Monitoring the available forage using Sentinel 2-derived NDVI data for sustainable rangeland management


Journal of Arid Environments, vol.200, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 200
  • Publication Date: 2022
  • Doi Number: 10.1016/j.jaridenv.2022.104727
  • Journal Name: Journal of Arid Environments
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, BIOSIS, CAB Abstracts, Communication Abstracts, Environment Index, Geobase, Index Islamicus, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Available forage, Rangeland monitoring, Remote sensing, Seasonal variation, NUTRITIVE-VALUE, NATIONAL-PARK, QUALITY, SEASON, MOUNTAIN, PASTURES, HERBAGE, BIOMASS
  • Eskisehir Osmangazi University Affiliated: Yes


© 2022 Elsevier LtdManagement problems could cause rangeland degradation worldwide. Monitoring the seasonal variation of available forage may help to prevent vegetation from deterioration and help to ensure sustainable animal production. Therefore, seasonal variations in the amounts of available forage, and the contents of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and digestible dry matter (DDM) were monitored for two years via both ground sampling and Sentinel 2A-derived NDVI data at semi-arid Bozdag Rangelands, Turkey. Available forage significantly varied between 374.4 and 936.4 kg ha−1 through the season and all quality parameters showed significant seasonal variations. Available forage was estimated in strong accuracy only in dry season (r2 = 0.72, P ≤ 0.01), but the seasonal variations of CP, ADF, and DDM contents were estimated in moderate accuracy (r2 = 0.56, 0.40, 0.41 respectively) by the satellite-derived NDVI data. Free Sentinel 2A-derived NDVI values gave promising results for monitoring the forage quality of these semi-arid rangelands, but further research is needed to develop new vegetation indexes for considering woody tissues in vegetation, and higher resolution for greater monitoring accuracy.