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21 results on '"Karner, Mathias"'

1. A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia

Author

Hadi, Yowargana, Ping, Zulkarnain, Muhammad Thoha, Mohamad, Fathir, Goib, Bunga K., Hultera, Paul, Sturn, Tobias, Karner, Mathias, Dürauer, Martina, See, Linda, Fritz, Steffen, Hendriatna, Adis, Nursafingi, Afi, Melati, Dian Nuraini, Prasetya, F. V. Astrolabe Sian, Carolita, Ita, Kiswanto, Firdaus, Muhammad Iqbal, Rosidi, Muhammad, and Kraxner, Florian

Published
2022
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2. A crowdsourced global data set for validating built-up surface layers

Author

See, Linda, Georgieva, Ivelina, Duerauer, Martina, Kemper, Thomas, Corbane, Christina, Maffenini, Luca, Gallego, Javier, Pesaresi, Martino, Sirbu, Flavius, Ahmed, Rekib, Blyshchyk, Kateryna, Magori, Brigitte, Blyshchyk, Volodymyr, Melnyk, Oleksandr, Zadorozhniuk, Roman, Mandici, Marian-Traian, Su, Yuan-Fong, Rabia, Ahmed Harb, Pérez-Hoyos, Ana, Vasylyshyn, Roman, Pawe, Chandra Kant, Bilous, Svitlana, Kovalevskyi, Serhii B., Kovalevskyi, Sergii S., Bordoloi, Kusumbor, Bilous, Andrii, Panging, Kripal, Bilous, Valentyn, Prestele, Reinhard, Sahariah, Dhrubajyoti, Deka, Anjan, Nath, Nityaranjan, Neves, Rui, Myroniuk, Viktor, Karner, Mathias, and Fritz, Steffen

Published
2022
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3. CraftQuest—Mobile App for Collecting Craft Village Data

Author

Nguyen, Binh Thanh, Gómez-Sanabria, Adriana, Karner, Mathias, Truong, An Ha, Nguyen, Trung Quang, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Satapathy, Suresh Chandra, editor, Bhateja, Vikrant, editor, Nguyen, Bao Le, editor, Nguyen, Nhu Gia, editor, and Le, Dac-Nhuong, editor

Published
2020
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7. AgroTutor: A Mobile Phone Application Supporting Agricultural Sustainable Intensification

Author

Bayas, Juan Carlos Laso, Gardeazabal, Andrea, Karner, Mathias, Folberth, Christian, Vargas, Luis, Skalský, Rastislav, Balkovič, Juraj, Subash, Anto, Saad, Moemen, Delerce, Sylvain, Cuaresma, Jesús Crespo, Hlouskova, Jaroslava, Molina-Maturano, Janet, See, Linda, Fritz, Steffen, Obersteiner, Michael, and Govaerts, Bram

Subjects
life_sciences_other
Abstract

Traditional agricultural extension services rely on extension workers, especially in countries with large agricultural areas. In order to increase adoption of sustainable agriculture, the recommendations given by such services must be adapted to local conditions and be provided in a timely manner. The AgroTutor mobile application was built to provide highly specific and timely agricultural recommendations to farmers across Mexico and complement the work of extension agents. At the same time, AgroTutor provides direct contributions to the United Nations Sustainable Development Goals, either by advancing their implementation or providing local data systems to measure and monitor specific indicators such as the proportion of agricultural area under productive and sustainable agriculture. The application is freely available and allows farmers to geo-locate and register plots and the crops grown there, using the phone’s in-built GPS, or alternatively, on top of very high-resolution imagery. Once a crop and some basic data such as planting date and cultivar type have been registered, the app provides targeted information such as weather, potential and historical yield, financial benchmarking information, data-driven recommendations as well as commodity price forecasts. Farmers are also encouraged to contribute in-situ information, e.g., soils, management, and yield data. The information can then be used by crop models, which, in turn, would send tailored results back to the farmers. Initial feedback from farmers and extension agents has already improved some of the app’s characteristics. More enhancements are planned for inclusion in the future to increase the app’s function as a decision support tool.

