المؤلفون: Eatidal Amin, Luca Pipia, Santiago Belda, Gregor Perich, Lukas Valentin Graf, Helge Aasen, Shari Van Wittenberghe, José Moreno, Jochem Verrelst

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103636- (2024)

مصطلحات موضوعية: Sentinel-2, Crop yield forecasting, Machine learning, Gaussian process regression (GPR), Time series gap-filling, Growing degree days (GDD), Physical geography, GB3-5030, Environmental sciences, GE1-350

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S1569843223004600Test; https://doaj.org/toc/1569-8432Test

الوصول الحر: https://doaj.org/article/a8bb85440b7f41fb9a8aa795e47f6f54Test

المؤلفون: Amin, Eatidal, Pipia, Luca, Belda, Santiago, Perich, Gregor, id_orcid:0 000-0002-5093-5352, Graf, Lukas Valentin, id_orcid:0 000-0003-4800-8258, Aasen, Helge, Van Wittenberghe, Shari, Moreno, José, Verrelst, Jochem

المصدر: International Journal of Applied Earth Observation and Geoinformation, 126

مصطلحات موضوعية: Sentinel-2, Crop yield forecasting, Machine learning, Gaussian process regression (GPR), Time series gap-filling, Growing degree days (GDD)

وصف الملف: application/application/pdf

العلاقة: info:eu-repo/semantics/altIdentifier/wos/001149913600001; info:eu-repo/grantAgreement/SNF/COST/198091; http://hdl.handle.net/20.500.11850/658091Test

الإتاحة: https://doi.org/20.500.11850/658091Test
https://doi.org/10.3929/ethz-b-000658091Test
https://doi.org/10.1016/j.jag.2023.103636Test
https://hdl.handle.net/20.500.11850/658091Test

المؤلفون: Zeeshan Ramzan, H. M. Shahzad Asif, Irfan Yousuf, Muhammad Shahbaz

المصدر: IEEE Access, Vol 11, Pp 42578-42594 (2023)

مصطلحات موضوعية: Multimodal, data fusion, deep neural networks, crop yield forecasting tea yield, Pakistan, satellite imagery, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

العلاقة: https://ieeexplore.ieee.org/document/10110955Test/; https://doaj.org/toc/2169-3536Test

الوصول الحر: https://doaj.org/article/0766b021dcc048bd8f6af45fe8f7c697Test

المؤلفون: Amin, Eatidal, Pipia, Luca, Belda, Santiago, Perich, Gregor, Graf, Lukas Valentin, Aasen, Helge, Van Wittenberghe, Shari, Moreno, José, Verrelst, Jochem

المساهمون: Universidad de Alicante. Departamento de Matemática Aplicada

مصطلحات موضوعية: Sentinel-2, Crop yield forecasting, Machine learning, Gaussian process regression (GPR), Time series gap-filling, Growing degree days (GDD)

العلاقة: https://doi.org/10.1016/j.jag.2023.103636Test; info:eu-repo/grantAgreement/EC/H2020/755617; International Journal of Applied Earth Observation and Geoinformation. 2024, 126: 103636. https://doi.org/10.1016/j.jag.2023.103636Test; 1569-8432 (Print); 1872-826X (Online); http://hdl.handle.net/10045/139501Test

الإتاحة: https://doi.org/10.1016/j.jag.2023.103636Test
http://hdl.handle.net/10045/139501Test

المؤلفون: Jabloun, Mohamed, Udugbezi, Emmanuel, Rivington, Mike

مصطلحات موضوعية: Crop yield forecasting, Earth Observations, Scotland, OurSmartFarm

العلاقة: https://zenodo.org/record/8146670Test; https://doi.org/10.5281/zenodo.8146670Test; oai:zenodo.org:8146670

الإتاحة: https://doi.org/10.5281/zenodo.8146670Test
https://doi.org/10.5281/zenodo.8146669Test
https://zenodo.org/record/8146670Test

المؤلفون: Subhadra Mishra, Debahuti Mishra, Gour Hari Santra

المصدر: Journal of King Saud University: Computer and Information Sciences, Vol 32, Iss 8, Pp 949-964 (2020)

مصطلحات موضوعية: AdaBoost, Linear regression, Lasso regression, ridge regression, SVR linear regression, SVR polynomial regression, SVR RBF regression, Crop yield forecasting, Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S1319157817301726Test; https://doaj.org/toc/1319-1578Test

الوصول الحر: https://doaj.org/article/f5c070de649e41bd9eac874117c05a14Test

المؤلفون: Paudel, Dilli, Boogaard, Hendrik, de Wit, Allard, van der Velde, Marijn, Claverie, Martin, Nisini, Luigi, Janssen, Sander, Osinga, Sjoukje, Athanasiadis, Ioannis N.

المصدر: Field Crops Research 276 (2022) ; ISSN: 0378-4290

مصطلحات موضوعية: Crop yield, Large-scale crop yield forecasting, Machine learning, Regional differences, Scalability

وصف الملف: application/pdf

العلاقة: https://edepot.wur.nl/559918Test; https://research.wur.nl/en/publications/machine-learning-for-regionalTest-crop-yield-forecasting-in-europe

الإتاحة: https://doi.org/10.1016/j.fcr.2021.108377Test
https://research.wur.nl/en/publications/machine-learning-for-regionalTest-crop-yield-forecasting-in-europe

المؤلفون: M.Saranya Dr (14247557)

مصطلحات موضوعية: Data mining and knowledge discovery, Crop yield prediction, Machine learning, Modularity, Reusability, Large-scale crop yield forecasting

العلاقة: https://figshare.com/articles/journal_contribution/Crop_yield_prediction_using_deep_learning/21711620Test

الإتاحة: https://doi.org/10.6084/m9.figshare.21711620.v1Test

المؤلفون: Qimeng Pan, Lysa Porth, Hong Li

المصدر: Sustainability; Volume 14; Issue 11; Pages: 6916

مصطلحات موضوعية: actuarial climate index, crop yield forecasting, agricultural insurance, high-resolution data, probit model

جغرافية الموضوع: agris

وصف الملف: application/pdf

العلاقة: Economic and Business Aspects of Sustainability; https://dx.doi.org/10.3390/su14116916Test

الإتاحة: https://doi.org/10.3390/su14116916Test

المؤلفون: Gommes, René, Das, Haripada, Mariani, Luigi, Challinor, Andrew, Tychon, Bernard, Balaghi, Riad, Dawod, Mohamed A.A.

المصدر: Chapter 6 : Agrometeorological forecasting. In WMO/CAgM Guide to Agricultural Meteorological Practices (GAMP) WMO n° 134. (2010).

مصطلحات موضوعية: Agrometerology, forecasting, crop yield forecasting, Life sciences :: Environmental sciences & ecology, Sciences du vivant :: Sciences de l'environnement & écologie, Life sciences :: Agriculture & agronomy, Sciences du vivant :: Agriculture & agronomie

الوصول الحر: https://orbi.uliege.be/handle/2268/94113Test