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Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low- and middle-income countries, crop yields have traditionally been assessed based on farmer-reported production and land areas in household and farm surveys, occasionally by objective crop cuts for a sub-section of a farmer’s plot, and rarely using full-plot harvests. In parallel, satellite data continue to improve in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study evaluates ground and satellite-based approaches to estimating crop yields and yield responsiveness to inputs, using data on maize from Eastern Uganda. Using unique, simultaneous ground data on yields based on farmer reporting, sub-plot crop cutting, and full-plot harvests across hundreds of smallholder plots, we document large discrepancies among the ground-based measures, particularly among yields based on farmer-reporting versus sub-plot or full-plot crop cutting. Compared to yield measures based on either farmer-reporting or sub-plot crop cutting, satellite-based yield measures explain as much or more variation in yields based on (gold-standard) full-plot crop cuts. Further, estimates of the association between maize yield and various production factors (e.g., fertilizer, soil quality) are similar across crop cut- and satellite-based yield measures, with the use of the latter at times leading to more significant results due to larger sample sizes. Overall, the results suggest a substantial role for satellite-based yield estimation in measuring and understanding agricultural productivity in the developing world.

This paper quantifies the significance and magnitude of the effect of measurement error in remote sensing weather data in the analysis of smallholder agricultural productivity. The analysis leverages 17 rounds of nationally-representative, panel household survey data from six countries in Sub-Saharan Africa. These data are spatially linked with a range of geospatial weather data sources and related metrics. The paper provides systematic evidence on measurement error introduced by (1) different methods used to obfuscate the exact GPS coordinates of households, (2) different metrics used to quantify precipitation and temperature, and (3) different remote sensing measurement technologies. First, the analysis finds no discernible effect of measurement error introduced by different obfuscation methods. Second, it finds that simple weather metrics, such as total seasonal rainfall and mean daily temperature, outperform more complex metrics, such as deviations in rainfall from the long-run average or growing degree days, in a broad range of settings. Finally, the analysis finds substantial amounts of measurement error based on remote sensing products. In extreme cases, the data drawn from different remote sensing products result in opposite signs for coefficients on weather metrics, meaning that precipitation or temperature drawn from one product purportedly increases crop output while the same metrics drawn from a different product purportedly reduces crop output. The paper concludes with a set of six best practices for researchers looking to combine remote sensing weather data with socioeconomic survey data.

Between 2014 and 2016 unprecedented and consecutive climatic shocks ravaged Malawi, one of the poorest countries in the world. The largest ever emergency relief operation in the country’s history ensued. The pathways and extent to which the humanitarian response protected livelihoods remain under researched. This paper uses a unique data set that combines longitudinal household survey data with GIS-based measures of weather shocks and climate conditions and longitudinal administrative data on the World Food Programme’s aid distribution. The paper aims to understand the drivers of humanitarian aid and evaluate the impact of aid and weather shocks on outcomes related to household production and consumption in Malawi. The analysis shows that droughts and floods had consistent negative impacts on a range of welfare outcomes, particularly for households that were subject to sequential shocks. Aid receipt is demonstrated to attenuate such impacts, again particularly for households that experienced the shocks consecutively. Households living in areas subject to a weather shock and with higher World Food Programme aid distribution were more likely to receive food aid, partially explaining the success of aid in mitigating the impacts of shocks. However, there is significant scope for improving the criteria for targeting humanitarian aid beneficiaries.

