Spatial prediction of soil classes using digital terrain analysis and multinomial logistic regression modeling integrated in GIS: Examples from Vestfold County, Norway

Debella-Gilo, Misganu; Etzelmüller, Bernd

doi:10.1016/j.catena.2008.12.001

Cited by 91 publications

(47 citation statements)

References 14 publications

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“…Blanket peat tends to form on impermeable rocks or thick layers of glacial till on shallow slopes (typically <10°, although slopes up to 25°have been noted) where saturated conditions are allowed to develop because of impeded and/or slow drainage (Taylor 1983). In other wetland areas, topography has been used to map the distribution of saturated areas in topographic hollows and floodplains (Creed et al 2008, Debella-Gilo & Etzelmüller 2009). However, blanket peat tends not to be confined to hollows or footslopes and is often found on hill-top plateaus (Taylor 1983).…”

Section: Limitationsmentioning

confidence: 99%

Assessing the vulnerability of blanket peat to climate change using an ensemble of statistical bioclimatic envelope models

et al. 2010

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ABSTRACT:We assessed the vulnerability of blanket peat to climate change in Great Britain using an ensemble of 8 bioclimatic envelope models. We used 4 published models that ranged from simple threshold models, based on total annual precipitation, to Generalised Linear Models (GLMs, based on mean annual temperature). In addition, 4 new models were developed which included measures of water deficit as threshold, classification tree, GLM and generalised additive models (GAM). Models that included measures of both hydrological conditions and maximum temperature provided a better fit to the mapped peat area than models based on hydrological variables alone. Under UKCIP02 projections for high (A1F1) and low (B1) greenhouse gas emission scenarios, 7 out of the 8 models showed a decline in the bioclimatic space associated with blanket peat. Eastern regions (Northumbria, North York Moors, Orkney) were shown to be more vulnerable than higher-altitude, western areas (Highlands, Western Isles and Argyle, Bute and The Trossachs). These results suggest a long-term decline in the distribution of actively growing blanket peat, especially under the high emissions scenario, although it is emphasised that existing peatlands may well persist for decades under a changing climate. Observational data from long-term monitoring and manipulation experiments in combination with process-based models are required to explore the nature and magnitude of climate change impacts on these vulnerable areas more fully.

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Section: Limitationsmentioning

confidence: 99%

Assessing the vulnerability of blanket peat to climate change using an ensemble of statistical bioclimatic envelope models

et al. 2010

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“…Folglich sollten die so ermittelten Indexwerte nur als relative Rangfolge und über zusammengefasste Variablengruppen interpretiert werden. BEHRENS et al 2010, GIASSON et al 2008, DEBELLA-GILO u. ETZELMÜLLER 2009, ILLES et al 2011, CRUZ-CARDENAS et al 2011. Bei der Disaggregierung komplexer Legendeneinheiten der bayrischen Übersichtsbodenkarte ermittelten auch HÄRING et al (2012) für β, ΔzC und TWI einen großen Einfluss in den entwickelten Klassifikationsbäumen.…”

Section: Materials Und Methodenunclassified

Gefährdungen der Ökosystemdienstleistungen von Wäldern

Versuchsanstalt¹

2016

Beiträge Aus Der Nordwestdeutschen Forstlichen Versuchsanstalt

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Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliographie; detaillierte bibliographische Daten sind im Internet über abrufbar.Global Forest Decimal Classification: 1. 1, 422.2, 114, 116 Herausgeber der Reihe: Nordwestdeutsche Forstliche Versuchsanstalt (NW-FVA) Grätzelstr. 2, D-37079 Göttingen Tel.: +49 (0)551-69401-0, Fax: +49 (0) ZusammenfassungIn Sachsen-Anhalt liegen flächenhafte Bodeninformationen in Form der vorläufigen Bodenkarte im Maßstab 1 : 50.000 (VBK50) und der räumlich höher aufgelösten forstlichen Standortskarte vor. Der Standortskarte können bodenphysikalische Parameter aus den Merkmalsspiegeln der forstlichen Lokalbodenformen (KOPP et al., unveröffentlicht, KOPP u. JOCHHEIM 2002, SCHWANECKE 1993, SCHULZE 1998 zugeordnet werden. Die Evaluierung dieser räumlich vorliegenden Bodeninformationen wurde anhand von punktuell vorliegenden Bodeninformationen der zweiten Bodenzustandserhebung im Wald (BZE II), der Bodendauerbeobachtungsflächen (BDF) und der Ökologischen Waldzustandskontrolle (ÖWK) in SachsenAnhalt durchgeführt.Der Vergleich zwischen den Bodeninformationen dieser forstlichen Umweltmessnetze mit der Standortskartierung ergab eine genauere und verzerrungsfreiere Schätzung der bodenphysikalischen Parameter als die Schätzung der vorläufigen Bodenkarte. Sand-(R² = 0,85), Schluff-(R² = 0,81) und Tongehalte (R² = 0,52) der Bodenprofile der forstlichen Umweltmessnetze wurden durch die flächenhaften Daten der Merkmalsspiegel gut wiedergegeben. Deutlich geringere Überein-stimmungen ergeben sich für den Skelettgehalt (R 2 = 0,44), sowie für die aus den Grundlagendaten ermittelten Kenngrößen, wie nutzbare Feldkapazität (R 2 = 0,23) und potenzielle Kationenaustauschkapazität (R 2 = 0,33). Insbesondere bei der Abschätzung der nutzbaren Feldkapazität bestehen erhebliche Unsicherheiten, die vornehmlich auf die unsichere Schätzung der Skelettgehalte zurückzuführen sind.Stichworte: Regionalisierung, bodenphysikalische Eigenschaften, Unsicherheitsbetrachtungen, nutzbare Feldkapazität, Verwitterungsoberfläche, Waldböden AbstractSpatial soil information in Saxony-Anhalt is available in the form of the preliminary 1 : 50000 soil map (VBK50) and the higher resolution forest site map. From the forest site map the soil physical parameters can be determined using characteristic soil profiles (KOPP et al., unpublished, KOPP and JOCHHEIM 2002, SCHWANECKE 1993, SCHULZE 1998). The quality of this available spatial soil information was evaluated using punctual soil information from the second national soil inventory (BZE II), the long-term soil monitoring network (BDF) and the ecological forest monitoring network (ÖWK) in Saxony-Anhalt.The comparison of the soil information from these forest monitoring networks with the characteristic soil profiles from the forest site map revealed a more exact, distortion-free estimation of the soil physical parameters than the comparison with the preliminary soil map. The sand (R² = 0.85), silt (R² = 0.81) and clay co...

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“…The multinomial logistic regression was used to evaluate multicolinearity (Debella-Gilo & Etzelmüller, 2009, Kempen et al, 2009). …”

Section: Pre-processing Of the Topographic Propertiesmentioning

confidence: 99%

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

Cruz-Cárdenas

Solorio

Trejo

et al. 2011

Rev. Bras. Ciênc. Solo

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SUMMARYMap units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.Index terms: decision tree, digital elevation model, map quality.(1) Received for publication in March 2010 and approved in January 2011.

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Spatial prediction of soil classes using digital terrain analysis and multinomial logistic regression modeling integrated in GIS: Examples from Vestfold County, Norway

Cited by 91 publications

References 14 publications

Assessing the vulnerability of blanket peat to climate change using an ensemble of statistical bioclimatic envelope models

Assessing the vulnerability of blanket peat to climate change using an ensemble of statistical bioclimatic envelope models

Gefährdungen der Ökosystemdienstleistungen von Wäldern

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

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