Using remote sensing data to predict road fill areas and areas affected by fill erosion with planned forest road construction: a case study in Kastamonu Regional Forest Directorate (Turkey)

Arıcak, Burak

doi:10.1007/s10661-015-4663-7

Cited by 24 publications

(19 citation statements)

References 5 publications

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“…Contreras et al [17] attempted to use the created DMT to determine the extent of groundworks during a hauling road design and compared its precision with the data obtained by the conventional ground-based method. Aricak et al [18] used the commercial satellite imagery system GeoEye-1 with high spatial resolution of 0.46 m pixels to create the DTM. However, the resulting definitions of about 1 meter cannot be used to evaluate the status of the wearing course [19].…”

Section: Introductionmentioning

confidence: 99%

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

et al. 2018

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Currently, a large part of forest roads with a bituminous surface course constructed in the Czech Republic in the second half of the last century has been worn out. The aim of the study is to verify the possibility and the accuracy of the road wearing course damage detected by four different remote sensing methods: close range photogrammetry, terrestrial laser scanning, mobile laser scanning and airborne laser scanning. At the beginning of verification, cross sections of the road surface were surveyed geodetically and then compared with the cross sections created in the DTMs which were acquired using the four methods mentioned above. The differences calculated between particular models and geodetic measurements show that close range photogrammetry achieved an RMSE of 0.0110 m and the RMSE of terrestrial laser scanning was 0.0243 m. Based on these results, we can conclude that these two methods are sufficient for the monitoring of the asphalt wearing course of forest roads. These methods allow precise and objective localization, size and quantification of the road damage. By contrast, mobile laser scanning with an RMSE of 0.3167 m does not reach the required precision for the damage detection of forest roads due to the vegetation that affects the precision of the measurements. Similar results are achieved by airborne laser scanning, with an RMSE of 0.1392 m. As regards the time needed, close range photogrammetry appears to be the most appropriate method for damage detection of forest roads.

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Section: Introductionmentioning

confidence: 99%

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

et al. 2018

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“…There is still another function, more and more presently pressing, and that is the necessary access to forests for fire fighters in case of fires (Najafi and Richards 2013). It follows the statement made by Aricak (2015) that the sustainable management of forest ecosystems requires a high-quality infrastructure of forest roads, despite the possibly negative environmental impact of the forest road network construction. The forest management of the Czech Republic manifests a constant effort to improve the quality of the forest access roads, both by the construction and maintenance of the forest road network which serves not only for timber transport.…”

Section: Introductionmentioning

confidence: 79%

“…Ahamed et al (2000) presented that the LiDAR accuracy of each point on the ground is approximately 15 cm in the vertical, and 1.0 m in the horizontal. Aricak (2015) stated that with a commercial satellite imagery system GeoEye-1, it is possible to achieve a high degree of resolution with an accuracy of 0.46 m. LiDAR method can help us update the maps of the forest road network, increase the eff ectiveness of the forest access, can be used for the planning of harvest processes, e.g., the direction and length of skidding and transport; however, the data processing can be lengthy and the method is not applicable for gaining more accurate and detailed data, as is the case of the wearing course surface damage. Despite the mentioned options of the LiDAR method, it is necessary to have high-quality data obtained by remote sensing of the Earth and work with a large volume of data; their accuracy can be lost by interpolation when creating a DTM.…”

Section: Discussionmentioning

confidence: 99%

“…Based on an accurate DTM (Digital Terrain Model) created using the LiDAR data, the locations of draining structures on the forest roads can also be laid out and the erosion resulting from the construction of forest roads can be reduced (Aruga et al 2005). Aricak (2015) created a DTM using a commercial satellite imagery system GeoEye-1. The images are then processed in software, ERDAS and ArcGIS, to determine locations prone to erosion as a basis for a design of a forest road network.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring of Forest Hauling Roads Wearing Course Damage Using Unmanned Aerial Systems

Hrůza¹,

Mikita²,

Janata³

2016

Acta Univ. Agric. Silvic. Mendelianae Brun.

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Currently, a large part of the forest roads that were built using the bituminous surface technology in the second half of the last century have been worn out. This means that forest owners and forest managers urgently need to determine the amount and extent of this damage and establish a suitable repair plan, which demands both time and staff. The aim of the study is to verify whether it is possible, and with what precision, to detect the damage of the wearing course by means of unmanned aerial systems, which would facilitate and accelerate this process and possibly make it cheaper. A 3D model of a forest road was created using photos of the current state of a damaged part of a forest road. The aerial photographs were taken by an unmanned aircraft. To verify the accuracy of the model, cross sections of the road surface were surveyed tachymetrically and compared with the cross sections created in the 3D model in ArcMap, from photogrammetric pointcloud using aerial photographs from the unmanned aircraft. The RMSE of the values of the control points in the 3D model cross sections compared to the values of the points in the tachymetric measurement of the cross sections reached to within 0.0198 m. The results of the tested road section showed that the unmanned aerial systems can be used to detect the forest road surface damage with the difference in accuracy being up to 2 cm compared with the accuracy of the current tachymetric methods. Based on the results we can conclude that the used method is appropriate for detailed monitoring of the condition of the asphalt wearing course of forest roads and allows for a precise and objective localization and quantification of damage.

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“…Some of the studies are using by GIS such as forestry, agriculture, landscape, protecting area (Aricak, 2015;Aricak et al, 2016;Cetin and Sevik, 2016;Kaya et al, 2009). But until now, GIS can't be used for erosion control.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of Soil Erosion and Sustainable Land Use Management in the Sarısu Basin

Karaş

Oğuz

2017

Turkish JAF Sci.Tech.

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Land use management requires controlling natural resources for sustainability. Soil erosion related to improper land use is a major issue around the world. Land degradation may harm the health of ecosystems. Defining the soil loss in a basin is the starting point in the restoration of soil quality for crop production. Reducing soil losses to a tolerable rate is one of the primary objectives for sustainability and soil conservation. Central Anatolia is under considerable risk due to an increase in the cultivation of marginal lands for food production. Cultivated lands have already been reached the final limits throughout the last 50 years. Moreover, forests and considerable areas of pasture have recently been converted to ploughed fields due to agricultural expansion. This study was conducted in the Sarısu basin to evaluate soil losses and land use management for sustainability. The Universal Soil Loss Equation model and Geographic Information System techniques were used to estimate the soil losses. The mean potential soil loss of the basin was calculated to be 1.88 t ha-1 per year with the Universal Soil Loss Equation model. These results are comparatively small when compared to the average value for Turkey of 13 t ha-1 yearly. Our calculated results are closer to the value for the Sakarya river basin, which is approximately 2.77 t ha-1 y-1. In this study, land usages in the Sarısu basin were evaluated in terms of soil losses, tolerable soil loss rates and soil conservation precautions.

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Using remote sensing data to predict road fill areas and areas affected by fill erosion with planned forest road construction: a case study in Kastamonu Regional Forest Directorate (Turkey)

Cited by 24 publications

References 5 publications

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

Monitoring of Forest Hauling Roads Wearing Course Damage Using Unmanned Aerial Systems

Evaluation of Soil Erosion and Sustainable Land Use Management in the Sarısu Basin

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