Modelling and validation of agricultural and forest biomass potentials for Germany and Austria

The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Tum, Markus [verfasserIn]
Hochschulschrift:	Göttingen, Univ., Diss., 2012

Format:	E-Book
Sprache:	Englisch

Erschienen:	2012

Schlagwörter:	Bioenergie / Agrarboden / Bodennutzungsintensität / Agrarproduktion / Deutschland / Österreich
Formangabe:	Hochschulschrift

Anmerkung:	Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation
Umfang:	Online-Ressource (PDF-Datei: 205 S., 42.153 KB) ; Ill., graph. Darst.
Beschreibung:	Systemvoraussetzungen: Acrobat Reader.

Weitere Ausgabe:	Erscheint auch als Druck-Ausgabe Tum, Markus: Modelling and validation of agricultural and forest biomass potentials for Germany and Austria - 2012

Links:	Link aufrufen Volltext Volltext Volltext Volltext

DOI / URN:	urn:nbn:de:gbv:7-webdoc-3597-0

Katalog-ID:	732483638

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title_auth	Modelling and validation of agricultural and forest biomass potentials for Germany and Austria
abstract	The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation
abstractGer	The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation
abstract_unstemmed	The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation
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allfields	13,O12 dnb 1043997784 DE-101 urn:nbn:de:gbv:7-webdoc-3597-0 urn (DE-627)732483638 (DE-576)9732483636 (DE-599)GBV732483638 (OCoLC)863899828 DE-627 ger DE-627 rakwb eng XA-DE-NI 330 DNB 550 38.03 bkl 38.60 bkl 48.30 bkl 48.40 bkl Tum, Markus verfasserin aut Modelling and validation of agricultural and forest biomass potentials for Germany and Austria vorgelegt von Markus Tum 2012 Online-Ressource (PDF-Datei: 205 S., 42.153 KB) Ill., graph. Darst. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation Göttingen, Univ., Diss., 2012 The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Systemvoraussetzungen: Acrobat Reader. Langzeitarchivierung gewährleistet pdager 1.1\x Bioenergie (DE-627)091352177 (DE-2867)14171-3 stw 1.2\x Agrarboden (DE-627)091345871 (DE-2867)19339-1 stw 1.3\x Bodennutzungsintensität (DE-627)09135238X (DE-2867)18328-4 stw 1.4\x Agrarproduktion (DE-627)091346029 (DE-2867)18980-6 stw 1.5\x Deutschland (DE-627)091354749 (DE-2867)18012-3 stw 1.6\x Österreich (DE-627)091381975 (DE-2867)16950-4 stw Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Göttingen uvp Erscheint auch als Druck-Ausgabe Tum, Markus Modelling and validation of agricultural and forest biomass potentials for Germany and Austria 2012 197 S. (DE-627)732406579 http://resolver.sub.uni-goettingen.de/purl/?webdoc-3597 text/html Verlag kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 text/html Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 2013-12-04 Resolving-System Volltext http://d-nb.info/1043997784/34 2013-12-04 Langzeitarchivierung Nationalbibliothek Volltext GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP SSG-OPC-FOR SSG-OPC-GGO GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_26 ISIL_DE-206 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_65 ISIL_DE-3 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_213 ISIL_DE-551 GBV_ILN_230 ISIL_DE-552 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2403 ISIL_DE-LFER 38.03 Methoden und Techniken der Geowissenschaften (DE-627)106411284 38.60 Bodenkunde: Allgemeines Geowissenschaften (DE-627)106406760 48.30 Natürliche Ressourcen Land- und Forstwirtschaft (DE-627)106409077 48.40 Forstwirtschaft (DE-627)106416006 BO 20 01 0084 1461954363 x 08-03-14 21 01 0046 1462020178 z 08-03-14 22 01 0018 1462085849 SUBolrd xu 08-03-14 23 01 0830 1462142419 olr-d x 08-03-14 26 01 0206 1454956569 08 K: VSM --%%-- --%%-- z1k 28-01-14 30 01 0104 1462169252 z 08-03-14 40 01 0007 1347261273 09.07.2012 11:43:24 ksn 18-12-12 60 01 0705 1462250963 OLRD z 08-03-14 63 01 3401 1595797521 ORD x 21-01-16 65 01 0003 4166364499 GBV-ODiss Open Access z 14-07-22 70 01 0089 1462339859 zdo 08-03-14 105 01 0841 1596610166 z 21-01-16 110 01 3110 146230964X x 08-03-14 132 01 0959 1498437087 OLR-DISS x 14-08-14 151 01 0546 3594210731 OLR-ODISS z 13-02-20 161 01 0960 1462366473 ORD x 08-03-14 213 01 0551 1462385834 ORD x 08-03-14 230 01 0552 1462438105 ORD x 08-03-14 293 01 3293 1598077856 ORD xf 28-01-16 370 01 4370 1788110692 x 26-07-18 2403 01 DE-LFER 3494976538 00 --%%-- --%%-- n --%%-- l01 18-07-19 20 01 0084 