Published
2020

8. Experiences from Recent Geo-Wiki Citizen Science Campaigns in the Creation and Sharing of New Reference Data Sets on Land Cover and Land Use 

Author

Laso Bayas, Juan Carlos, primary, See, Linda, additional, Lesiv, Myroslava, additional, Dürauer, Martina, additional, Georgieva, Ivelina, additional, Schepaschenko, Dmitry, additional, Karner, Mathias, additional, Danylo, Olga, additional, Bartl, Hedwig, additional, Subash, Anto, additional, Karanam, Santosh, additional, Sturn, Tobias, additional, McCallum, Ian, additional, and Fritz, Steffen, additional

Published
2021
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10. AgroTutor: A Mobile Phone Application Supporting Sustainable Agricultural Intensification

Author

Laso Bayas, Juan Carlos, primary, Gardeazabal, Andrea, additional, Karner, Mathias, additional, Folberth, Christian, additional, Vargas, Luis, additional, Skalský, Rastislav, additional, Balkovič, Juraj, additional, Subash, Anto, additional, Saad, Moemen, additional, Delerce, Sylvain, additional, Crespo Cuaresma, Jesús, additional, Hlouskova, Jaroslava, additional, Molina-Maturano, Janet, additional, See, Linda, additional, Fritz, Steffen, additional, Obersteiner, Michael, additional, and Govaerts, Bram, additional

Published
2020
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11. Monitoring of land use change by citizens: The FotoQuest experience

Author

Laso Bayas, Juan Carlos, primary, See, Linda, additional, Sturn, Tobias, additional, Karner, Mathias, additional, Fraisl, Dilek, additional, Moorthy, Inian, additional, Subash, Anto, additional, Georgieva, Ivelina, additional, Hager, Gerid, additional, Lesiv, Myroslava, additional, Hadi, Hadi, additional, Danylo, Olha, additional, Karanam, Santosh, additional, Dürauer, Martina, additional, Dahlia, Domian, additional, Shchepashchenko, Dmitry, additional, McCallum, Ian, additional, and Fritz, Steffen, additional

Published
2020
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12. AgroTutor: A Mobile Phone Application Supporting Sustainable Agricultural Intensification

Author

Laso Bayas, Juan Carlos, Gardeazabal, Andrea, Karner, Mathias, Folberth, Christian, Vargas, Luis, Skalský, Rastislav, Balkovič, Juraj, Subash, Anto, Saad, Moemen, Delerce, Sylvain, Crespo Cuaresma, Jesús, Hlouskova, Jaroslava, Molina-Maturano, Janet, See, Linda, Fritz, Steffen, Obersteiner, Michael, Govaerts, Bram, Laso Bayas, Juan Carlos, Gardeazabal, Andrea, Karner, Mathias, Folberth, Christian, Vargas, Luis, Skalský, Rastislav, Balkovič, Juraj, Subash, Anto, Saad, Moemen, Delerce, Sylvain, Crespo Cuaresma, Jesús, Hlouskova, Jaroslava, Molina-Maturano, Janet, See, Linda, Fritz, Steffen, Obersteiner, Michael, and Govaerts, Bram

Abstract

Traditional agricultural extension services rely on extension workers, especially in countries with large agricultural areas. In order to increase adoption of sustainable agriculture, the recommendations given by such services must be adapted to local conditions and be provided in a timely manner. The AgroTutor mobile application was built to provide highly specific and timely agricultural recommendations to farmers across Mexico and complement the work of extension agents. At the same time, AgroTutor provides direct contributions to the United Nations Sustainable Development Goals, either by advancing their implementation or providing local data systems to measure and monitor specific indicators such as the proportion of agricultural area under productive and sustainable agriculture. The application is freely available and allows farmers to geo-locate and register plots and the crops grown there, using the phone’s built-in GPS, or alternatively, on top of very high-resolution imagery. Once a crop and some basic data such as planting date and cultivar type have been registered, the application provides targeted information such as weather, potential and historical yield, financial benchmarking information, data-driven recommendations, and commodity price forecasts. Farmers are also encouraged to contribute in-situ information, e.g., soils, management, and yield data. The information can then be used by crop models, which, in turn, send tailored results back to the farmers. Initial feedback from farmers and extension agents has already improved some of the application’s characteristics. More enhancements are planned for inclusion in the future to increase the application’s function as a decision support tool.

