understanding of the spatial variation of bonding, bridging and linking social capital in low-income countries using Malawi as a case study. Using secondary data and spatial statistics, including kriging and geographically weighted regression, we explore the spatial variation of social capital typologies and their spatial associations with various sustainable development indicators. There were three key combinations of bonding, bridging and linking social capital, which differ from the standard model of social capital typologies for the rural poor. We also found social capital’s association with sustainable development indicators depends on the social capital typology, study area and the sustainable development indicator in question. With this in mind, development practitioners, researchers and policymakers should aim to understand the specific social capital context prior to sustainable development research or project implementation
Community-level climate and environmental change adaptation initiatives in Nawalparasi, Nepal
No full textEvaluating the utility of the ensemble transform Kalman filter for adaptive sampling when updating a hydrodynamic model
No full textThis paper compares two Monte Carlo sequential data assimilation methods based on the Kalman filter, for estimating the effect of measurements on simulations of state error variance made by a one-dimensional hydrodynamic model. The first method used an ensemble Kalman filter (EnKF) to update state estimates, which were then used as initial conditions for further simulations. The second method used an ensemble transform Kalman filter (ETKF) to quickly estimate the effect of measurement error covariance on forecast error covariance without the need to re-run the simulation model. The ETKF gave an unbiased estimate of EnKF analysed error variance, although differences in the treatment of measurement errors meant the results were not identical. Estimates of forecast error variance could also be made, but their accuracy deteriorated as the time from measurements increased due in part to model non-linearity and the decreasing signal variance. The motivation behind the study was to assess the ability of the ETKF to target possible measurements, as part of an adaptive sampling framework, before they are assimilated by an EnKF-based forecasting model on the River Crouch, Essex, UK. The ETKF was found to be a useful tool for quickly estimating the error covariance expected after assimilating measurements into the hydrodynamic model. It, thus, provided a means of quantifying the ‘usefulness’ (in terms of error variance) of possible sampling schemes.<br/
A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+
No full textThe automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 ?m, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classification
The 1999 super cyclone in Odisha, India: A systematic review of documented losses
No full textClimate-related hazards accounted for over 90% of disasters over the past two decades and cause massive losses every year worldwide. In the face of the climate crisis, we are confronted with unprecedented challenges that require transformational change. The Sustainable Development Goals, the Paris Agreement and the Sendai Framework for Disaster Risk Reduction set ambitious global goals and targets. Monitoring and reporting are fundamental towards their achievement. We are, thus, faced with an urgency to step up accountability efforts. India is one of the top ten countries by cumulative disaster losses, with the most intense recorded event being the 1999 Odisha super cyclone. Twenty years later, there is still no comprehensive documentation of the losses caused by the cyclone at the micro-level, nor an understanding of long-term post-disaster recovery patterns. To fill this gap, a systematic review has been conducted to gather evidence of recorded losses by type and their spatial distribution. Results show that satellite remote sensing has contributed to a finer and more localised estimation of losses compared to official records from 1999; that coastal and riverine districts are proven to be the worst impacted; and that we now have an understanding, albeit partial, of the non-physical impacts associated with the 1999 cyclone. This review provides the most comprehensive catalogue of documented losses induced by the 1999 super cyclone and is the best estimate of a baseline of impacts which can serve to investigate long-term recovery trends.</p
Hazard, vulnerability and risk on the Brahmaputra basin: a case study of river bank erosion
No full textThe authors present an assessment of risk from river bank erosion in the Brahmaputra river basin. The concept of risk is conceptualised in the context of socio-economic vulnerability, and the potential for exposure to hazard. By addressing both the physical hazard and the variations across the socio-economic surface the approach presented attempts to spatially combine these parameters to provide a risk surface for use by policy makers and decision makers at a number of administrative levels. The concept of vulnerability and risk as a description of the status of a society with respect to an imposed hazard such as flooding or the associated bank erosion exacerbated by climate change is deep rooted in a very broad research effort and its associated publications. In part, this reflects the complex evolution of the underlying notion of hazard - which itself shows the concurrent evolution of a series of strands each representing one disciplinary tradition. The concept of vulnerability has been very widely treated in the literature, and For present purposes an acceptable approach to vulnerability may be to start with an influential (but still controversial) established model by IPCC (2001) who have developed working definition - and then explore its ramifications in order to develop a set of working definitions and operational indicators for the project. This provides a pragmatic route towards a realistic target. It also offers a possible buffer against the common experience that the more sophisticated indices of vulnerability are strongly sensitive to contingent local/historical circumstances. This approach is explored within this chapter. The hazard posed by unabated bank erosion has been analysed with the help of satellite imagery based data and through adoption of Plan Form Index along with its threshold values develop for the Brahmaputra. The land loss to erosion is depicting a significantly rising trend which has obviously contributed to the impoverishment of the riverine population. The attendant uncertainties of climate change of hydrological and hydraulic river behaviour may exacerbate the channel instability of the Brahmaputra
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