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 21 01 0046 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 22 01 0018 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 23 01 0830 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 30 01 0104 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 40 01 0007 http://resolver.sub.uni-goettingen.de/purl/?webdoc-3597 LF 40 01 0007 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 LF 60 01 0705 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 LF 65 01 0003 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 70 01 0089 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 105 01 0841 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 110 01 3110 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 132 01 0959 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 161 01 0960 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 213 01 0551 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 230 01 0552 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 293 01 3293 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 370 01 4370 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 26 00 DE-206 56 Agriculture 26 00 DE-206 56 Austria 26 00 DE-206 56 Bio-energy 26 00 DE-206 56 Biomass 26 00 DE-206 56 Forest 26 00 DE-206 56 Germany 26 00 DE-206 56 Model 26 00 DE-206 56 Remote Sensing 26 00 DE-206 56 Soil water budged 26 00 DE-206 56 validation 40 00 DE-7 00 (DE-627)621264997 QDK 000 Vegetationsgeographie 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 40 01 0007 09.07.2012 11:43:24 60 01 0705 OLRD 63 01 3401 ORD 65 01 0003 GBV-ODiss 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 213 01 0551 ORD 230 01 0552 ORD 293 01 3293 ORD 23 01 0830 2014-03-08:22:45:49
spelling	13,O12 dnb 1043997784 DE-101 urn:nbn:de:gbv:7-webdoc-3597-0 urn (DE-627)732483638 (DE-576)9732483636 (DE-599)GBV732483638 (OCoLC)863899828 DE-627 ger DE-627 rakwb eng XA-DE-NI 330 DNB 550 38.03 bkl 38.60 bkl 48.30 bkl 48.40 bkl Tum, Markus verfasserin aut Modelling and validation of agricultural and forest biomass potentials for Germany and Austria vorgelegt von Markus Tum 2012 Online-Ressource (PDF-Datei: 205 S., 42.153 KB) Ill., graph. Darst. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation Göttingen, Univ., Diss., 2012 The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Systemvoraussetzungen: Acrobat Reader. Langzeitarchivierung gewährleistet pdager 1.1\x Bioenergie (DE-627)091352177 (DE-2867)14171-3 stw 1.2\x Agrarboden (DE-627)091345871 (DE-2867)19339-1 stw 1.3\x Bodennutzungsintensität (DE-627)09135238X (DE-2867)18328-4 stw 1.4\x Agrarproduktion (DE-627)091346029 (DE-2867)18980-6 stw 1.5\x Deutschland (DE-627)091354749 (DE-2867)18012-3 stw 1.6\x Österreich (DE-627)091381975 (DE-2867)16950-4 stw Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Göttingen uvp Erscheint auch als Druck-Ausgabe Tum, Markus Modelling and validation of agricultural and forest biomass potentials for Germany and Austria 2012 197 S. (DE-627)732406579 http://resolver.sub.uni-goettingen.de/purl/?webdoc-3597 text/html Verlag kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 text/html Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 2013-12-04 Resolving-System Volltext http://d-nb.info/1043997784/34 2013-12-04 Langzeitarchivierung Nationalbibliothek Volltext GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP SSG-OPC-FOR SSG-OPC-GGO GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_26 ISIL_DE-206 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_65 ISIL_DE-3 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_213 ISIL_DE-551 GBV_ILN_230 ISIL_DE-552 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2403 ISIL_DE-LFER 38.03 Methoden und Techniken der Geowissenschaften (DE-627)106411284 38.60 Bodenkunde: Allgemeines Geowissenschaften (DE-627)106406760 48.30 Natürliche Ressourcen Land- und Forstwirtschaft (DE-627)106409077 48.40 Forstwirtschaft (DE-627)106416006 BO 20 01 0084 1461954363 x 08-03-14 21 01 0046 1462020178 z 08-03-14 22 01 0018 1462085849 SUBolrd xu 08-03-14 23 01 0830 1462142419 olr-d x 08-03-14 26 01 0206 1454956569 08 K: VSM --%%-- --%%-- z1k 28-01-14 30 01 0104 1462169252 z 08-03-14 40 01 0007 1347261273 09.07.2012 11:43:24 ksn 18-12-12 60 01 0705 1462250963 OLRD z 08-03-14 63 01 3401 1595797521 ORD x 21-01-16 65 01 0003 4166364499 GBV-ODiss Open Access z 14-07-22 70 01 0089 1462339859 zdo 08-03-14 105 01 0841 1596610166 z 21-01-16 110 01 