Published
2020
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13. Estimating the global distribution of field size using crowdsourcing

Author

Lesiv, Myroslava, primary, Laso Bayas, Juan Carlos, additional, See, Linda, additional, Duerauer, Martina, additional, Dahlia, Domian, additional, Durando, Neal, additional, Hazarika, Rubul, additional, Kumar Sahariah, Parag, additional, Vakolyuk, Mar'yana, additional, Blyshchyk, Volodymyr, additional, Bilous, Andrii, additional, Perez‐Hoyos, Ana, additional, Gengler, Sarah, additional, Prestele, Reinhard, additional, Bilous, Svitlana, additional, Akhtar, Ibrar ul Hassan, additional, Singha, Kuleswar, additional, Choudhury, Sochin Boro, additional, Chetri, Tilok, additional, Malek, Žiga, additional, Bungnamei, Khangsembou, additional, Saikia, Anup, additional, Sahariah, Dhrubajyoti, additional, Narzary, William, additional, Danylo, Olha, additional, Sturn, Tobias, additional, Karner, Mathias, additional, McCallum, Ian, additional, Schepaschenko, Dmitry, additional, Moltchanova, Elena, additional, Fraisl, Dilek, additional, Moorthy, Inian, additional, and Fritz, Steffen, additional

Published
2018
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15. An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency

Author

Olteanu-Raimond, Ana-Maria, primary, Jolivet, Laurence, additional, Van Damme, Marie-Dominque, additional, Royer, Timothée, additional, Fraval, Ludovic, additional, See, Linda, additional, Sturn, Tobias, additional, Karner, Mathias, additional, Moorthy, Inian, additional, and Fritz, Steffen, additional

Published
2018
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16. A global dataset of crowdsourced land cover and land use reference data

Author

Fritz, Steffen, primary, See, Linda, additional, Perger, Christoph, additional, McCallum, Ian, additional, Schill, Christian, additional, Schepaschenko, Dmitry, additional, Duerauer, Martina, additional, Karner, Mathias, additional, Dresel, Christopher, additional, Laso-Bayas, Juan-Carlos, additional, Lesiv, Myroslava, additional, Moorthy, Inian, additional, Salk, Carl F., additional, Danylo, Olha, additional, Sturn, Tobias, additional, Albrecht, Franziska, additional, You, Liangzhi, additional, Kraxner, Florian, additional, and Obersteiner, Michael, additional

Published
2017
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17. A global dataset of crowdsourced land cover and land use reference data

Author

Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F.; Danylo, Ohla; Sturn, Tobais; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael, http://orcid.org/0000-0001-7930-8814 You, Liangzhi, Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F.; Danylo, Ohla; Sturn, Tobais; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael, and http://orcid.org/0000-0001-7930-8814 You, Liangzhi

Abstract

PR, IFPRI3; ISI, EPTD

Published
2017
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20. Estimating the global distribution of field size using crowdsourcing

Author

Lesiv, Myroslava, Laso Bayas, Juan Carlos, See, Linda, Duerauer, Martina, Dahlia, Domian, Durando, Neal, Hazarika, Rubul, Kumar Sahariah, Parag, Vakolyuk, Mar'yana, Blyshchyk, Volodymyr, Bilous, Andrii, Perez‐Hoyos, Ana, Gengler, Sarah, Prestele, Reinhard, Bilous, Svitlana, Akhtar, Ibrar Ul Hassan, Singha, Kuleswar, Choudhury, Sochin Boro, Chetri, Tilok, Malek, Žiga, Bungnamei, Khangsembou, Saikia, Anup, Sahariah, Dhrubajyoti, Narzary, William, Danylo, Olha, Sturn, Tobias, Karner, Mathias, McCallum, Ian, Schepaschenko, Dmitry, Moltchanova, Elena, Fraisl, Dilek, Moorthy, Inian, and Fritz, Steffen

Subjects
2. Zero hunger

21. Estimating the global distribution of field size using crowdsourcing.

Author

Lesiv M, Laso Bayas JC, See L, Duerauer M, Dahlia D, Durando N, Hazarika R, Kumar Sahariah P, Vakolyuk M, Blyshchyk V, Bilous A, Perez-Hoyos A, Gengler S, Prestele R, Bilous S, Akhtar IUH, Singha K, Choudhury SB, Chetri T, Malek Ž, Bungnamei K, Saikia A, Sahariah D, Narzary W, Danylo O, Sturn T, Karner M, McCallum I, Schepaschenko D, Moltchanova E, Fraisl D, Moorthy I, and Fritz S

Subjects
Agriculture, Crowdsourcing statistics & numerical data, Farms, Satellite Imagery
Abstract

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture., (© 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

Published
2019
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