Estimation of biomass potential based on classification and height information

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dc.identifier.uri http://dx.doi.org/10.15488/977
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/1001
dc.contributor.author Müller, S.
dc.contributor.author Büscher, O.
dc.contributor.author Jandewerth, M.
dc.date.accessioned 2016-12-22T10:06:46Z
dc.date.available 2016-12-22T10:06:46Z
dc.date.issued 2013
dc.identifier.citation Müller, S.; Büscher, O.; Jandewerth, M.: Estimation of biomass potential based on classification and height information. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 (2013), Nr. 1W1, S. 263-268. DOI:
dc.description.abstract On the way to make energy supply independent from fossil resources more and more renewable energy sources have to be explored. Biomass has become an important energy resource during the last years and the consumption is rising steadily. Common sources of biomass are agricultural production and forestry but the production of these sources is stagnating due to limited space. To explore new sources of biomass like in the field of landscape conservation the location and available amount of biomass is unknown. Normally, there are no reliable data sources to give information about the objects of interest such as hedges, vegetation along streets, railways and rivers, field margins and ruderal sites. There is a great demand for an inventory of these biomass sources which could be answered by applying remote sensing technology. As biomass objects considered here are sometimes only a few meters wide, spectral unmixing is applied to separate different material mixtures reflected in one image pixel. The spectral images are assumed to have a spatial resolution of 5-20m with multispectral or hyperspectral band configurations. Combining the identified material part fractions with height information and GIS data afterwards will give estimates about the location of biomass objects. The method is applied to test data of a Sentinel-2 simulation and the results are evaluated visually. eng
dc.description.sponsorship Federal Ministry of Economics and Technology (BMWi)
dc.description.sponsorship DLR/50EE1212
dc.description.sponsorship DLR/50EE1213
dc.description.sponsorship DLR/50EE1214
dc.language.iso eng
dc.publisher Hannover : International Society for Photogrammetry and Remote Sensing
dc.relation.ispartof ISPRS Hannover Workshop 2013, 21-24 May 2013, Hannover, Germany
dc.relation.ispartofseries International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 (2013)
dc.rights CC BY 3.0
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Dem eng
dc.subject Extraction eng
dc.subject Monitoring eng
dc.subject Resources eng
dc.subject Satellite eng
dc.subject Spatial infrastructures eng
dc.subject Sustainable eng
dc.subject Agriculture eng
dc.subject Classification (of information) eng
dc.subject Data visualization eng
dc.subject Energy resources eng
dc.subject Remote sensing eng
dc.subject Renewable energy resources eng
dc.subject Satellites eng
dc.subject Spectroscopy eng
dc.subject Agricultural productions eng
dc.subject Landscape conservation eng
dc.subject Remote sensing technology eng
dc.subject Renewable energy source eng
dc.subject Resources eng
dc.subject Spatial infrastructures eng
dc.subject Sustainable eng
dc.subject Biomass eng
dc.subject.ddc 000 | Informatik, Informationswissenschaft, allgemeine Werke ger
dc.subject.ddc 550 | Geowissenschaften ger
dc.title Estimation of biomass potential based on classification and height information
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 16821750
dc.bibliographicCitation.issue 1W1
dc.bibliographicCitation.volume 40
dc.bibliographicCitation.firstPage 263
dc.bibliographicCitation.lastPage 268
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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