Temporal drone phenotyping captures crop development, but irregular flight schedules complicate comparisons across environments. We release curated imagery from 356 flights across 19 Genomes to Fields environments containing 1,180 maize (Zea mays L.) hybrids. To evaluate its utility, we integrated functional principal...
Aaron J. DeSalvio, Peiman Mohseni, Alper Adak et al.· bioRxiv· 1 citation
Spatial variation is a major source of error in agricultural field experiments affecting genotype performance prediction. Implementing statistical models that account for spatial effects can improve the prediction of genotype performance. This study evaluated the impact of the P-spline spatial correction method on the...
T. Setotaw, Christine Nyaga, David J. Waring et al.· PLoS ONE· 0 citations
Recent learning-based damage assessment methods using remote sensing data have greatly contributed to the rapid identification and classification of damaged buildings from pre- and post-disaster imagery. However, most outputs are provided in the form of final damage labels or scores. To address this limitation, this st...
Ahram Song, Jin-Ha Jung, A. Chang et al.· ISPRS International Journal...· 0 citations
Temperature retrieval from unmanned aerial vehicle (UAV) thermal imagery commonly relies on proprietary manufacturer radiometric calibration software. However, the correction procedures used by these workflows are generally undisclosed, and some user-defined parameters, particularly altitude, are restricted to ranges t...
Gaia Cervini, Jin-Ha Jung, Nicholas A. Roberts et al.· Photogrammetric Engineering...· 0 citations
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