A within-season approach for detecting early growth stages in corn and soybean using high temporal and spatial resolution imagery

Feng Gao, Martha Anderson, Craig Daughtry, Arnon Karnieli, Dean Hively, William Kustas

Research output: Contribution to journalArticlepeer-review

74 Scopus citations

Abstract

Crop emergence date is a critical input to models of crop development and biomass accumulation. The ability to robustly detect and map emergence date using remote sensing would greatly benefit operational yield estimation and crop monitoring efforts; however, this has proven to be challenging. Previous remote-sensing phenology algorithms showed that crop stages can typically be detected starting only around the V3-V4 (3 to 4 established leaves) vegetative stage. Furthermore, traditional approaches have a strong assumption regarding the temporal evolution of plant growth and normally require a complete growth period of observations to define seasonal changes. Most approaches were not designed for within-season operational mapping, particularly in the early growing season. In the current paper, we describe a new within-season emergence (WISE) approach to mapping crop green-up date using satellite observations available during early growth stages. The approach was first optimized using high spatiotemporal resolution (10 m, 2-day revisit) imagery from the Vegetation and Environment monitoring New MicroSatellite (VENμS) research mission, and assessed using ground observations of early crop growth stages (emergence VE and one leaf V1 stages for corn, and emergence VE and unifoliolate VC stages for soybeans) collected over the Beltsville Agricultural Research Center (BARC) experimental fields in Beltsville, MD during the 2019 growing season. Results show that early crop growth stages can be reliably detected at sub-field scale about two weeks after crop emergence. The remote-sensing green-up dates were about 4–5 days after crop emergence on average. Coefficients of determination (R2) between green-up dates and the mid-point dates of the early growth stages were above 0.90. The mean absolute differences, standard deviations, and root mean square errors comparing to the early growth stage mid-point dates were within six days. The maximum differences were within ±10 days across all fields. The WISE approach was assessed using operational Sentinel-2 data (10 m, 5-day revisit) over BARC. The detected green-up dates from Sentinel-2 were consistent with those from VENμS. Some fields were not detected due to the lack of observations around the emergence dates. For independent evaluation, the WISE approach was applied over an agricultural watershed on the Maryland Eastern Shore using both VENμS and the Harmonized Landsat and Sentinel-2 (HLS) data (30 m, 3–4-day revisit). The detected green-up dates were compared with emergence dates in crop progress reports from the National Agricultural Statistics Service (NASS) at the state-level. The WISE-detected green-up dates at the regional scale are within VE stage ranges but slightly earlier than NASS crop progress reports at the state-level. The WISE approach uses remote-sensing observations during the early crop growth stages and has potential for operational application within the season using Sentinel-2 and HLS data.

Original languageEnglish
Article number111752
JournalRemote Sensing of Environment
Volume242
DOIs
StatePublished - 1 Jun 2020

Keywords

  • Crop emergence
  • Crop growth stages
  • Crop progress
  • Harmonized Landsat and Sentinel-2
  • Landsat
  • Remote-sensing phenology
  • Sentinel-2
  • Time-series analysis
  • VENμS

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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