Jaeger, Dirk

[["dc.bibliographiccitation.journal","Current Forestry Reports"],["dc.contributor.author","Hoffmann, Stephan"],["dc.contributor.author","Schönauer, Marian"],["dc.contributor.author","Heppelmann, Joachim"],["dc.contributor.author","Asikainen, Antti"],["dc.contributor.author","Cacot, Emmanuel"],["dc.contributor.author","Eberhard, Benno"],["dc.contributor.author","Hasenauer, Hubert"],["dc.contributor.author","Ivanovs, Janis"],["dc.contributor.author","Jaeger, Dirk"],["dc.contributor.author","Lazdins, Andis"],["dc.contributor.author","Astrup, Rasmus"],["dc.date.accessioned","2022-02-01T10:32:01Z"],["dc.date.available","2022-02-01T10:32:01Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract Purpose of Review Mechanized logging operations with ground-based equipment commonly represent European production forestry but are well-known to potentially cause soil impacts through various forms of soil disturbances, especially on wet soils with low bearing capacity. In times of changing climate, with shorter periods of frozen soils, heavy rain fall events in spring and autumn and frequent needs for salvage logging, forestry stakeholders face increasingly unfavourable conditions to conduct low-impact operations. Thus, more than ever, planning tools such as trafficability maps are required to ensure efficient forest operations at reduced environmental impact. This paper aims to describe the status quo of existence and implementation of such tools applied in forest operations across Europe. In addition, focus is given to the availability and accessibility of data relevant for such predictions. Recent Findings A commonly identified method to support the planning and execution of machine-based operations is given by the prediction of areas with low bearing capacity due to wet soil conditions. Both the topographic wetness index (TWI) and the depth-to-water algorithm (DTW) are used to identify wet areas and to produce trafficability maps, based on spatial information. Summary The required input data is commonly available among governmental institutions and in some countries already further processed to have topography-derived trafficability maps and respective enabling technologies at hand. Particularly the Nordic countries are ahead within this process and currently pave the way to further transfer static trafficability maps into dynamic ones, including additional site-specific information received from detailed forest inventories. Yet, it is hoped that a broader adoption of these information by forest managers throughout Europe will take place to enhance sustainable forest operations."],["dc.description.abstract","Abstract Purpose of Review Mechanized logging operations with ground-based equipment commonly represent European production forestry but are well-known to potentially cause soil impacts through various forms of soil disturbances, especially on wet soils with low bearing capacity. In times of changing climate, with shorter periods of frozen soils, heavy rain fall events in spring and autumn and frequent needs for salvage logging, forestry stakeholders face increasingly unfavourable conditions to conduct low-impact operations. Thus, more than ever, planning tools such as trafficability maps are required to ensure efficient forest operations at reduced environmental impact. This paper aims to describe the status quo of existence and implementation of such tools applied in forest operations across Europe. In addition, focus is given to the availability and accessibility of data relevant for such predictions. Recent Findings A commonly identified method to support the planning and execution of machine-based operations is given by the prediction of areas with low bearing capacity due to wet soil conditions. Both the topographic wetness index (TWI) and the depth-to-water algorithm (DTW) are used to identify wet areas and to produce trafficability maps, based on spatial information. Summary The required input data is commonly available among governmental institutions and in some countries already further processed to have topography-derived trafficability maps and respective enabling technologies at hand. Particularly the Nordic countries are ahead within this process and currently pave the way to further transfer static trafficability maps into dynamic ones, including additional site-specific information received from detailed forest inventories. Yet, it is hoped that a broader adoption of these information by forest managers throughout Europe will take place to enhance sustainable forest operations."],["dc.identifier.doi","10.1007/s40725-021-00153-8"],["dc.identifier.pii","153"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/99002"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-517"],["dc.relation.eissn","2198-6436"],["dc.relation.haserratum","/handle/2/99003"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","102614"],["dc.bibliographiccitation.journal","International Journal of Applied Earth Observation and