Modelling forest road trafficability with satellite-based soil moisture variables

References

• Ågren AM, Lindberg W, Strömgren M, Ogilvie J, Arp PA. 2014. Evaluating digital terrain indices for soil wetness mapping – a Swedish case study. Hydrol Earth Syst Sci. 18(9):3623–3634. doi: 10.5194/hess-18-3623-2014.
   Web of Science ®Google Scholar
• Ambadan JT, MacRae HC, Colliander A, Tetlock E, Helgason W, Gedalof Z, Berg AA. 2022. Evaluation of SMAP Soil Moisture Retrieval Accuracy over a Boreal Forest Region. IEEE Trans Geosci Remote Sens. 60(2022):4414611. doi: 10.1109/TGRS.2022.3212934.
   Google Scholar
• Askne J, Santoro M, Smith G, Fransson JES. 2003. Multitemporal repeat-pass SAR interferometry of boreal forests. IEEE Trans Geosci Remote Sens. 41(7):1540–1550. doi: 10.1109/TGRS.2003.813397.
   Web of Science ®Google Scholar
• Aurstad J, Aksnes J, Berntsen G, Gryteselv D, Johansen R, Lindland T, Ø M, Oset F, Ottesen HB, Paulsrud G, et al. 2016. Textbook for road technology (bd. 626). Norwegian: Vegdirektoratet.
   Google Scholar
• Bauer-Marschallinger B, Freeman V, Cao S, Paulik C, Schaufler S, Stachl T, Modanesi S, Massari C, Ciabatta L, Brocca L. 2019. Toward global soil moisture monitoring with Sentinel-1: harnessing assets and overcoming obstacles. IEEE Trans Geosci Remote Sens. 57(1):520–539. doi: 10.1109/TGRS.2018.2858004.
   Web of Science ®Google Scholar
• Benton AR, Blanchard AJ, Newton RW 1983. Determination of mobility and trafficability indicators with multifrequency imaging radar. Proceedings: SPIE 0414 optical engineering for cold environments; Sept 22; Arlington, USA.
   Google Scholar
• Berg S, Frumerie G, Forshed N. 1991. Terrain classification system for forestry work. Forest Operat Inst Sweden. 1–28.
   Google Scholar
• Bergqvist M, Bradley A, Björheden R, Eliasson L. 2017. Validation of the surfacing thickness program for Swedish conditions. Skogforsk Arbetsrapport No.920-2017. 1–39.
   Google Scholar
• Bergstrand K-G. 1987. Planning and analysis of time studies on forest technology. Forest Operat Inst Sweden. 17:1–58.
   Google Scholar
• Biometria. 2021. Klassning av skogsbilvägar (classification of forest roads). Swedish. (https://www.biometria.se/media/fa1ba4qc/klassning-av-skogsbilvaegar_september2021_webb.pdf).
   Google Scholar
• Bolander P, Marocco D, Kennedy R. 1995. Earth and aggregate surfacing design guide for low volume roads. Washington: USDA Forest Service; p. 302.
   Google Scholar
• Bradley A. 2001 October. Evaluation of forest access road design for use with CTI equipped logging trucks. FERIC Advantage. 2(53):1–16.
   Google Scholar
• Choi KK, Gaul N, Jayakumar P, Wafy TM, Funk M 2018. Framework of reliability-based stochastic mobility map for next generation Nato reference mobility model. Proceedings of the 2018 Ground Vehicle Systems Engineering and Technology Symposium; Aug 7-9; Novi, Michigan. p. 1–15.
   Google Scholar
• Christoffersson P, Johansson S 2012. Rehabilitation of the timmerleden forest road. A ROADEX demonstration report, the Swedish transport administration, Northern Region, Sweden. 38 pp.
   Google Scholar
• Cohen J, Rautiainen K, Lemmetyinen J, Smolander T, Vehviläinen J, Pulliainen J. 2021. Sentinel-1 based soil freeze/thaw estimation in boreal forest environments. Remote Sens Environ. 254:112267. doi: 10.1016/j.rse.2020.112267.
   Web of Science ®Google Scholar
• Colliander A, Reichle RH, Crow WT, Cosh MH, Chen F, Chan S, Das NN, Bindlish R, Chaubell J, Seungbum K, et al. 2022. Validation of soil moisture data products from the NASA SMAP mission. IEEE J Sel Top Appl Earth Observat Remote Sens. 15:364–392. doi: 10.1109/JSTARS.2021.3124743.
   Web of Science ®Google Scholar
• Entekhabi D, Njoku EG, O’Neill PE, Kellogg KH, Crow WT, Edelstein WN, Entin JK, Goodman SD, Jackson TJ, Johnson J, et al. 2010. The Soil Moisture Active Passive (SMAP) mission. Proc IEEE. 98(5):704–716. doi: 10.1109/JPROC.2010.2043918.
   Web of Science ®Google Scholar
• Fjeld D, Bjerketvedt J, Fønhus M 2018. Nye muligheter for klassifisering av bæreevne (New possibilities for classifying bearing capacity). Norsk Skogbruk 4-2018: 45–47. Norwegian.
