Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat 8

TL;DR

This study demonstrates that freely available satellite imagery, especially Sentinel-2, significantly enhances the accuracy of forest biomass change estimates over five years in Norway, compared to traditional field-based methods.

Contribution

It introduces a model-assisted estimation approach combining national forest inventory data with Sentinel-2 and Landsat imagery for improved biomass change assessment.

Findings

Remotely sensed data improved estimate precision up to threefold.

Bi-temporal Sentinel-2 data yielded the most precise biomass change estimates.

Accurate Delta AGB estimation is possible with remote sensing data even at the end of monitoring periods.

Abstract

This study aimed at estimating total forest above-ground net change (Delta AGB, Mt) over five years (2014-2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a boreal forest area (approx. 1.4 Mill hectares) in Norway where bi-temporal national forest inventory (NFI), Sentinel-2, and Landsat data were available. Biomass change was modelled based on a direct approach. The precision of estimates using only the NFI data in a basic expansion estimator were compared to four different alternative model-assisted estimates using 1) Sentinel-2 or Landsat data, and 2) using bi- or uni-temporal remotely sensed data. We found that the use of remotely sensed data improved the precision of the purely field-based estimates by a factor of up to three. The most precise estimates were found for the model-assisted estimation using bi-temporal Sentinel-2 (standard error; SE= 1.7 Mt). However, the decrease in precision when using Landsat data was small (SE= 1.92 Mt). In addition, we found that Delta AGB could be precisely estimated also when remotely sensed data were available only at the end of the monitoring period. We conclude that satellite optical data can considerably improve Delta AGB estimates, even in those cases where repeated and coincident NFI data are available. The free availability, global coverage, frequent update, and long-term time horizon make data from programs such as Sentinel-2 and Landsat a valuable data source for a consistent and durable monitoring of forest carbon dynamics.