Publication Abstracts
Yang et al. 2020
Yang, Y., W. Ren, B. Tao, L. Ji, L. Liang, , J.B. Fisher, J. Liu, M. Sama, Z. Li, and Q. Tian, 2020: Characterizing spatiotemporal patterns of crop phenology across North America during 2000-2016 using satellite imagery and agricultural survey data. ISPRS J. Photogramm. Remote Sens., 170, 156-173, doi:10.1016/j.isprsjprs.2020.10.005.
Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology re main unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeo chemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spa tiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000 2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our pre dicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R2, RM SEs, and MAEs in the ranges of 0.35-0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were de layed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = 0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = 0.62, p < 0.01) or a har vest advance by 2.22 days/°C (r = 0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing decision-making adaptation strategies.
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BibTeX Citation
@article{ya04200y,
author={Yang, Y. and Ren, W. and Tao, B. and Ji, L. and Liang, L. and Ruane, A. C. and Fisher, J. B. and Liu, J. and Sama, M. and Li, Z. and Tian, Q.},
title={Characterizing spatiotemporal patterns of crop phenology across North America during 2000-2016 using satellite imagery and agricultural survey data},
year={2020},
journal={ISPRS J. Photogramm. Remote Sens.},
volume={170},
pages={156--173},
doi={10.1016/j.isprsjprs.2020.10.005},
}
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RIS Citation
TY - JOUR ID - ya04200y AU - Yang, Y. AU - Ren, W. AU - Tao, B. AU - Ji, L. AU - Liang, L. AU - Ruane, A. C. AU - Fisher, J. B. AU - Liu, J. AU - Sama, M. AU - Li, Z. AU - Tian, Q. PY - 2020 TI - Characterizing spatiotemporal patterns of crop phenology across North America during 2000-2016 using satellite imagery and agricultural survey data JA - ISPRS J. Photogramm. Remote Sens. VL - 170 SP - 156 EP - 173 DO - 10.1016/j.isprsjprs.2020.10.005 ER -
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