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  • The role of climate in the trend and variability of Ethiopia's cereal crop yields

    Yang, M., Wang, G., Ahmed, K. F., Adugna, B., Eggen, M., Atsbeha, E., You, L., Koo, J. & Anagnostou, E.

    Sci. Total Environ., 2020, 723, 137893.

    DOI:10.1016/j.scitotenv.2020.137893
  • Rapeseed Stand Count Estimation at Leaf Development Stages With UAV Imagery and Convolutional Neural Networks

    Zhang, J., Zhao, B., Yang, C., Shi, Y., Liao, Q., Zhou, G., Wang, C., Xie, T., Jiang, Z., Zhang, D., Yang, W., Huang, C. & Xie, J.

    Front. Plant Sci, 2020, 11, 617.

    DOI:10.3389/fpls.2020.00617
  • Within-Season Producer Response to Warmer Temperatures: Defensive Investments by Kenyan Farmers

    Jagnani, M., Liu, Y., Barret, C. & You, L.

    The Economic Journal, 2020, ueaa063.

    DOI:10.1093/ej/ueaa063
  • Improving potential of nitrogen linked gray water footprint in China's intensive cropping systems

    Zhang, Y., Liu, X., You, L. & Zhang, F.

    Journal of Cleaner Production, 2020, 122307.

    DOI:10.1016/j.jclepro.2020.122307
  • Segmenting Purple Rapeseed Leaves in the Field from UAV RGB Imagery Using Deep Learning as an Auxiliary Means for Nitrogen Stress Detection

    Zhang, J., Xie, T., Yang, C., Song, H., Jiang, Z., Zhou, G., Zhang, D., Feng, H. & Xie, J.

    Remote Sensing, 2020, 12, 1403.

    DOI:10.3390/rs12091403
  • Evaluation of a UAV-mounted consumer grade camera with different spectral modifications and two handheld spectral sensors for rapeseed growth monitoring: performance and influencing factors

    Zhang, J., Wang, C., Yang, C., Jiang, Z., Zhou, G., Wang, B., Shi, Y., Zhang, D., You, L. & Xie, J.

    Precision Agric, 2020.

    DOI:10.1007/s11119-020-09710-w
  • Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring

    Zhang, J., Wang, C., Yang, C., Xie, T., Jiang, Z., Hu, T., Luo, Z., Zhou, G. & Xie, J.

    Remote Sensing, 2020, 12, 1207.

    DOI:10.3390/rs12081207
  • Estimating fractional vegetation cover from leaf area index and clumping index based on the gap probability theory

    Zhao, J., Li, J., Liu, Q., Xu, B., Yu, W., Lin, S. & Hu, Z.

    International Journal of Applied Earth Observation and Geoinformation, 2020, 90, 102112.

    DOI:10.1016/j.jag.2020.102112
  • The Ability of Sun-Induced Chlorophyll Fluorescence From OCO-2 and MODIS-EVI to Monitor Spatial Variations of Soybean and Maize Yields in the Midwestern USA

    Gao, Y., Wang, S., Guan K., Wolanin, A., You, L., Ju, W. & Zhang, Y.

    Remote Sensing, 2020, 12(7), 1111.

    DOI:10.3390/rs12071111
  • Evaluation of Global Decametric-Resolution LAI, FAPAR and FVC Estimates Derived from Sentinel-2 Imagery

    Hu, Q., Yang, J., Xu, B., Huang, J., Memon, S. M., Yin, G., Zeng, Y., Zhao, J. & Liu, K.

    Remote Sensing, 2020, 12, 912-935.

    DOI:10.3390/rs12060912
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