7.1. General
Road condition monitoring techniques can be generally described as a) functional condition monitoring, that measures the service level to the road users and b) structural condition monitoring which can be related more to the asset value of the road. Road service level monitoring techniques have been earlier described in the chapter 3 wearing course, so this chapter will discuss more about the structural monitoring techniques of gravel roads and forest roads and how these results can be used in the strengthening design. Some of the structural condition techniques are also described in chapter 5 “Roads on weak subgrade”, chapter 5 “Drainage” and Chapter 10 “Seasonal changes”.
The ROADEX webinar presented on 14 December 2022 gave a brief summary of the new technologies in gravel and forest road surveys and this can be seen in the following link.
7.2. Structural and functional condition
Gravel or forest road structures and their quality beneath the wearing course are normally measured only when there are already some visual problems that could be related to poor bearing capacity. In forest roads structural condition surveys should be made if there are plans for especially big harvesting operations in the area that require continuous timber haulage without accessibility problems.
7.2.1. Excavator surveys, sampling
The traditional way to survey a gravel road or forest road structure thickness is to open the road structure with an excavator on a few points on a cross section or opening the whole cross section. This technique is very usual for instance to define if the problem can be related to Mode 1 or Mode 2 rutting. The layer thickness can also be verified and samples taken using a canvas sheet and shovel.
7.2.2. Ground Penetrating Radar
While excavator pits can give good information at specific points, the benefit of GPR (Ground Penetrating Radar) is the continuous profile that is created along the gravel road or forest road. However the problem is that these structures can change substantially in the transverse direction of the road. That is why data collection and analysis using a 3D GPR system enables a full 3D analysis to be made of the gravel road structures. Cross sections with GPR also give valuable information about the road structures in 3D. More information about the theory of GPR technology is given in ROADEX “Permanent Deformation” eLearning package.
There are a few issues that however should be known when designing GPR surveys. First of all the extensive use of dust suppressant salts in a wearing course increases the conductivity of the material and this can cause GPR signal attenuation resulting in good quality data being collected only from the surface layers. If this is the case, GPR surveys should be made during the wintertime when the surface materials are frozen and conductivity is close to zero. When measurements are done during the wintertime the presence of frost line and ice lenses also give valuable information for differential frost heave and bearing capacity problems during the spring thaw weakening. The rule of thumb is the deeper the frost line is in the winter the less will be spring thaw weakening problems during the spring. Finally, earlier ROADEX tests with a 3D GPR system gave very promising results in detecting large boulders in the road structure that sooner or later will heave up to the road surface requiring removal.
7.2.3. Deflection surveys using FWD and LWD techniques
Information how a gravel road or forest road structure will deflect under a heavy truck axle is essential in the structural diagnostics of roads. The theory of falling weight deflectometer (FWD) and light weight deflectometer (LWD) is explained in more detail in the ROADEX “Permanent deformation” eLearning package.

FWD data is more useful in gravel road diagnostics as it provides valuable information about the deflection bowl. From the deflection bowl data different bearing capacity indexes can be calculated indicating if the problems can be related to poor quality road surface materials (Mode 1 rutting), or if the main problem is that the road structure cannot spread the truck load wide enough over a weak subgrade soil (Mode 2 rutting). The benefit of the FWD data is also that it can be used, together with thickness data from GPR, to back-calculation or forward calculation of the road structure and subgrade moduli values. These can be further used in the bearing capacity design in the road strengthening projects. There are a few issues that should be remembered when ordering FWD surveys on forest or gravel roads. First of all these surveys should not be made in the spring or early summer when frost is still in the subgrade because results will be too good. Also in the dry and warm summer days when road structure is dry, the results might be high. The best time for surveys is late summer and fall when the structures have more moisture and results are more representative.
LWD measures only the E2 value on the road surface but it is cheaper and easy to use and gives information about the general bearing capacity level and its changes in the road surface. LWD has proven also to be a good tool in compaction control when building gravel and forest roads.
In gravel and forest road bearing capacity basic diagnostics ROADEX recommends using bearing capacity indexes SCI (surface curvature index) and BCI (base curvature index). SCI is calculated from the difference between geophones 0 mm and 200 mm. High SCI values indicate a high risk for deformations close to road surface and Mode 1 rutting. BCI is calculated from the difference between 900 mm and 1200 mm. High BCI values indicate a high risk for deformation at the road structure / subgrade interface and for Mode 2 rutting. Presenting SCI and BCI values makes it possible to locate the road sections with different types of bearing capacity and deformation risks.
In addition, a further useful bearing capacity parameter is the surface bearing capacity (E2) that gives a general overview of the bearing capacity of a single gravel road or forest road or road network. Another good parameter is the subgrade moduli value that gives information about the stiffness of the subgrade soil or embankment at the depth of 1.0-1.4 m. Combining these two pieces of data enables engineers to define those sections where the problems are subgrade related and more expensive to strengthen, and sections where bearing capacity can be improved in much easier way.
