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Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation

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Abstract

Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated in the irrigated wheat and barley fields in the Qazvin irrigation network, Iran. To this end, the leaf area index (LAI) and relative evapotranspiration (ETrel) were extracted from the Landsat data and incorporated into the methods. A comparative analysis was undertaken to evaluate the performance of the satellite-based approaches using percent absolute error (PAE). By updating SWAP with satellite-derived LAI and surface incoming solar radiation, the PAE decreased significantly. Results of different Spectral Indices (SIs) in the RUE method showed that NDVI performed best with PAE of 1.52 percent and RMSE of 664.6 kg ha−1. Also, the RUE method with RMSE of 664.6 kg ha−1 had 4.7 and 23.8 lower PAE compared to the SWAP (RMSE = 2221.4 kg ha−1) and FAO33 (RMSE = 4394.2 kg ha−1), respectively. However, this was not the only criteria for a well-performed method, because earlier AGB forecast was only feasible by making use of SWAP since the satellite-derived parameters were only incorporated into the model about one month before the harvest.

Zusammenfassung

Vergleich von drei auf Satellitenbildern basierten Verfahren zur Abschätzung der oberirdischen Biomasse. Nur die Fernerkundung eignet sich für eine effektive, schnelle und preisgünstige Schätzung der Ernteerträge auf regionaler Ebene. Für die Schätzung der oberirdischen Biomasse (aboveground biomass, AGB) wurden bislang eine ganze Reihe von auf fernerkundlichen Daten basierenden Ansätze vorgeschlagen. In dieser Studie wurden drei dieser Ansätze, und zwar die RUE Methode (radiation use efficiency), das SWAP (Boden Wasser Atmosphäre Pflanze / soil water atmosphere plant) - Modell und die FAO33-Methode anhand von bewässerten Weizen- und Gerstenfeldern in Qazvin, Iran, verglichen und bewertet. Zu diesem Zweck wurden der Blattflächenindex (leaf area index, LAI) und die relative Evapotranspiration (ETrel) aus Landsat-Daten berechnet und in die Methoden integriert. Eine vergleichende Analyse wurde durchgeführt, um die Leistung der satellitengestützten Ansätze unter Verwendung des prozentualen absoluten Fehlers (percent absolute error, PAE) zu bewerten. Durch Verwendung des satellitengestützten LAI und die Berücksichtigung der Sonneneinstrahlung auf der Geländeoberfläche konnte die Genauigkeit des SWAP-Modells verbessert werden, was sich durch die signifikante Abnahme des PAE belegen ließ. Der Vergleich der Signifikanz verschiedener Spektralindizes (SIs) bei der RUE-Methode zeigte, dass der NDVI am besten mit einem PAE von 1,52 Prozent und einem RMSE von 664,6 kg ha−1 abschnitt. Auch die RUE-Methode mit einem RMSE von 664,6 kg ha−1 hatte im Vergleich zum SWAP-Modell (RMSE = 2221,4 kg ha−1) und zur FAO33-Methode (RMSE = 4394,2 kg ha−1) mit 4,7 bzw. 23,8 einen kleineren PAE. Ein weiteres Kriterium für diese gut funktionierende Methode ist die frühere AGB-Prognose, die nur unter Verwendung von SWAP durchführbar war, da die vom Satelliten abgeleiteten Parameter bis etwa einen Monat vor der Ernte in das Modell aufgenommen werden konnten.

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Authors and Affiliations

  1. Department of Irrigation and Reclamation Engineering, College of Agricultural and Natural Resources, University of Tehran, Alborz, Iran

    Ali Mokhtari, Hamideh Noory & Abdullah Balkhi

  2. Department of Civil Engineering, Monash University, 23 College Walk, Clayton, VIC, 3800, Australia

    Sina Alaghmand

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  1. Ali Mokhtari
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  2. Hamideh Noory
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  3. Abdullah Balkhi
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  4. Sina Alaghmand
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Correspondence to Ali Mokhtari.

Appendix

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See Table 8.

Table 8 Soil parameters measured in each plot (P.1–P.8) for wheat and barley
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Mokhtari, A., Noory, H., Balkhi, A. et al. Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation. PFG 89, 33–47 (2021). https://doi.org/10.1007/s41064-020-00134-9

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