Geoinformation"],["dc.bibliographiccitation.volume","105"],["dc.contributor.author","Schönauer, Marian"],["dc.contributor.author","Väätäinen, Kari"],["dc.contributor.author","Prinz, Robert"],["dc.contributor.author","Lindeman, Harri"],["dc.contributor.author","Pszenny, Dariusz"],["dc.contributor.author","Jansen, Martin"],["dc.contributor.author","Maack, Joachim"],["dc.contributor.author","Talbot, Bruce"],["dc.contributor.author","Astrup, Rasmus"],["dc.contributor.author","Jaeger, Dirk"],["dc.date.accessioned","2022-01-11T14:05:36Z"],["dc.date.available","2022-01-11T14:05:36Z"],["dc.date.issued","2021"],["dc.description.abstract","The utilization of detailed digital terrain models entails an enhanced basis for supporting sustainable forest management, including the reduction of soil impacts through predictions of site trafficability during mechanized harvesting operations. Since wet soils are prone to traffic-induced damages, soil moisture is incorporated into several systems for spatial predictions of trafficability. Yet, only few systems consider temporal dynamics of soil moisture, impeding the accuracy and practical value of predictions. The depth-to-water (DTW) algorithm cal- culates a cartographic index which indicates wet areas. Temporal dynamics of soil moisture are simulated by different DTW map-scenarios derived from set flow initiation areas (FIA). However, the concept of simulating seasonal moisture conditions by DTW map-scenarios was not analyzed so far. Therefore, we conducted field campaigns at six study sites across Europe, capturing time-series of soil moisture and soil strength along several transects which crossed predicted wet areas. Assuming overall dry conditions (FIA = 4.00 ha), DTW predicted 20% of measuring points to be wet. When a FIA of 1.00 ha (moist conditions) or 0.25 ha (wet conditions) were applied, DTW predicted 29% or 58% of points to be wet, respectively. De facto, 82% of moisture measurements were predicted correctly by the map-scenario for overall dry conditions – with 44% of wet measurements deviating from predictions made. The prediction of soil strength was less successful, with 66% of low values occurring on areas where DTW indicated dryer soils and subsequently a sufficient trafficability. The condition- specific usage of different map-scenarios did not improve the accuracy of predictions, as compared to static map- scenarios, chosen for each site. We assume that site-specific and non-linear hydrological processes compromise the generalized assumptions of simulating overall moisture conditions by different FIA"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.1016/j.jag.2021.102614"],["dc.identifier.pii","S0303243421003214"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97700"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.relation.issn","0303-2434"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Spatio-temporal prediction of soil moisture and soil strength by depth-to-water maps"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Current Forestry Reports"],["dc.contributor.author","Hoffmann, Stephan"],["dc.contributor.author","Schönauer, Marian"],["dc.contributor.author","Heppelmann, Joachim"],["dc.contributor.author","Asikainen, Antti"],["dc.contributor.author","Cacot, Emmanuel"],["dc.contributor.author","Eberhard, Benno"],["dc.contributor.author","Hasenauer, Hubert"],["dc.contributor.author","Ivanovs, Janis"],["dc.contributor.author","Jaeger, Dirk"],["dc.contributor.author","Lazdins, Andis"],["dc.contributor.author","Astrup, Rasmus"],["dc.date.accessioned","2022-02-01T10:32:01Z"],["dc.date.available","2022-02-01T10:32:01Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1007/s40725-022-00159-w"],["dc.identifier.pii","159"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/99003"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-517"],["dc.relation.eissn","2198-6436"],["dc.relation.iserratumof","/handle/2/99002"],["dc.rights.uri","https://www.springer.com/tdm"],["dc.title","Correction to: Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","erratum_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","S0303243422000563"],["dc.bibliographiccitation.firstpage","102730"],["dc.bibliographiccitation.journal","International Journal of Applied Earth Observation and Geoinformation"],["dc.bibliographiccitation.volume","108"],["dc.contributor.author","Schönauer, Marian"],["dc.contributor.author","Prinz, Robert"],["dc.contributor.author","Väätäinen, Kari"],["dc.contributor.author","Astrup, Rasmus"],["dc.contributor.author","Pszenny, Dariusz"],["dc.contributor.author","Lindeman, Harri"],["dc.contributor.author","Jaeger, Dirk"],["dc.date.accessioned","2022-05-02T08:09:54Z"],["dc.date.available","2022-05-02T08:09:54Z"],["dc.date.issued","2022"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.1016/j.jag.2022.102730"],["dc.identifier.pii","S0303243422000563"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/107499"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-561"],["dc.relation.issn","1569-8432"],["dc.rights","CC BY-NC-ND 4.0"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]