   Google Scholar
• Fjeld D, Bjerketvedt J, Bråthen M 2021. Forest road availability – inferences from logging truck delivery messages. Proceedings COFE-FORMEC 2021; Sept 27-30; Corvallis, OR. p. 180–183.
   Google Scholar
• Fjeld D, Bjerketvedt J, Bråthen M, 2022. Baereevneklassifisering av skogsbilveier. Resultater av pilotforsöket 2018-2021 (Bearing capacity classification of forest roads – results of a pilot study). NIBIO Report Vol. 8 No. 147: 41 pp. Norwegian.
   Google Scholar
• Flisberg P, Rönnqvist M, Willén E, Frisk M, Friberg G. 2020. Spatial optimization of ground-based primary extraction routes using the BestWay decision support system. Can J For Res. 51(5):675–691. doi: 10.1139/cjfr-2020-0238.
   Google Scholar
• Frankenstein S, Stevens M, Scott C. 2015. Ingestion of simulated SMAP L3 soil moisture data into military maneuver planning. Journal Of Hydrometereol. 16(1):427–440. doi: 10.1175/JHM-D-14-0032.1.
   Web of Science ®Google Scholar
• Holzinger A, Saranti A, Angerschmid A, Retzlaff CO, Gronauer A, Pejakovic V, Medel F, Krexner T, Gollob C, Stampfer K. 2022. Digital Transformation in Smart Farm and forest operations needs human-centered AI: challenges and future directions. Sensors. 22(8):3043. doi: 10.3390/s22083043.
   PubMed Web of Science ®Google Scholar
• IPCC. 2022. Sixth assessment report. Working group 1- the physical science basis. Regional fact sheet Europe. (www.ipcc.ch).
   Google Scholar
• Jevrejeva S, Drabkin VV, Kostjukov J, Lebedev AA, Leppäranta M, Mironov YU, Schmelzer N, Sztobryn M. 2004. Baltic Sea ice seasons in the twentieth century. Clim Res. 25:217–227. doi: 10.3354/cr025217.
   Web of Science ®Google Scholar
• Johannessen KA 2017. Examination of the relationship between soil types, soil moisture and the carrying capacity of roads. Masters thesis NMBU Inst. Natural Resource Management. 51 pp. Norwegian
   Google Scholar
• Kaakkurivaara T, Uusitalo J. 2015. Applicability of portable tools in assessing the bearing capacity of forest roads. Silva Fenn. 49(2):1239. doi: 10.14214/sf.1239.
   Web of Science ®Google Scholar
• Kellomäki S, Maajärvi M, Strandman H, Kilpeläinen A, Peltola H. 2010. Model computations on the climate change effects on snow cover, soil moisture and soil frost in the boreal conditions over Finland. Silva Fenn. 44(2):213–233. doi: 10.14214/sf.455.
   Web of Science ®Google Scholar
• KvarkenSat 2022. Kvarken Space Center – Enabling New Space Economy in Kvarken. www.kvarkenspacecenter.org.
   Google Scholar
• Lenngren CA, Mårtensson B 2003. The falling weight deflectometer – an underestimated tool for managing forest road design and maintenance. Proc. 2nd Forest Engineering Conference; May 12-15; Växjö SkogForsk Arbetsrapport 535. p. 129–138.
   Google Scholar
• Lievens H, Reichle RH, Liu Q, De Lannoy GHM, Dunbar RS, Kim SB, Das NN, Cosh M, Walker JP, Wagner W. 2017. Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates. Geophys Res Lett. 44(12):6145–6153. doi: 10.1002/2017GL073904.
   PubMed Web of Science ®Google Scholar
• LMD. 2013. Normaler for landbruksveier med byggebeskrivelse (Guidelines for agricultural roads with construction descriptions). Landbruks- og matdepartementet. (http://www.skogkurs.no/vegnormaler)
   Google Scholar
• Maagaard JS 2021. Transport lead times – a survey of variation and causes. NMBU masters thesis. Faculty for environmental sciences and natural resource management. Norwegian. 35 pp
   Google Scholar
• McCullough M, Jayakumar P, Dasch J, Gorsich D. 2017. The next generation NATO reference mobility model development. J Terramechanics. 73(2017):49–60. doi: 10.1016/j.jterra.2017.06.002.
   Google Scholar
• MET. 2017. Klima siste 100 år (climate the latest 100 years). Norwegian: Meterologisk Institutt.
   Google Scholar
• Metsäteho 2001. Guideline for forest roads. Metsäteho. Finnish.
   Google Scholar
• Mohseni F, Mirmazloumi SM, Mokhtarzade M, Jamali S, Homayouni S. 2022. Global Evaluation of SMAP/Sentinel-1 Soil Moisture Products. Remote Sens. 14(18):4624. doi: 10.3390/rs14184624.
   Google Scholar
• Murphy PN, Ogilvie J, Arp PA. 2009. Topographic modelling of soil moisture conditions: a comparison and verification of two models. European J Soil Sci. 60(1):94–109. doi: 10.1111/j.1365-2389.2008.01094.x.
