In many countries, most organic waste is usually placed in landfills, which generates public concern about the health effects of emissions pollutants. The natural bacterial decomposition of organic waste produces landfill gases, about half of the methane, with the remainder mainly carbon dioxide and minor amounts of other gases. Real-time measurement and modeling of emissions gases in landfills are essential. This work develops a low-cost wireless measurement system using MOS gas sensors (MQ4, MQ5, and MQ9), a 32 bits microcontroller, an XBee module, and HC-12 wireless communications modules. The system can be mounted on an uncrewed aerial vehicle (UAV, drone) or deployed as a wireless sensor network. Experiments have been carried out near a closed landfill, and measurement results show high methane concentrations.

Estimating the measurement uncertainties of coordinates of points that are not accessible by direct geodetic surveying (hidden points) is the topic of this study. The simplicity by which the uncertainties can be found for such hidden points when practicing indirect observations by total station or by Global Navigation Satellite System (GNSS) is demonstrated. A three-dimensional solution is obtained by total station observations using a two-prism hidden-point rod and a two-dimensional solution by GNSS observations on the ground. An intention with the study is that methods and results should apply for general geodetic purposes, like engineering surveying. The derived uncertainty formulae have been verified by Monte Carlo simulations. An important finding is their geometric dependence by the quotient between the two distances involved when two coordinated points are collinear with a third hidden point. 

The number of landfills in Sweden is not exactly known, but the number of closed landfills containing organic waste is estimated to be between 4000 and 8000. Some of these are close to large and growing cities and are of interest to exploitation. Urban air quality affects people's health and well-being, real-time measurement and modelling of gases in the air is important for planning future cities. In this paper, we present a cost-effective method for monitoring methane and CO2 based on gas sensors mounted on an unmanned aircraft (UAV, drone). A drone-based wireless system is developed with MOS sensors (MQ2, MQ4 and TGS2611), Arduino-nano, XBee wireless communications modules and the interface to a base station's computer is written in Python. The system was tested in real field measurements with good results.

The purpose of this paper is to investigate the height uncertainty of digital terrain models (DTMs) generated from unmanned aircraft system (UAS) surveys over different surface types – asphalt, gravel and grass. The data used in the study was acquired during two UAS flights performed in spring 2014 with a fixed wing aircraft and two different cameras, from the flying height of about 100 m, and it was processed in different software suites – Agisoft PhotoScan, RapidStation and RapidTerrain. The results show that it is possible to achieve the height uncertainty (expressed as a Root Mean Square Error) in a DTM of below 0.02 m on asphalt surfaces and below 0.04 m on gravel and grass surfaces, provided an overcast sky.

In order to investigate the possibilities for the generation of digital elevation models with a height uncertainty of 20 mm or less using unmanned aerial vehicles, a survey with a fixed-wing aircraft was carried out over a gravel quarry in Gävle, Sweden. At flying heights of about 80 and 160 m, the resulting imagery had ground sample distances of 24 and 50 mm, respectively. The data was processed in two different software suites – computer-vision-based PhotoScan and photogrammetric RapidStation/RapidTerrain. The results show that PhotoScan was more effective in flat terrain, with height uncertainties of 10 and 17 mm compared with 30 to 40 mm for RapidTerrain, whereas the latter had a clear advantage over undulating terrain.

Syftet med det här projektet har varit att undersöka utbudet av befintliga UAS för laserskanning, studera erfarenheter av deras tillämpning inom 3D-kartering, samt bedöma deras potential för framställning av DTM för byggnadsinformationsmodellering (BIM). Med tanke på teknikens snabba utveckling bör den här rapporten ses mer eller mindre som en ”ögonblicksbild” av ”UAS-laserskanningslandskapet” i slutet av 2015.

Byggnadsinformationsmodellering (BIM) är ett begrepp som avser att ge en effektiv byggprocess genom digital representation av både fysiska och funktionella aktiviteter i ett byggprojekt. I en vid bemärkelse kan BIM användas i hela byggprocessen, från planering, projektering och byggande till förvaltning, renovering och slutlig destruktion. I en mer snäv bemärkelse används BIM enbart för digitala modeller (Volk m.fl., 2013), som i den här rapporten, där fokus ligger på framställning av digitala terrängmodeller (DTM) för exempelvis byggprocessens planering och/eller projektering.

Methane built up in landlls as a result of breaking down of organic materials can be a renewable energy source if it is taken advantage of. The aim of research presented in this paper is to detect landll gas (that contains methane) by means of terrestrial laser scanning. The hypothesis is that where no surface leakage has been reported, the landll gas will expand or migrate. Therefore, it is possible to detect it through repeated scanning of the same area and comparison of Digital Terrain Models (DTMs) generated from the point clouds. Only the most signicant movements, i.e. vertical, are of interest in this case. During September–November 2011, a small area at Forsbacka landll in the vicinity of Gävle was scanned 10 times. Epoch-to-epoch comparisons of the resulting DTMs have shown two signicant changes (–27 and +19 mm) in elevation of the surface, and it is not impossible that they are caused by migrating landll gas. The method tested in this study is deemed to be rigorous and accurate for detecting small-scale swell-shrink behaviour of the ground surface (in our case a landll surface). However, both data processing and interpretation of the results have been considerably complicated by presence of low vegetation (weeds) on the study site, which was di-cult to lter away completely from the data. Based on our pilot study, we recommend that a larger area and a longer period of time are chosen to give basis for more grounded conclusions about presence of landll gas.

På Högskolan i Gävle har under vårterminen 2013 fyra examensarbeten genomförts för att undersöka möjligheter och problem med användandet av obemannade flygfarkoster för fotogrammetriska ändamål. Studenterna har läst det treåriga lantmätarprogrammet med teknisk inriktning, som liksom alla högskoleprogram, avslutas med ett examensarbete. De här fyra grupperna har haft ett gemensamt intresse, nämligen UAS, och deras undersökningar refereras i artikeln nedan. Men först en kort beskrivning av UAS.

This paper reports on investigation of measurement uncertainty in positioning of a terrestrial laser scanner with network RTK (Real-Time Kinematic) service provided by SWEPOS®, Swedish national network of permanent reference stations for GNSS (Global Navigation Satellite System). To simulate measurements by a scanner, a rotating flat bar fixed to a prism base, attached to a tribrach, was used. The tests have been carried out with both a rotating GNSS antenna (placed at different distances from the centre of rotation – radii) and a stationary antenna, under different time intervals (1–5 min). The results show that it is possible to achieve a standard uncertainty of less than 10 mm in plane and 16 mm in height, independently of the observation time and radius. Hence, network RTK can be used with advantage for precise direct georeferencing of point clouds, not only for determination of the position of the scanner, but also its orientation.