Búsqueda
Autor: Kai Sonder
Kai Sonder Guillaume Chomé (2017)
Use of remote sensing based radar images for zero tillage detection in Sinaloa (Municipality of Santiago, El Fuerte and Guasave), Mexico.
Dataset
FAO-SIAC Estimating CA adoption in Guanajuato, Mexico (calibration sites)
Kai Sonder Guillaume Chomé (2017)
Use of remote sensing based radar images for zero tillage detection in Guanajuato, Mexico.
Dataset
Kai Sonder Guillaume Chomé (2018)
Conservation agriculture has been tested and out scaled for over 60 years in rural areas of Mexico, however the rate of adoption and dis adoption, as well as the current area under CA is unknown. Estimates range between 50,000 ha and over 800,000 ha depending on the source. Studies and surveys in several states where CA was propagated in the past show an unclear picture. Tillage and crop residue detection based on remote sensing data has been successfully tested since the mid-1980s and seems a valid technology to essay larger areas or countries with minimal cost based on freely available satellite image sources. A promising approach utilizing radar imagery from Sentinel 1A developed in Belgium for tillage recognition was chosen for the current study. Radar imagery having the advantage of not being affected by clouds or haze. In parallel work being done in the Indo Gangetic Plains as a collaboration between the Université catholique de Louvain and CIMMYT images for areas in the states of Sonora and Sinaloa in Northern Mexico as well as Guanajuato in Central Mexico were acquired from ESA and analyzed. Initial results for Sinaloa show an average accuracy of 94% for predicting tillage type. Current limitations of widespread utilization of the technology include the need for availability of spatial data delineating field boundaries in order to clearly identify cropped and non cropped areas as well as the association of crop management data such as irrigation timings and crop types. Some of this is expected to improve in the near future with big data and crowd sourcing applications for field boundary detection. The results from the associated study in India indicate however that there is good potential to utilize this also in areas with smaller field sizes and utilizing Sentinel 2 data for segmentation of landscapes to substitute detailed field boundary data.
Dataset
FAO-SIAC Estimating CA adoption in Sinaloa, Mexico (calibration sites)
Kai Sonder Guillaume Chomé (2017)
Use of remote sensing based radar images for zero tillage detection in Sinaloa, Mexico.
Dataset
FAO-SIAC Estimating CA adoption in Sinaloa, Mexico (calibration sites)
Kai Sonder Guillaume Chomé (2017)
Use of remote sensing based radar images for zero tillage detection in Sinaloa, Mexico. These were conservation agriculture plots (Zero or reduced tillage)
Dataset
Kai Sonder Santiago Lopez-Ridaura (2024)
Series of thematic maps on biophysical and socioeconomic status of Malawi to guide targeting of agricultural technologies
Dataset
Harvestplus household survey, Zambia 2011, section on storage and climate
Hugo De Groote Zachary Gitonga Kai Sonder (2023)
In this data base, representative georeferenced farmer survey data from Zambia from 2011 are combined with climate data to estimate storage losses, analyze their relationship with climate, and estimate the effect of climate change on storage losses. The storage loss data include importance of different pests (maize weevils and larger grain borer), and farmers’ estimates of storage loss due to both pests, in grain and cobs. The climate data include temperature (from WorldClim) and relative humidity (from CHIRTS) over the storage season in 2011.
Dataset
Threat of wheat blast to South Asia’s food security: An ex-ante analysis
Khondoker Mottaleb Kai Sonder Gideon Kruseman Hans-Joachim Braun (2017)
Impacts of wheat blast disease on food security in South Asia- ex-ante impact study
Dataset
Threat of wheat blast to South Asia’s food security: An ex-ante analysis
Khondoker Mottaleb Kai Sonder Gideon Kruseman Hans-Joachim Braun (2017)
Impacts of wheat blast disease on food security in South Asia- ex-ante impact study
Dataset
Wheat blast: averting wheat blast in India
Khondoker Mottaleb Kai Sonder Gideon Kruseman Olaf Erenstein (2018)
The emergence of wheat-blast disease in Bangladesh in the 2015-16 wheat (Triticum aestivum) crop threatens the food security of South Asia. As wheat is the second most important staple and India has been emerging as a net wheat exporter, a potential spread of the disease from Bangladesh to India could have devastating impacts on India’s overall food security. West Bengal state in eastern India shares a 2,217 km-long border with Bangladesh and has a similar agro-ecology in its nine border districts, enhancing the possibility that disease may enter India via West Bengal. The present study explores the possibility of a ‘wheat holiday’ policy in the nine border districts of West Bengal, India. Under the policy, farmers in these districts would stop wheat cultivation for a few years. The present study attempts to find economically feasible alternative crops to wheat by applying an ex ante assessment framework. Of the ten crops considered, only maize, lentils, gram (chick pea), urad (black gram), khesari (grass pea), rapeseed, mustard and potatoes are found to be feasible alternatives. Such substitution would need support to ease the transition including addressing the challenges related to the management of the alternative crops, ensuring adequate crop combinations and value chain development. Still, as wheat is a major staple, there is some urgency also to support further research on disease epidemiology and forecasting, as well as the development and dissemination of blast-resistant wheat varieties across South Asia
Dataset