Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Yanjun Yang, Wei Ren, Bo Tao, Lei Ji, Liang Liang, Alex C. Ruane, Joshua B. Fisher, Jiangui Liu, Michael Sama, Zhe Li, Qingjiu Tian

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

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 remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical 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 spatiotemporal 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 predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R2, RMSEs, 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 delayed 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 harvest 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 adaptation strategies.

Original languageEnglish
Pages (from-to)156-173
Number of pages18
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume170
DOIs
StatePublished - Dec 2020

Bibliographical note

Funding Information:
This work was supported by the National Institute of Food and Agriculture , U.S. Department of Agriculture (NIFA‐USDA Hatch project 2352437000), and NASA Kentucky under NASA award (number NNX15AR69H). The work by L. Ji was performed under USGS Contract 140G0119C0001. Contributions by A.C. Ruane were supported by the NASA Earth Sciences Division support of the NASA GISS Climate Impacts Group. JBF contributed to this research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. JBF was supported in part by NASA IDS, CMS, and INCA programs. We thank Dr. Sanath Sathyachandran for reviewing the manuscript and providing valuable comments. Datasets derived from this study will be made available on the website. The authors declare no conflicts of interest.

Funding Information:
This work was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture (NIFA?USDA Hatch project 2352437000), and NASA Kentucky under NASA award (number NNX15AR69H). The work by L. Ji was performed under USGS Contract 140G0119C0001. Contributions by A.C. Ruane were supported by the NASA Earth Sciences Division support of the NASA GISS Climate Impacts Group. JBF contributed to this research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. JBF was supported in part by NASA IDS, CMS, and INCA programs. We thank Dr. Sanath Sathyachandran for reviewing the manuscript and providing valuable comments. Datasets derived from this study will be made available on the website. The authors declare no conflicts of interest. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Publisher Copyright:
© 2020

Keywords

  • Climate change
  • Crop phenology
  • Cropping intensity
  • EVI-curve-based approach
  • North America
  • Spatiotemporal trend analysis

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences

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