Spatio-temporal prediction of soil moisture and soil strength by depth-to-water maps

Schönauer, Marian; Väätäinen, Kari; Prinz, Robert; Lindeman, Harri; Pszenny, Dariusz; Jansen, Martin; Maack, Joachim; Talbot, Bruce; Astrup, Rasmus; Jaeger, Dirk

doi:10.1016/j.jag.2021.102614

Cited by 10 publications

(11 citation statements)

References 46 publications

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“…There, only DTMs with a grid cell size of 5 m, 10 m or 200 m, respectively, are made openly accessible according to the INSPIRE programme [64]. Although the application of the DTW algorithm is generally robust to DTMs of different size [54], best results are achieved with DTM resolutions not exceeding 5-10 m, and ideally be even less than 5 m [92]. Thus, DTW modelling is technically also possible on DTMs with a low resolution of e.g.…”

Section: Discussionmentioning

confidence: 99%

“…Besides technical and administrative challenges, a fullrange implementation of DTW-based trafficability maps would require a dynamic approach, accounting for seasonal variation of soil moisture [92,97,98]. Research activities currently address this issue, for example by sequential combination of DTW maps and additional, freely accessible weather data.…”

Section: Discussionmentioning

confidence: 99%

“…This led to a recently conducted dynamic approach, integrating information about topography, soil and vegetation [99], used for trafficability prediction on pilot sites in Finland, creating suitable outputs with a grid cell size of 16 m [46••]. Including real-time weather forecasts in the trafficability models would further enhance prediction quality at a dynamic level [92,97,98].…”

Section: Discussionmentioning

confidence: 99%

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Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

et al. 2022

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“…Overall, a prediction accuracy of 85% was achieved in modeling soil vulnerability to rutting in study II. More recently, the DTW index in particular has been widely applied in terrain trafficability predictions (Hoffmann 2022), andSchönauer et al (2021) have presented promising results of spatio-temporal soil moisture and soil strength predictions using this index. All the earlier studies could be improved using the findings of study III, as the overland flow routing and the derivative wetness indices were better modeled using the high-resolution LiDAR data.…”

Section: Mapping Within-stand Soil Wetness Variationmentioning

confidence: 99%

Producing information from airborne LiDAR data for peatland forest management

Niemi¹

2022

Diss. For.

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In Finland, peatland forests are significant for wood supply, although simultaneously, they are also important for biodiversity, carbon sequestration, water conservation, and recreation. In the 1960s and 1970s, peatland forests in Finland were extensively drained to increase tree growth and fulfil the needs of the forest sector. However, this extensive drainage has negatively impacted on the biodiversity of peatland ecosystems, and substantially increased nutrient and sediment emissions to lakes and rivers resulting in eutrophication, turbidity, and brownification of these water bodies. This dissertation presents a number of approaches to move peatland forest management in a more environmentally sound direction, which may increase the general acceptability of peatland forestry. Airborne LiDAR (Light detection and ranging, i.e., laser scanning) derived 3D point cloud provides useful data, for example, to estimate forest biomass, to identify low-productive peatland forests, to model overland water flows, and to identify wet areas. The strength of airborne LiDAR is the ability of laser pulses to pass through tree canopies and obtain accurate observations from the ground level. The information derived from airborne LiDAR can enhance the planning of peatland forest management, as much of the planning can be done remotely, and supplementary field work can be implemented in areas of strategic need. This study presented the novel idea of applying local binary patterns for the prediction of terrain trafficability, which should be considered in further studies and practice. The moisture index derived from the local neighborhood can reveal the small-scale variations in terrain moisture. This study also presented the novel idea to create spatial models to identify suitable locations for water protection structures, which may help forest managers to plan water protection of ditch network maintenance or peatland restoration operations. Overall, the utilization of airborne LiDAR-derived information for the development of peatland forestry practices shows great potential.

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“…DTW maps have been applied and tested in a Boreal climate for the prediction of perennial streams, wet or water-saturated areas, and sensitive areas for ground-based trafficking [25][26][27][28]. These instruments are well-established in the Boreal climates and are assumed to be good predictors of soil moisture conditions [27,29].…”

Section: Introductionmentioning

confidence: 99%

Depth-to-Water Maps to Identify Soil Areas That Are Potentially Sensitive to Logging Disturbance: Initial Evaluations in the Mediterranean Forest Context

Latterini

Picchio

2022

Land

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Scientific research on reduced-impact logging has been addressed to develop effective approaches and methodologies to limit soil disturbance caused by forest operations. In recent years, the development of soil trafficability maps based on soil wetness indices is the approach that has been extensively used in the context of the Boreal forests. In particular, the depth-to-water (DTW) index has been identified as an interesting solution for the identification of areas particularly sensitive to soil disturbance. This study aimed to evaluate the cost-benefit factor of DTW maps for the identification of soil-sensitive areas in the Mediterranean context. In particular, a DTW map was developed for two oak coppice areas located in Italy and harvested over a period of 2–4 years with different mechanisation levels. Soil surveys concerning soil moisture, physico-chemical properties (bulk density, penetration resistance, shear resistance, organic matter), and biological properties (soil microarthropods community measure via soil biological quality (QBS-ar) index) were carried out in these forests, checking for significant differences between the zones at DTW index ≤1 (which should be more sensitive to soil disturbance) and the other areas of the forest soil. The results obtained revealed the efficiency of a DTW index in potential areas at a higher level of soil moisture. On the other hand, the values of soil physico-chemical properties in the areas at a DTW index ≤1 did not differ significantly from the ones in other zones. However, the values of the QBS-ar index in areas with a low DTW index were significantly lower than the ones in zones at the DTW index >1. Therefore, the obtained findings reveal that the DTW index is a reliable tool to identify and predict which areas are more prone to impact soil biological properties.

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Spatio-temporal prediction of soil moisture and soil strength by depth-to-water maps

Cited by 10 publications

References 46 publications

Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

Producing information from airborne LiDAR data for peatland forest management

Depth-to-Water Maps to Identify Soil Areas That Are Potentially Sensitive to Logging Disturbance: Initial Evaluations in the Mediterranean Forest Context

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