7.2.4. Laser Scanners and gravel and forest roads
Since the 2010’s laser scanner technology, also called lidar, together with improved positioning systems such as GPS and Inertial Motion Units (IMU) have become more precise and cheaper. In addition more powerful PC’s and better software packages can process larger laser scanner data sets in a more efficient and easier way.
Laser scanning is a technique whereby distance measurement is derived from the travel time of a laser beam from the laser scanner to the target and back. When the laser beam angle is known, and beams are sent to a range of directions from a moving vehicle with a known position, it is possible to make a 3D surface image, a “point cloud”, of a road and its surroundings. The point cloud can have millions of points, with every point having x, y & z coordinates and additional reflection or emission characteristics. The laser scanner should be place as high as possible on the survey vehicle so that data can be collected also from the inner slope and ditch bottoms.
The great benefit from the laser scanner data is that it is possible to measure all the critical parameters and dimensions needed for a road: road width, cross slopes, ditch bottom levels, inner slope shapes angles and outer slope angles. And if there are, for instance, vegetation or other obstacles in the road area, these too can also be detected.
In addition to the above standard parameters there are many other new parameters that can be calculated from laser scanner data that can be useful in the gravel road or forest road condition management. For instance rut depth measurements can be used for indirect information about any bearing capacity problem sections. Experience has shown that after grading operations rut growth is always the highest on the same sections with permanent deformation problems.
Another useful laser scanner application in road maintenance is detecting verges to be removed. As reported in the drainage chapter, verges keep water in the road surface and this can lead to potholes, deformations and even erosion during periods of heavy rain.
Finally, laser scanners can be used to monitor dusting problems on gravel roads and where dust suppressant should be spread.
7.2.5. 3D Accelerometer techniques
A three-dimensional (3D) accelerometer is an electromechanical device that detects and measures non-gravitational accelerations. These forces can appear as motion, vibration, or orientation of the equipment. Such forces include static and dynamic accelerations outside the range of normal gravity (G). Thanks to their low price 3D accelerometers have become more common and these sensors can be found for instance in modern cellular phones. Also most of the new generation vehicles have several 3D accelerometers installed and already in 2005 the ROADEX project reported about the use of yaw sensors in detecting black ice and other friction problems on roads.
On gravel and forest roads 3D accelerometers can be used in monitoring the functional condition, ie. the service level of these roads. Due to dusting problems traditional laser based systems cannot be used in unsurfaced roads. These 3D sensors can also be used during wintertime when point lasers have problems with snow smoke.
Gravel or forest road roughness can be measured with different cellular phone applications, but if acceleration forces need to be measured in a repeatable and comparable way, specially calibrated 3D accelerometers should be used. These systems consist of a high quality 3D accelerometer sensor installed on the floor under the driver’s seat and a camera in the front (or back) window. In addition the system has data collection unit working with 12V DC as well as GPS and 4G/5G antenna. The system can measure automatically when the vehicle is running, or it can be started remotely by cellphone. Because acceleration forces are speed dependent the systems need to be speed calibrated and because different vehicle have different suspensions systems this calibration should be done with different artificial or known “bumps”. The collected data is then stored in the cloud and can be viewed and analysed using special web browser software packages.
The greatest benefit of these systems is that they can be installed on normal vehicles used by engineers responsible of the follow-up of gravel road maintenance contracts or by the supervision staff of the contractors who are driving regularly on the road network. In this way it is relatively easy to collect valuable data about changes in gravel road network roughness in different seasons and years. Results of using these systems so far indicate that a single measurement each year will not provide any kind of reliable general picture of the gravel road condition over the year.
By presenting the 3D accelerometer results as GIS maps it is easy to make objective comparisons of the average condition of roads in specific areas and thereby focus any special maintenance measures on those road sections with the biggest problems.
The roughness problems of a particular gravel road can be analysed by a condition history over spring, summer and fall. In this analysis problems related to differential frost heave are normally those ones with decreasing roughness problems from spring to summer, and no problems during the late summer and fall. Wearing course related problems can be seen mainly during the summer and they can change based on how well the maintenance measures have been made.
Photographs can also be a great help in 3D accelerometer based roughness condition analyses. They can give a quick understanding of the reasons for the roughness problems in each area. View the photos from the map.











Photographs with vertical acceleration values also help the preparation of roughness classifications for gravel roads or forest roads.
Finally 3D accelerometer data can be used also on the classification of the three most common roughness problems on gravel road, ie. differential frost bumps, potholes and washboarding. Their root cause and also their repair method is totally different.
The best indication of differential frost heave related bumps are 3D accelerometer pitch values and their variation, with additional comparisons of the spring values to early autumn values. The autumn pitch values should be much lower than the spring values.
Potholes and washboarding can often be separated with a wavelength analysis of the vertical acceleration data. Potholes can be mainly related to drainage problems and high water content in the road structure. That is why sections with potholes will also have high amounts of long wavelengths whilst washboarding is mainly surface related problems without long wavelength components.