With the surge in publicly available high-resolution satellite imagery, satellite-based monitoring of smallholder agricultural outcomes is gaining momentum. This paper provides recommendations on how large-scale household surveys should be conducted to generate the data needed to train models for satellite-based crop type mapping in smallholder farming systems. The analysis focuses on maize cultivation in Malawi and Ethiopia, and leverages rich, georeferenced plot-level data from national household surveys that were conducted in 2018–20 and that are integrated with Sentinel-2 satellite imagery and complementary geospatial data. To identify the approach to survey data collection that yields optimal data for training remote sensing models, 26,250 in silico experiments are simulated within a machine learning framework. The best model is then applied to map seasonal maize cultivation from 2016 to 2019 at 10-meter resolution in both countries. The analysis reveals that smallholder plots with maize cultivation can be identified with up to 75 percent accuracy. However, the predictive accuracy varies with the approach to georeferencing plot locations and the number of observations in the training data. Collecting full plot boundaries or complete plot corner points provides the best quality of information for model training. Classification performance peaks with slightly less than 60 percent of the training data. Seemingly small erosion in accuracy under less preferable approaches to georeferencing plots results in total area under maize cultivation being overestimated by 0.16 to 0.47 million hectares (8 to 24 percent) in Malawi.

The availability of affordable head-mounted display technology has facilitated new, potentially more immersive, interactive multimedia experiences. These technologies were traditionally focused on entertainment; however, academia and industry are now exploring applications in other domains such as health, learning and training. Key to the success of these new multimedia experiences is the understanding of a user’s perceived quality of experience (QoE). Subjective user ratings have been the primary mechanism to capture insights into a user’s experience. Such ratings have generally been captured post experience and reflected using a mean opinion score (MOS). However, user perception is multifactorial and subjective ratings alone do not express the true measure of an experience. As a result, recent efforts to capture QoE have included exploring the use of implicit metrics (e.g. physiological measures). This article presents the results of an experimental QoE evaluation and comparison of immersive applications delivered across three multimedia platforms. The platforms compared were augmented reality, tablet and virtual reality. The QoE methodology employed considered explicit (post-test questionnaire) and implicit (heart rate and electrodermal activity) assessment methods. The results indicate comparatively higher levels of QoE for users of the augmented reality and tablet platforms. yes

This paper studies the impact of transport infrastructure projects of the Belt and Road Initiative on shipment times and trade costs. Based on a new data on completed and planned Belt and Road transport projects, Geographic Information System analysis is used to estimate shipment times before and after the Belt and Road Initiative. Two sets of data are computed to address different research questions: a global database based on an analysis of 1,000 cities in 191 countries and 47 sectors and a regional database that focuses on more granular information (1,818 cities) for Belt and Road economies only. The paper uses sectoral estimates of “value of time” to transform changes in shipment times into changes in ad valorem trade costs at the country-sector level. The findings show that the Belt and Road Initiative will significantly reduce shipment times and trade costs. For the world, the average reduction in shipment time will range between 1.2 and 2.5 percent, leading to reduction of aggregate trade costs between 1.1 and 2.2 percent. For Belt and Road economies, the change in shipment times and trade costs will range between 1.7 and 3.2 percent and 1.5 and 2.8 percent, respectively. Belt and Road economies located along the corridors where projects are built experience the largest gains. Shipment times along these corridors decline by up to 11.9 percent and trade costs by up to 10.2 percent. The paper also shows that these effects are magnified by policy reforms that reduce border delays and improve corridor management.

Crop yields in smallholder systems are traditionally assessed using farmer-reported information in surveys, occasionally by crop cuts for a sub-section of a farmer's plot, and rarely using full-plot harvests. Accuracy and cost vary dramatically across methods. In parallel, satellite data is improving in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study uses data from a survey experiment in Uganda, and evaluates the accuracy of Sentinel-2 imagery-based, remotely-sensed plot-level maize yields with respect to ground-based measures relying on farmer self-reporting, sub-plot crop cutting (CC), and full-plot crop cutting (FP). Remotely-sensed yields include two versions calibrated to FP and CC yields (calibrated), and an alternative based on crop model simulations, using no ground data (uncalibrated). On the ground, self-reported yields explained less than 1 percent of FP (and CC) yield variability, and while the average difference between CC and FP yields was not significant, CC yields captured one-quarter of FP yield variability. With satellite data, both calibrated and uncalibrated yields captured FP yield variability on pure stand plots similarly well, and both captured half of FP yield variability on pure stand plots above 0.10 hectare. The uncalibrated yields were consistently 1 ton per hectare higher than FP or CC yields, and the satellite-based yields were less well correlated with the ground-based measures on intercropped plots compared with pure stand ones. Importantly, regressions using CC, FP and remotely-sensed yields as dependent variables all produced very similar coefficients for yield response to production factors.

