Search Results - "Truth."

International river basin organizations: variation, options and insights by Lautze, Jonathan F., Wegerich, Kai, Kazbekov, Jusipbek S., Yakubov, Murat

“…The results provide a set of options for future IRBOs, and serve to ground-truth and nuance theoretical divisions between different types of organizations in transboundary basins.…”
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Misperceived quality: fertilizer in Tanzania by Michelson, H., Fairbairn, A., Ellison, B., Maertens, A., Manyong, Victor

“…Our results suggest the existence of an equilibrium where farmer beliefs about fertilizer are inconsistent with the truth, and seller incentives to invest to alter beliefs are limited, motivating future research into the origins and persistence of such an equilibrium.…”
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CGIAR GENDER Impact Platform Newsletter, November-December 2022, issue 3 by CGIAR GENDER Impact Platform

“…Updates from across CGIAR include an analysis calling the newly established fund for Loss and Damage “an empty glass waiting to be filled”; the promising potential of targeted video-based extension to boost women’s adoption of key climate-smart technologies; and a myth-busting paper on the 'feminization of agriculture' that digs out kernels of truth.…”
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Women in agriculture: Four myths by Doss, Cheryl, Meinzen-Dick, Ruth S., Quisumbing, Agnes R., Theis, Sophie

“…After reviewing the conceptual and empirical literature, the paper presents the kernel of truth underlying each myth, questions its underlying assumptions and implications, and examines how it hinders us from developing effective food security policies.…”
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Environmental impacts of trypanosomiasis control through land-use change: Conceptual model, approach and preliminary results by Reid, Robin S., Kruska, Russell L., Ellis, J.E., Wilson, C.J., Perry, Brian D.

“…Geographical information systems (GIS) are used to generate hypotheses and to analyse broad-scale patterns, while field studies are used to establish causality and to ground-truth large-scale data sets. Preliminary analyses provide support for the hypothesis that trypanosomiasis is retarding the large-scale correlations show that there is no simple inverse relationship between the presence of tsetse and the presence of agricultural land-use and that tsetse appears to limit agricultural land-use more strongly in southern than in West Africa. …”
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Crop planting structure extraction in irrigated areas from multi-sensor and multi-temporal remote sensing data. In Chinese by Xueliang Cai, Yuanlai Cui

“…Accuracy assessment suggests good agreement with statistical data and 91% classification accuracy when using IKONOS high resolution images as Ground Truth data. The application demonstrates the method a cost-efficient and robust approach to extract crop planting structure at irrigation system scale.…”
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Landsat 5 thematic mapper models of soybean and corn crop characteristics by Thenkabail, Prasad S., Ward, A.D., Lyon, J.

“…This study used Landsat-5 Thematic Mapper (TM) data to develop empirical models for determining soybean and corn crop yield, leaf area index, wet biomass, dry biomass and plant height. Ground-truth data was obtained from more than 50 commercial farms in Ohio, USA, during 1988 and 1989. …”
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Smallholder maize yield estimation using satellite data and machine learning in Ethiopia by Guo, Zhe, Chamberlin, Jordan, You, Liangzhi

“…In this study we described a machine learning approach to estimate smallholder maize yield in Ethiopia, using well-measured and broadly distributed ground truth data and freely available spatiotemporal covariates from remote sensing. …”
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Integrating spatial heterogeneity to enhance spatial temporal crop yield predictions by Msangi, F.M.

“…Over the years remote sensing data and machine learning models have been employed with the help of ground truth data as reference in the estimation of crop yields across space and time. …”
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Agricultural transformation in the savannah: Perspectives from the village by Johnson, Michael E., Houssou, Nazaire, Kolavalli, Shashidhara, Hazell, Peter B. R.

“…This chapter seeks to ground the truth of some of the key findings by providing village and farmer perspectives on important changes that have impacted on their livelihoods since the 1980s, and how they have adapted their farming systems and practices. …”
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A critical approach to co-producing knowledge for development by Nehring, Ryan, Galeana, Fernando, Faxon, Hilary

“…Co-production implies bringing together different knowledges to create something new, acknowledging that knowledge is both plural and partial; there are multiple ways of knowing and no one way represents truth. Yet existing literature on co-production tends to focus mostly on strategies for engagement rather than reckoning with structural forces and practical problems to realizing co-production. …”
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Integrating Earth Observation, Machine Learning and Citizen Science to Map Prosopis juliflora Invasion in Semi-Arid Rangelands of Kenya by Cherotich, Fredah, Galgallo, Diba, Dhulipala, Ram, Whitbread, Anthony M, Paliwal, Ambica

“…It further utilizes ground-truth observations to predict the spread of this invasive species across the region. …”
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Inclusive agricultural insurance for sustainable wheat intensification as a pathway to smallholder resilience in Ethiopia by Ebrahim, Mohammed

“…The model will combine remote sensing, geospatial, and ground-truth agronomic data through machine learning and simulation to enable accurate yield prediction and premium estimation. …”
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Fourier analysis of historical NOAA time series data to estimate bimodal agriculture by Canisius, F., Turral, Hugh, David, S.

“…This result indicates that estimating bimodal agriculture area that is one of the main sources of information for irrigated area mapping at regional or global scale, with improved accuracy possible if greater spatial, temporal resolution is achieved, for instance from MODIS or SPOT vegetation time series NDVI data, combined with (1) an improved decision tree classification algorithm and (2) a greater precision and geographical distribution of ground-truth data. The principle merits of this approach are automation and repeatability.…”
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Improved usefulness of continental soil databases for agricultural management through local adaptation by Söderström, Mats, Piikki, Kristin, Cordingley, Jeremy

“…In tests to improve the continental database locally at the levels examined in this study, regression kriging of SOC and pH from the continental data set with only 100 soil samples was found to reduce errors, and the predictions better resembled those in the ‘ground truth’ data set. The improved map was better for administrative sector averages than point locations and was more pronounced for SOC than for pH. …”
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Building capacities: the next generation of women scientists by Triana Ángel, Natalia, Urrea Benítez, José Luis, Villegas, Daniel Mauricio

“… ● Despite individual and collective efforts to close the gender gap, both in access to educational opportunities and in the labor market, the truth is that women continue to be a minority in the world and scientific praxis…”
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Integrating earth observation, artificial intelligence, and Crop modelling for maize yield estimation in smallholder farming systems in Kenya by Owuor, C.A.

“…Accurate crop yield estimation remains a persistent challenge in smallholder farming systems, particularly in Sub-Saharan Africa, where fragmented fields, diverse cropping practices, and limited ground-truth data hinder the scalability and precision of models. …”
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An evaluation of flood inundation mapping from MODIS and ALOS satellites for Pakistan by Amarnath, Giriraj, Rajah, Ameer

“…A statistical study is performed to analyze false positive and false negative rates using the ALOS sensors as ‘ground truth’. Comparison of two flood products at a grid size of 10 km resulted in the coefficient of determination range of 0.72–0.97. …”
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Qualitative methods for gender research in agricultural development by Rubin, Deborah

“…In a brief discussion of the analysis of qualitative data, the paper notes that informant responses are not “the truth” but need to be assessed against other sources of data. …”
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In-season crop-type mapping in Kenya using Sentinel-2 imagery by Li, Hui, Guo, Zhe, Di, Liping, Guo, Liying, Zhang, Chen, Lin, Li

“…We used surveyed growing crop ground truth data at the end of August 2023 and European Space Agency (ESA) WorldCover data serving as training labels, including nine crop types (Maize, Coffee, Grassland, Tea, Sugarcane, Exotic tree, Legumes, Vegetable, Native tree). …”
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