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Blockchain Technology for Agriculture: Applications and Rationale
Xiong, H., Dalhaus, T., Wang, P., & Huang, J.
Frontiers in Blockchain, 2020, 3, 7.
DOI:10.3389/fbloc.2020.00007
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Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt
Wolanin, A., Mateo-García, G., Camps-Valls, G., Gómez-Chova, L., Meroni, M., Duveiller, G., You, L. & Guanter, L.
Environmental Research Letters, 2020, 15(2), 24019.
DOI:10.1088/1748-9326/ab68ac
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Improving leaf area index retrieval over heterogeneous surface mixed with water
Xu, B., Li, J., Park, T., Liu, Q., Zeng, Y., Yin, G., Yan, K., Chen, C., Zhao, J., Fan, W., Knyazikhin, Y. & Myneni, R. B.
Remote Sensing of Environment, 2020, 240, 111700.
DOI:10.1016/j.rse.2020.111700
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A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory
Zeng, Y., Li, J., Liu, Q., Huete, A. R., Xu, B., Yin, G., Fan, W., Ouyang, Y., Yan, K., Hao, D. & Chen, M.
IEEE Transaction on Geoscience and Remote Sensing, 2019, 58, 2571-2589.
DOI:10.1109/TGRS.2019.2952377
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区块链技术在食品安全管理中的应用研究
汪普庆，瞿翔，熊航和汪志广
农业技术经济, 2019, (09), 82-90.
DOI:10.13246/j.cnki.jae.2019.09.008
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Assimilating Soil Moisture Retrieved from Sentinel-1and Sentinel-2 Data into WOFOST Model to Improve Winter Wheat Yield Estimation
Zhuo, W., Huang, J., Li, L., Zhang, X., Ma, H., Gao, X., Huang, H., Xu, B. & Xiao, X.
Remote Sensing, 2019, 11, 1618.
DOI:10.3390/rs11131618
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Synchronous crop failures and climate-forced production variability
Anderson, W. B., Seager, R., Baethgen, W., Cane, M. & You, L.
Science Advances, Vol. 5, no. 7, eaaw1976.
DOI:10.1126/sciadv.aaw1976
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A phenology-based spectral and temporal feature selection method for crop mapping from satellite time series
Hu, Q., Sulla-Menashe, D., Xu, B., Yin, H., Tang, H., Yang, P. & Wu, W.
International Journal of Applied Earth Observation and Geoinformation, 2019, 80:218-229.
DOI:10.1016/j.jag.2019.04.014
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Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
Cai, Y., Guan, K., Lobell, D., Andries, P., Wang, S., Peng, J., Xu, T., Asseng, S., Zhang, Y., You, L. & Peng, B.
Agricultural and Forest Meteorology, 2019, 274, 144-159.
DOI:10.1016/j.agrformet.2019.03.010
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Design and rating of risk- contingent credit for balancing business and financial risks for Kenyan farmers
Shee, A., Turvey, C. G. & You, L.
Applied Economics, 2019, 51(50), 5447-5465.
DOI: 10.1080/00036846.2019.1613502
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Rice production and climate change in Northeast China: evidence of adaptation through land use shifts
Hu, Y., Fan, L., Liu, Z., Yu, Q., Liang, S., Chen, S., You, L., Wu, W. & Peng, Y.
Environmental Research Letters, 2019, 14, 024014.
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China and India lead in greening of the world through land-use management
Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturvedi, R. K., Fuchs, R., Brovkin, V., Ciais, P., Fensholt, R., Tømmervik, H., Bala, G., Zhu, Z., Nemani, R. R. & Myneni, R. B.
Nature Sustainability, Volume 2, 122–129.
DOI:10.1038/s41893-019-0220-7
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A comparison of global agricultural monitoring systems and current gaps
Fritz, S., See, L., Bayas, J. C. L., Waldner, F., Jacques, D., Becker-Reshef, I., Whitcraft, A., Baruth, B., Bonifacio, R., Crutchfield, J., Rembold, F., Rojas, O., Schucknecht, A., Van der Velde, M., Verdin, J., Wu, B., Yan, N., You, L., Gilliams, S., Mücher, S., Tetrault, R., Moorthy, I. & McCallum, I.
Agricultural Systems, 2019, 168, 258-272.
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Remoteness, urbanization, and child nutrition in sub-Saharan Africa. Agricultural Economics
Headey, D., Stifel, D., You, L. & Guo, Z.
Agricultural Economics, 2018, 49, 765-775.
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Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth's Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations
Wanjuan Song, Yuri Knyazikhin, Guoyong Wen, Alexander Marshak, Matti Mõttus, Kai Yan, Bin Yang, Baodong Xu, Taejin Park, Chi Chen, Yelu Zeng, Guangjian Yan, Xihan Mu, & B. Ranga Myneni
Remote Sensing, 10, 1594-1616.
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Representation of decision-making in European agricultural agent-based models
Robert Huber, Martha Bakker, Alfons Balmann, Thomas Berger, Mike Bithell, Calum Brown, Adr-ienne Grêt-Regamey, Hang Xiong et.al
Agricultural Systems,Volume 167, 2018, Pages 143-160, ISSN 0308-521X.
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Rapeseed Seedling Stand Counting and Seeding Performance Evaluation at Two Early Growth Stages Based on Unmanned Aerial Vehicle Imagery
Zhao, B., Zhang, J., Yang, C., Zhou, G., Ding, Y., Shi, Y., Zhang, D., Xie, J. & Liao, Q.
Front. Plant Sci, 2018, 9:1362.
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Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations
Zeng, Y., Xu, B., Yin, G., Wu, S., Hu, G., Yan, K., Yang, B., Song, W. & Li, J.
Remote Sensing, 2018, 10, 1508-1524.
DOI:10.3390/rs10101508
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Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations
Yelu Zeng, Baodong Xu, Gaofei Yin, Shengbiao Wu, Guoqing Hu, Kai Yan, Bin Yang, Wanjuan Song, & Jing Li
Remote Sensing, 10, 1508-1524.
DOI:10.3390/rs10101508
Language：
中文