3110 146230964X x 08-03-14 132 01 0959 1498437087 OLR-DISS x 14-08-14 151 01 0546 3594210731 OLR-ODISS z 13-02-20 161 01 0960 1462366473 ORD x 08-03-14 213 01 0551 1462385834 ORD x 08-03-14 230 01 0552 1462438105 ORD x 08-03-14 293 01 3293 1598077856 ORD xf 28-01-16 370 01 4370 1788110692 x 26-07-18 2403 01 DE-LFER 3494976538 00 --%%-- --%%-- n --%%-- l01 18-07-19 20 01 0084 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 21 01 0046 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 22 01 0018 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 23 01 0830 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 30 01 0104 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 40 01 0007 http://resolver.sub.uni-goettingen.de/purl/?webdoc-3597 LF 40 01 0007 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 LF 60 01 0705 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 LF 65 01 0003 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 70 01 0089 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 105 01 0841 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 110 01 3110 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 132 01 0959 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 161 01 0960 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 213 01 0551 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 230 01 0552 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 293 01 3293 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 370 01 4370 http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:7-webdoc-3597-0 26 00 DE-206 56 Agriculture 26 00 DE-206 56 Austria 26 00 DE-206 56 Bio-energy 26 00 DE-206 56 Biomass 26 00 DE-206 56 Forest 26 00 DE-206 56 Germany 26 00 DE-206 56 Model 26 00 DE-206 56 Remote Sensing 26 00 DE-206 56 Soil water budged 26 00 DE-206 56 validation 40 00 DE-7 00 (DE-627)621264997 QDK 000 Vegetationsgeographie 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 40 01 0007 09.07.2012 11:43:24 60 01 0705 OLRD 63 01 3401 ORD 65 01 0003 GBV-ODiss 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 213 01 0551 ORD 230 01 0552 ORD 293 01 3293 ORD 23 01 0830 2014-03-08:22:45:49
allfields_unstemmed	13,O12 dnb 1043997784 DE-101 urn:nbn:de:gbv:7-webdoc-3597-0 urn (DE-627)732483638 (DE-576)9732483636 (DE-599)GBV732483638 (OCoLC)863899828 DE-627 ger DE-627 rakwb eng XA-DE-NI 330 DNB 550 38.03 bkl 38.60 bkl 48.30 bkl 48.40 bkl Tum, Markus verfasserin aut Modelling and validation of agricultural and forest biomass potentials for Germany and Austria vorgelegt von Markus Tum 2012 Online-Ressource (PDF-Datei: 205 S., 42.153 KB) Ill., graph. Darst. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation Göttingen, Univ., Diss., 2012 The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Systemvoraussetzungen: Acrobat Reader. Langzeitarchivierung gewährleistet pdager 1.1\x Bioenergie (DE-627)091352177 (DE-2867)14171-3 stw 1.2\x Agrarboden (DE-627)091345871 (DE-2867)19339-1 stw 1.3\x Bodennutzungsintensität (DE-627)09135238X (DE-2867)18328-4 stw 1.4\x Agrarproduktion (DE-627)091346029 (DE-2867)18980-6 stw 1.5\x Deutschland (DE-627)091354749 (DE-2867)18012-3 stw 1.6\x Österreich (DE-627)091381975 (DE-2867)16950-4 stw Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Göttingen uvp Erscheint auch als Druck-Ausgabe Tum, Markus Modelling and validation of agricultural and forest biomass potentials for Germany and Austria 2012 197 S. 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allfieldsGer	13,O12 dnb 1043997784 DE-101 urn:nbn:de:gbv:7-webdoc-3597-0 urn (DE-627)732483638 (DE-576)9732483636 (DE-599)GBV732483638 (OCoLC)863899828 DE-627 ger DE-627 rakwb eng XA-DE-NI 330 DNB 550 38.03 bkl 38.60 bkl 48.30 bkl 48.40 bkl Tum, Markus verfasserin aut Modelling and validation of agricultural and forest biomass potentials for Germany and Austria vorgelegt von Markus Tum 2012 Online-Ressource (PDF-Datei: 205 S., 42.153 KB) Ill., graph. Darst. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation Göttingen, Univ., Diss., 2012 The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Systemvoraussetzungen: Acrobat Reader. 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allfieldsSound	13,O12 dnb 1043997784 DE-101 urn:nbn:de:gbv:7-webdoc-3597-0 urn (DE-627)732483638 (DE-576)9732483636 (DE-599)GBV732483638 (OCoLC)863899828 DE-627 ger DE-627 rakwb eng XA-DE-NI 330 DNB 550 38.03 bkl 38.60 bkl 48.30 bkl 48.40 bkl Tum, Markus verfasserin aut Modelling and validation of agricultural and forest biomass potentials for Germany and Austria vorgelegt von Markus Tum 2012 Online-Ressource (PDF-Datei: 205 S., 42.153 KB) Ill., graph. Darst. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation Göttingen, Univ., Diss., 2012 The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. Finally the carbon content of dry matter is estimated ... Systemvoraussetzungen: Acrobat Reader. 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authorswithroles_txt_mv	Tum, Markus @@aut@@