"This is a work of fiction and a novel-in-progress."--Abstract from author supplied metadata

In an era of neo-liberal ideology, this thesis examines the impact of a paradigm which promotes the ideals of a self-regulating global market and the privatisation of state assets and services. An epoch where humanity’s existence is reduced to mere ‘clients’ and ‘consumers’ of services and products. Whereby the promise of ‘freedom of choice’ means the freedom to; exploit workers, charge extortionate interest-rates for public and private debt, poison our natural habitat and tax avoidance (if you can afford it) (Monbiot, 2016). As the prevalence rates of mental ill health are on the increase and according to some, could be considered to have reached epidemic proportions (Carlat, 2010, Kirsch, 2010, Whitaker, 2010). Investigating the high percentage rate of consumption in prescriptive anti-depressant drugs, I would argue that it is perhaps the pressures from living in a world, as described above, that people are opting out of life and choosing death by suicide. Examining, recent structural changes in our Irish adult and community education sector, I reflect upon the absence of critical and reflexive skills and argue that perhaps this is also having an impact on our mental health. Not being given an opportunity to identify the source of our oppression, how can we act against the forces that cause it? (Freire, 1970). Given that the political left and centre parties have not produced an alternative to neoliberal ideology, those of us who are disillusioned, disturbed and desire to see social justice being restored are seeking other routes to overcome this subordination of our society. My research explores such an attempt, by highlighting the experiential reflections of the lives of ten women, from different religious and cultural backgrounds as well as a wide spectrum in age variance. The participants seek to learn tools for self-transcendence and reflexivity. Although the findings suggest that the participants are active in the engagement of a journey towards a higher consciousness and they support each other. Nevertheless, it appears that they do not engage in collective action for social change. A hypothesis that they are in the process of ‘healing’ themselves first is mooted. As the groups didn’t see the socio-political dimension of community education or spirituality, this study concludes, given the value of inner peace, love and solidarity being over-arching themes in the theory of self-transcendence, I argue, that this is perhaps the necessary first step in creating a new world order.

In rural societies of low- and middle-income countries, land is a major measure of wealth, a critical input in agricultural production, and a key variable for assessing agricultural performance and productivity. In the absence of cadastral information to refer to, measures of land plots have historically been taken with one of two approaches: traversing (accurate, but cumbersome), and farmers' self-report (cheap, but marred by measurement error). Recently, the advent of cheap handheld GPS devices has held promise for balancing cost and precision. Guided by purposely collected primary data from Ethiopia, Nigeria, and Tanzania (Zanzibar), and with consideration for practical household survey implementation, the paper assesses the nature and magnitude of measurement error under different measurement methods and proposes a set of recommendations for plot area measurement. The results largely point to the support of GPS measurement, with simultaneous collection of farmer self-reported areas.

The collection of survey data from war zones or other unstable security situations is vulnerable to error because conflict often limits the implementation options. Although there are elevated risks throughout the process, this paper focuses specifically on challenges to frame construction and sample selection. The paper uses simulations based on data from the Mogadishu High Frequency Survey Pilot to examine the implications of the choice of second-stage selection methodology on bias and variance. Among the other findings, the simulations show the bias introduced by a random walk design leads to the underestimation of the poverty headcount by more than 10 percent. The paper also discusses the experience of the authors in the time required and technical complexity of the associated back-office preparation work and weight calculations for each method. Finally, as the simulations assume perfect implementation of the design, the paper also discusses practicality, including the ease of implementation and options for remote verification, and outlines areas for future research and pilot testing.