The purpose of this study is rangeland biomass estimation and its spatial–temporal dynamics. Remote sensing has been a significant method for estimating biomass in recent years. The connection between vegetation index and field biomass will be used to assign probabilities, but in some cases, it does not provide acceptable results because of soil background and geographical and temporal variability.

    Design/methodology/approach

    In this study, the normalized difference red-edge (NDRE) index was used to calculate the rangeland biomass in comparison to five vegetation indices. Field measurements of biomass of natural rangeland in the West of Iran were taken in 2015, 2018 and 2021, and SENTINEL-2 data were used for analysis.

    Findings

    The results indicated that the overall advantage of NDRE stems from the fact that it adjusts for changes in leaf water content while overcoming the detrimental effects of soil substrate heterogeneity, both of these factors have a significant impact on pasture biomass. These results suggest that an NDRE-based biomass estimation model might be useful for estimating and monitoring biomass in large rangelands with significant geographical and temporal variability.

    Originality/value

    Identifying the best vegetation index to establish a vegetation-based biomass regression model for rangelands in large areas with different climatic conditions, plant compositions and soil types is the overall aim of this study.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Remotely sensed normalized difference red-edge index for rangeland biomass estimation


    Contributors:

    Published in:

    Publication date :

    2023-06-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Cotton Yield Estimation Using the Remotely Sensed Cotton Boll Index from UAV Images

    Guanwei Shi / Xin Du / Mingwei Du et al. | DOAJ | 2022

    Free access

    Normalized Difference Vegetation Index for Malaysia

    Kamaruzaman, J. | Online Contents | 2000


    Removing Ambiguities In Remotely Sensed Winds

    Shaffer, Scott J. / Dunbar, Roy S. / Hsiao, Shuchi V. et al. | NTRS | 1991



    Digital processing of remotely sensed images

    Moik, Johannes G. | TIBKAT | 1980