   Web of Science ®Google Scholar
• NGU. 2015. Product specification: surface deposits. Oslo: Norwegian Geological Survey. http://www.ngu.no/upload/Aktuelt/DOK_Produktspesifikasjon_Losmasser_ver3.pdf.
   Google Scholar
• O’Neill P, Chan S, Njoku E, Jackson T, Bindlish R, Chaubell J. 2016. SMAP enhanced L3 radiometer global daily 9 km EASE-grid soil moisture, version 1. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center.
   Google Scholar
• Peng J, Albergel C, Balenzano A, Brocca L, Cartus O, Cosh MH, Crow WT, Dabrowska-Zielinska K, Dadson S, Davidson MWJ, et al. 2021. A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements. Remote Sens Environ. 252(2021):112162. doi:10.1016/j.rse.2020.112162.
   Google Scholar
• R Core Team. (2022). R: a language and Environment for Statistical Computing in R Foundation for Statistical Computing. https://www.r-project.org/
   Google Scholar
• Rodríguez-Veiga P, Quegan S, Carreiras J, Persson HJ, Fransson JES, Hoscilo A, Ziółkowski D, Stereńczak K, Lohberger S, Stängel M, et al. 2019. Forest biomass retrieval approaches from earth observation in different biomes. Int J App Earth Observat Geoinformat. 77:53–68. doi: 10.1016/j.jag.2018.12.008.
   Web of Science ®Google Scholar
• Santoro M, Cartus O, Fransson JES, Wegmüller U. 2019. Complementarity of X-, C -, and L-band SAR backscatter observations to retrieve forest stem volume in boreal forest. Remote Sens. 11(13):1–25. doi: 10.3390/rs11131563.
   Google Scholar
• Santoro M, Beaudoin A, Beer C, Cartus O, Fransson JES, Hall RJ, Pathe C, Schmullius C, Schepaschenko D, Shvidenko A, et al. 2015. Forest growing stock volume of the northern hemisphere: spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sens Environ. 168:316–334. doi: 10.1016/j.rse.2015.07.005.
   Web of Science ®Google Scholar
• Santoro M, Cartus O, Fransson JES, Shvidenko A, McCallum I, Hall RJ, Beaudoin A, Beer C, Schmullius C. 2013. Estimates of forest growing stock volume for Sweden, Central Siberia, and Québec using envisat advanced synthetic aperture radar backscatter data. Remote Sens. 5(9):4503–4532. doi: 10.3390/rs5094503.
   Google Scholar
• Schönauer M 2022. The need for more timely estimations of soil moisture – proof of concept. Submission at KvarkenSat Innovation Challenge (https://ultrahack.org).
   Google Scholar
• Schönauer M, Prinz R, Väätäinen K, Astrup R, Pszenny D, Lindeman H, Jaeger D. 2022. Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals. Int J App Earth Observat Geoinformat. 108:102730. doi: 10.1016/j.jag.2022.102730.
   Web of Science ®Google Scholar
• Sjöberg J 2022. Skonsamt från trakt til bilväg (Reduced impact from forest to road). SLU Masters thesis, Dept. of forest biomaterials and technology, Swedish. 2022:22. 67 pp.
   Google Scholar
• Sjölling I, Rönnqvist E, Fjeld D. 2023. Rail transport in Swedish wood supply – seasonal variation, system risks and mitigation costs. Int J For Eng. 34(2):294–302. doi: 10.1080/14942119.2023.2167379.
   Web of Science ®Google Scholar
• Skogsstyrelsen.2011. Anvisningar för projektering och byggandet av skogsbilv’gar klass 3 och 4. 50 pp. Version 2011-01-01. Swedish. www.skogsstyrelsen.se
   Google Scholar
• Sterner K, Edman T, Fjeld D. 2023. Transport management – a Swedish case study of organizational processes and performance. Int J For Eng. p. 1–8. doi: 10.1080/14942119.2023.2202614.
   Google Scholar
• Stevens MT, McKinley GB, Vahedifard F. 2016. A comparison of ground vehicle mobility analysis based on soil moisture time series datasets from WindSat, LIS, and in situ sensors. J Terramechanics. 65(2016):49–59. doi: 10.1016/j.jterra.2016.02.002.
   Google Scholar
• Strandström M 2018. Ongoing work with road bearing capacity and new planning tools in Finland. In: Venaläinen P, and Fjeld D (editors) Cost modelling approaches and latest news from the front. Proceedings from the Nordic-Baltic workshop; Oslo; Sept 11-12; NB-Nord Roads and Transportation Group p. 30–31.
   Google Scholar
• Stridsman A 2006. Quality of road data- an inventory of forest road standards and comparisons with local evaluation and database classification. SLU Masters thesis no. 85 2006 in Forest Technology. Swedish. 31 pp.
   Google Scholar
• Svenson G, Fjeld D. 2016. The impact of road geometry and surface roughness on fuel consumption of logging trucks. Scand J Forest Res. 31(5):526–536. doi: 10.1080/02827581.2015.1092574.
   Web of Science ®Google Scholar
• Tvengsberg H 2016. Measuring carrying capacity of forest roads using light weight deflectometer. NMBU masters thesis. Institute for Natural Resource Management. 40 pp.
   Google Scholar