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Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+

Overview of attention for article published in Carbon Balance and Management, June 2015
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Title
Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+
Published in
Carbon Balance and Management, June 2015
DOI 10.1186/s13021-015-0023-8
Pubmed ID
Authors

Svein Solberg, Belachew Gizachew, Erik Næsset, Terje Gobakken, Ole Martin Bollandsås, Ernest William Mauya, Håkan Olsson, Rogers Malimbwi, Eliakimu Zahabu

Abstract

REDD+ implementation requires establishment of a system for measuring, reporting and verification (MRV) of forest carbon changes. A challenge for MRV is the lack of satellite based methods that can track not only deforestation, but also degradation and forest growth, as well as a lack of historical data that can serve as a basis for a reference emission level. Working in a miombo woodland in Tanzania, we here aim at demonstrating a novel 3D satellite approach based on interferometric processing of radar imagery (InSAR). Forest carbon changes are derived from changes in the forest canopy height obtained from InSAR, i.e. decreases represent carbon loss from logging and increases represent carbon sequestration through forest growth. We fitted a model of above-ground biomass (AGB) against InSAR height, and used this to convert height changes to biomass and carbon changes. The relationship between AGB and InSAR height was weak, as the individual plots were widely scattered around the model fit. However, we consider the approach to be unique and feasible for large-scale MRV efforts in REDD+ because the low accuracy was attributable partly to small plots and other limitations in the data set, and partly to a random pixel-to-pixel variation in trunk forms. Further processing of the InSAR data provides data on the categories of forest change. The combination of InSAR data from the Shuttle RADAR Topography Mission (SRTM) and the TanDEM-X satellite mission provided both historic baseline of change for the period 2000-2011, as well as annual change 2011-2012. A 3D data set from InSAR is a promising tool for MRV in REDD+. The temporal changes seen by InSAR data corresponded well with, but largely supplemented, the changes derived from Landsat data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 77 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 21%
Student > Master 12 15%
Student > Ph. D. Student 9 12%
Student > Bachelor 7 9%
Other 7 9%
Other 11 14%
Unknown 16 21%
Readers by discipline Count As %
Environmental Science 25 32%
Earth and Planetary Sciences 13 17%
Agricultural and Biological Sciences 10 13%
Engineering 4 5%
Computer Science 3 4%
Other 4 5%
Unknown 19 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 June 2015.
All research outputs
#14,689,232
of 22,813,792 outputs
Outputs from Carbon Balance and Management
#165
of 236 outputs
Outputs of similar age
#143,266
of 264,477 outputs
Outputs of similar age from Carbon Balance and Management
#6
of 8 outputs
Altmetric has tracked 22,813,792 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 236 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,477 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.