No abstract

No abstract

There is a need to quantify and better understand how wildlife interact with linear features, as these are integral elements of most landscapes. One potentially important aspect is linear feature tracking (LFT), yet studies rarely succeed in directly revealing or quantifying this behavior. In a proof-of-concept study, we employed short-term intensive GPS monitoring of red foxes ( Vulpes vulpe s) in a multiple-use landscape in southern Norway. Using periodic bursts of high frequency GPS position fixes, we performed modified path selection analyses to estimate the propensity of foxes to track natural and man-made linear features (roads, forest edges, and streams) once they are encountered. Foxes in our study tracked primarily forest edges and roads. Forty-three percent of bursts that encountered any linear feature resulted in LFT. LFT, although prominent, was manifested as a short-lived behavior, with overall median times to linear feature abandonment around two minutes. Movement speeds were highest along roads, perhaps due to greater ease of travel or higher perceived risk. In the highly heterogeneous habitats that characterize human-dominated landscapes, LFT may be manifested at such a fine spatio-temporal scale that it would remain hidden during telemetry studies employing conventional position fix frequencies. The approach described here may aid others studying spatial behaviors that are manifested over very short durations, yet are biologically significant.

The second international comparison of absolute gravimeters was held in Walferdange, Grand Duchy of Luxembourg, in November 2007, in which twenty absolute gravimeters took part. A short description of the data processing and adjustments will be presented here and will be followed by the presentation of the results. Two different methods were applied to estimate the relative offsets between the gravimeters. We show that the results are equivalent as the uncertainties of both adjustments overlap. The absolute gravity meters agree with one another with a standard deviation of 2 μgal (1 gal = 1 cm/s 2 ). In 1999, a laboratory ( Fig. 5.1) dedicated to the comparison of absolute gravimeters was built within the WULG. The laboratory lies 100 m below the surface at a distance of 300 m from the entrance of the mine. The WULG is environmentally stable (i.e., constant temperature and humidity within the lab), and is extremely well isolated from anthropogenic noise. It has the power and space requirements to be able to accommodate up 16 instruments operating simultaneously. IntroductionMultiple absolute gravimeter comparisons are regularly carried out. Being absolute instruments, these gravimeters cannot really be calibrated. Only some of their components (such as the atomic clock and the laser) can be calibrated by comparison with known standards. The only way one currently has to verify their good working order is via a simultaneous comparison with other absolute gravimeters of the same and/or if possible even of a different model, to detect possible systematic errors.During a comparison, we cannot estimate how accurate the meters are: in fact, as we have no way to know the true value of g, we can only investigate the relative offsets between instruments. This means that all instruments can suffer from the same unknown and undetectable systematic error. However, differences larger than the uncertainty of the measurements, is usually indicative of a possible systematic error.For the second comparison in Walferdange, a few new procedures have been introduced. First, some of the participants accepted to take part in a

In this paper, we present an automatic motion planner for agricultural robots that allows us to set up a robot to follow rows without having to explicitly enter waypoints. In most cases, when robots are used to cover large agricultural areas, they will need waypoints as inputs, either as premeasured coordinates in an outdoor environment, or as positions in a map in an indoor environment. This can be a tedious process as several hundreds or even thousands of waypoints will be needed for large farms. In particular, we find that in unstructured environments such as the ones found on farms, the need for waypoints increases. In this paper, we present an approach that enables robots to safely traverse not only between straight rows but also through curved rows without the need for any predetermined waypoints. Most types of infrastructure found in agriculture, such as polytunnels, are built on uneven terrain, thus containing a mix of straight and curved plant rows, for which traditional methods of row following will fail. Different from traditional approaches of row following that only consider straight‐line‐of‐sight rows, our approach identifies the rows on each side with the goal of staying in the middle of the rows, even if the rows are not straight. Waypoints are only needed on the very extreme of the rows, and these will be automatically generated by the system. With our approach, the robot can just be placed in the corner of the field and will then determine the trajectory without further input from the user. We thus obtain an approach that can reduce the installation time from potentially hours to just a matter of minutes. The final autonomous system is low cost and efficient for various tasks that requires moving between plant rows inside a polytunnel. Several experiments were performed and the robot demonstrates 1.4% position drift over 21 m of navigation path.