Mapping foliar N in miombo woodlands using sentinel-2 derived chlorophyll and structural indices

Godfrey Mutowo; Onisimo Mutanga; Mhosisi Masocha

doi:10.1117/1.JRS.12.046028

27 December 2018 Mapping foliar N in miombo woodlands using sentinel-2 derived chlorophyll and structural indices

Godfrey Mutowo, Onisimo Mutanga, Mhosisi Masocha

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 046028 (December 2018). https://doi.org/10.1117/1.JRS.12.046028

Abstract

The remote estimation of foliar nitrogen (N) is key in mapping and monitoring ecosystem health globally. Hyperspectral remote estimation of foliar N has mainly been via its relationship with chlorophyll content. However, the application of broadband remote sensing in foliar N estimation has been receiving increasing attention. The broadband estimation of N provides opportunities for landscape level estimation of N due to the wider spatial coverage. To this end, several studies have tested the potential applications of broadband sensors in estimating N. These were mainly focused on the near-infrared region. Our study was carried out in miombo woodlands, one of the most extensive woodland types in southern Africa. A bootstrapped random forest regression technique, in the R environment, was used for testing for significance in differences in accuracies of chlorophyll and structural indices when estimating foliar N. Our results showed a significant difference between the root mean square error of prediction obtained when chlorophyll indices (mean = 0.52 % ) and structural indices (mean = 0.57 % ) are used for predicting foliar N. We conclude that the chlorophyll indices predict foliar N significantly better than structural indices. This finding is significant in the estimation of foliar N at the landscape level.

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Godfrey Mutowo, Onisimo Mutanga, and Mhosisi Masocha "Mapping foliar N in miombo woodlands using sentinel-2 derived chlorophyll and structural indices," Journal of Applied Remote Sensing 12(4), 046028 (27 December 2018). https://doi.org/10.1117/1.JRS.12.046028

Received: 7 August 2018; Accepted: 4 December 2018; Published: 27 December 2018

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