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Combining airborne laser scanning and Landsat data for statistical modeling of soil carbon and tree biomass in Tanzanian Miombo woodlands
Department of Forest Resource Management, Swedish University of Agricultural Sciences.
Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Samhällsvetenskap.
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences.
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences.
Vise andre og tillknytning
2017 (engelsk)Inngår i: Carbon Balance and Management, ISSN 1750-0680, E-ISSN 1750-0680, Vol. 12, nr 1, artikkel-id 8Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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.Landsat 8 Operational Land Imager satellite data and airborne laser scanning datawere evaluated separately and in combination for modeling soil organic carbon, aboveground tree biomass and below ground tree biomass. The test site is situated in theLiwale district in southeastern Tanzania and is dominated by Miombo woodlands. Treedata from 15m radius field-surveyed plots and samples of soil carbon down to a depthof 30cm were used as reference data for tree biomass and soil carbon estimations.Cross-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 Landsat8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results forbelow ground tree biomass were similar to above ground biomass. Additionally it wasfound that an early dry season satellite image was preferable for modelling biomasswhile images from later in the dry season were better for modelling soil carbon.The results show that laser data is superior to Landsat 8 when predicting both soilcarbon and biomass above and below ground in landscapes dominated by Miombowoodlands. Furthermore, the combination of laser data and Landsat data weremarginally better than using laser data only.

sted, utgiver, år, opplag, sider
BioMed Central, 2017. Vol. 12, nr 1, artikkel-id 8
HSV kategori
Forskningsprogram
Nationalekonomi
Identifikatorer
URN: urn:nbn:se:ltu:diva-62858DOI: 10.1186/s13021-017-0076-yPubMedID: 28413852Scopus ID: 2-s2.0-85017550466OAI: oai:DiVA.org:ltu-62858DiVA, id: diva2:1086548
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Validerad; 2017; Nivå 1; 2017-04-24 (andbra)

Tilgjengelig fra: 2017-04-03 Laget: 2017-04-03 Sist oppdatert: 2018-07-10bibliografisk kontrollert

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