genre_facet	Hochschulschrift
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000cam a2200265 4500</leader><controlfield tag="001">732483638</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240716202219.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">121218s2012 gw \|\|\|\|\|om 00\| \|\|eng c</controlfield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">13,O12</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">1043997784</subfield><subfield code="2">DE-101</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">urn:nbn:de:gbv:7-webdoc-3597-0</subfield><subfield code="2">urn</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)732483638</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-576)9732483636</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBV732483638</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)863899828</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="c">XA-DE-NI</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">330</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">38.03</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">38.60</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">48.30</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">48.40</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Tum, Markus</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Modelling and validation of agricultural and forest biomass potentials for Germany and Austria</subfield><subfield code="c">vorgelegt von Markus Tum</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource (PDF-Datei: 205 S., 42.153 KB)</subfield><subfield code="b">Ill., graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Besteht aus teilweise bereits publizierten, teilweise bisher nur eingereichten Aufsätzen. Kumulative Dissertation</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="a">Göttingen, Univ., Diss., 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The Biosphere Energy Transfer Hydrology Model (BETHY/DLR), a process model that estimates the net primary productivity of agricultural and forested areas was used to assess biomass potentials for Germany and Austria. The model is driven by remote sensing data and meteorological data. Remotely sensed datasets including a time series of the leaf area index, which describes vegetation condition, and a land cover classification, which provides information about land use, are needed. Leaf area indices and land cover data derived from the sensor VEGETATION are used. Both datasets have spatial resolutions of about 1km x 1km and are freely available for the area of investigation. The meteorological input parameters are air temperature (at 2m height), precipitation, cloud cover, wind speed (at 10m height) and soil water content (inthe four uppermost soil layers); these are obtained from the European Centre for Medium-Range Weather Forecasts, with a spatial resolution of about 0.25ʿ x 0.25ʿ and a temporal resolution up to four times daily. The output of the model, the gross primary productivity, is calculated at daily resolution. By subtracting the cumulative plant maintenance and growth respiration, the net primary productivity is then determined. In order to validate the modelled net primary productivity, crop yield estimates and mean above ground biomass increases derived from the national statistics of Germany and Austria are used. After estimating above-ground biomass using plant-specific above- to below-ground ratios, conversion factors (corn-to-straw and leaf-to-beet relations) are applied to estimate total biomass. 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title_short	Modelling and validation of agricultural and forest biomass potentials for Germany and Austria
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Modelling and validation of agricultural and forest biomass potentials for Germany and Austria

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