气候变化领域集成服务门户(CCPortal): Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

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DOI	10.1007/s40725-021-00153-8
	Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry
	Hoffmann, Stephan; Schoenauer, Marian; Heppelmann, Joachim; Asikainen, Antti; Cacot, Emmanuel; Eberhard, Benno; Hasenauer, Hubert; Ivanovs, Janis; Jaeger, Dirk; Lazdins, Andis; Mohtashami, Sima; Moskalik, Tadeusz; Nordfjell, Tomas; Sterenczak, Krzysztof; Talbot, Bruce; Uusitalo, Jori; Vuillermoz, Morgan; Astrup, Rasmus
发表日期	2022
ISSN	2198-6436
起始页码	55
结束页码	71
卷号	8 期号:1
英文摘要	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.
英文关键词	Depth-to-water; Remote sensing; Digital terrain models; European forestry; Precision forestry; Trafficability prediction
语种	英语
WOS研究方向	Forestry
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000740379200001
来源期刊	CURRENT FORESTRY REPORTS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/281089
作者单位	Norwegian Institute of Bioeconomy Research; University of Gottingen; Natural Resources Institute Finland (Luke); University of Natural Resources & Life Sciences, Vienna; Latvian State Forest Research Institute Silava; Skogforsk; Warsaw University of Life Sciences; Swedish University of Agricultural Sciences; Forest Research Institute; Stellenbosch University; University of Helsinki
推荐引用方式 GB/T 7714	Hoffmann, Stephan,Schoenauer, Marian,Heppelmann, Joachim,et al. Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry[J],2022,8(1).
APA	Hoffmann, Stephan.,Schoenauer, Marian.,Heppelmann, Joachim.,Asikainen, Antti.,Cacot, Emmanuel.,...&Astrup, Rasmus.(2022).Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry.CURRENT FORESTRY REPORTS,8(1).
MLA	Hoffmann, Stephan,et al."Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry".CURRENT FORESTRY REPORTS 8.1(2022).