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2018-08-22Zeitschriftenartikel DOI: 10.18452/19459
From sample to pixel: multi-scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes
dc.contributor.authorPedro J., Leitão
dc.contributor.authorSchwieder, Marcel
dc.contributor.authorPötzschner, Florian
dc.contributor.authorPinto, José R. R.
dc.contributor.authorTeixeira, Ana M. C.
dc.contributor.authorPedroni, Fernando
dc.contributor.authorSanchez, Maryland
dc.contributor.authorRogass, Christian
dc.contributor.authorLinden, Sebastian van der
dc.contributor.authorBustamante, Mercedes M. C.
dc.contributor.authorHostert, Patrick
dc.date.accessioned2018-10-04T12:55:23Z
dc.date.available2018-10-04T12:55:23Z
dc.date.issued2018-08-22
dc.identifier.issn2150-8925
dc.identifier.other10.1002/ecs2.2298
dc.identifier.urihttp://edoc.hu-berlin.de/18452/20229
dc.description.abstractIn times of rapid global change, ecosystem monitoring is of utmost importance. Combined field and remote sensing data enable large‐scale ecosystem assessments, while maintaining local relevance and accuracy. In heterogeneous landscapes, however, the integration of field‐collected data with remote sensing image pixels is not a trivial matter. Indeed, much of the uncertainty in models that use remote sensing to map larger areas lies on the field data integration. In this study, we propose to use fine spatial resolution (5 × 5 m2) remote sensing data as auxiliary data for upscaling field‐sampled aboveground carbon data to target (meso‐scale, i.e., 30 × 30 m2) image pixels. In this process, we assess the effects of field data disaggregation and extrapolation, with and without the auxiliary data. We test this on three study sites in heterogeneous landscapes of the Brazilian savanna. We thus compare two methods that use auxiliary data—surface method, which uses a weighting layer, and regression method, which applies a regression model—with one method without auxiliary data—cartographic method. To evaluate our results, we compared observed vs. estimated aboveground carbon values (for known samples) at the pixel level. Additionally, we fitted a random forest regression model with the assigned carbon estimates and the target satellite imagery and assessed the influence of the fraction of extrapolated vs. sampled carbon values on model performance. We observed that, in heterogeneous landscapes, the use of fine spatial resolution remote sensing data improves the upscaling of field‐based aboveground carbon data to coarser image pixels. We also show that a surface method is more suitable for spatial disaggregation, while a regression approach is preferable for extrapolating non‐sampled pixel fractions. In our study, larger datasets, which included a higher proportion of estimated values, generally delivered better models of aboveground carbon than smaller datasets that are assumed to more reliably reflect reality. Our approach enables to link field and remote sensing data, which in turn enables the detailed mapping of aboveground carbon in heterogeneous landscapes over large areas through the optimized integration of field data and multi‐scale remote sensing data.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 3.0) Attribution 3.0 Unportedger
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.subjectaboveground carboneng
dc.subjectBrazilian savannaeng
dc.subjectcarbon mappingeng
dc.subjectCerradoeng
dc.subjectdata integrationeng
dc.subjectecosystem monitoringeng
dc.subjectHyperioneng
dc.subjecthyperspectraleng
dc.subjecthyperspectraleng
dc.subjectupscalingeng
dc.subject.ddc550 Geowissenschaften
dc.titleFrom sample to pixel: multi-scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/20229-7
dc.identifier.doihttp://dx.doi.org/10.18452/19459
dc.type.versionpublishedVersion
local.edoc.container-titleEcosphere
local.edoc.pages14
local.edoc.anmerkungNachgenutzt gemäß den CC-Bestimmungen des Lizenzgebers bzw. einer im Dokument selbst enthaltenen CC-Lizenz.
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultät
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameEcological Society of America
local.edoc.container-publisher-placeIthaca, NY
local.edoc.container-volume9
local.edoc.container-issue8

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