Citizen science supporting agricultural monitoring with hundreds of low-cost sensors in comparison to remote sensing data

Chiara Corbari (Lead / Corresponding author), N. Paciolla, I. Ben Charfi, D. Skokovic, J. A. Sobrino, M. Woods

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
57 Downloads (Pure)


The ever-increasing importance of irrigation monitoring and water-use optimization in agriculture calls for new solutions for a more complete understanding of the plant growth dynamic and the agricultural water cycle. In this study, the fitness for use of the Flower Power low-cost sensors, not designed for scientific applications, is evaluated in an integrated agricultural monitoring context in contrast to freely available satellite information from Landsat 8, Sentinel 1 and 2. Measurements of air temperature, solar radiation, leaf area index (LAI) and soil moisture are considered. 456 sensors have been deployed in the Capitanata Irrigation Consortium (Italy) as part of the GROW Observatory project with local farmers collaborating as citizen scientists to either deploy these sensors, monitor the environmental variables and control irrigation management. The main results are: (i) positive agreement between Flower Power sensors and high-quality professional stations for measurements of meteorological variables (5.6°C RMSE for Air Temperature); (ii) acceptable estimates of crops LAI (RMSE = 0.55 m2 m−2) and mixed ones of Surface Soil Moisture (m = 0.75, R2 = 0.23) from Flower Power sensors in respect to different satellite data; (iii) potentiality of these sensors combined with remote sensing in providing suitable tools for irrigation management.

Original languageEnglish
Pages (from-to)388-408
Number of pages21
JournalEuropean Journal of Remote Sensing
Issue number1
Early online date13 Jun 2022
Publication statusE-pub ahead of print - 13 Jun 2022


  • citizen science
  • irrigation water needs
  • low-cost sensors
  • Multiple remote sensing data
  • soil moisture

ASJC Scopus subject areas

  • General Environmental Science
  • Computers in Earth Sciences
  • Atmospheric Science
  • Applied Mathematics


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