Abstract
BackgroundSoil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations.ResultsCross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon.ConclusionThe results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.
Highlights
Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas
The Miombo woodlands of Tanzania are under pressure for several reasons, among them a general population increase which brings a need for subsistence agriculture as well as small scale charcoal production [1, 2]
There is a large number of criteria used for defining Miombo degradation [6] of which the United Nations Framework Convention on Climate Change (UNFCCC) definition is related to loss of carbon stock during a certain time period [7]
Summary
Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Soil organic carbon (SOC) is an important part of the soil ecosystem; the disturbance of natural forests in tropical areas, as well as the conversion of forests and woodlands to agricultural land is known to generally reduce SOC [8,9,10,11,12]. Land degradation is a continuous process and it is of interest to investigate to what degree remote sensing in combination with field plot data can be an aid for following this process over time [13]
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