Browsing by Subject "UAV"
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(2021)Municipal environmental authorities are required to conduct environmental monitoring. Unmanned aerial vehicles, UAVs, may be helpful in environmental monitoring but their applicability as a tool for municipal environmental monitoring has not been studied. In this thesis it was studied, how municipalities have been utilizing UAVs. Additionally, UAVs applicability for environmental monitoring and inspection work was tested using a litter monitoring experiment as an example. In the first part of the study, a questionnaire was sent to municipal environmental authorities in Finland, to municipalities in Sweden and to those participating in Eurocities WG Waste group (n = 512), covering the used applications, their utilization frequencies and successfulness, reasons for failures and future plans. The results were analyzed using descriptive statistics. In the second part of the study, a UAV was utilized in a litter monitoring experiment on four sites in Helsinki. Litter by category and leaves were counted based on visual observations from UAV imagery. The accuracy of UAV imagery detection was assessed by comparing its and ground assessment (GA) results. On one site, a control group also carried out UAV imagery detections in order to assess the magnitude of bias or offset occurring when both the GA and the litter detection from UAV imagery are conducted by a single individual. The Wilcoxon signed rank and Cronbach’s α reliability tests were used for statistical analysis of the results. Response rate of the questionnaire was low, 3.7% (n = 19). The pool of used applications was extensive and covered a variety of monitoring and inspecting targets with emphasis on the presumably manually piloted applications. Utilization was very successful. The most important reasons for failures were poor weather followed by lack of information and expertise. UAVs were included in the future plans of most participants for municipal environmental monitoring purposes. The UAV imagery detection accuracies of litter and leaves compared to the GA results were high, 90.5% for litter and 87.5% for litter and leaves, and no statistically significant differences existed between the assessment results. Especially leaves proved challenging to detect from UAV imagery. The control group’s detection accuracies were 67.9% without and 49.0% with leaves, and with leaves the results differed with statistical significance (p = 0.028). The internal reliability of the control group was relatively high, α = 0.776 without and α = 0.805 with leaves. UAVs are deemed sufficiently accurate and versatile as monitoring and inspecting tools for municipal environmental authorities. They have the capability to complement ground assessments or, with certain prerequisites, even function as an independent monitoring method. Further application and detection method development and research on municipal UAV utilization are needed.
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(2020)The number of drones has increased in both the private and corporate sectors. There is also an interest in the use of drones in agriculture since by using them the large fields can be monitored easily. Automatic flight systems of drones are simple to use. More accurate overview of the field can be got by utilizing the drones than by making observations from the side of the field. With aerial photographs the measures for the field can be planned further. For example, based on the photos pesticide spraying or fertilize spreading can be planned for the field. Drones can also be used to estimate crop biomasses. With drones the development of the crops is possible to observe as a timeseries during the growing season. The aim of this study was to explore the use of multispectral images and 3D models in crop monitoring. Crop leaf area index (LAI), biomass and chlorophyll content were measured. There were 8 different plants/fertilization levels in this study. In this study, a multispectral camera and a RGB-camera were used to estimate crops features. With a multispectral camera the reflectance values of the vegetation, which described how much of the incoming sun radiation was reflected back from the vegetation, were able to determine. The multispectral camera had five spectral bands (blue, green, red, red edge and NIR). Based on these bands NDVI vegetation index was calculated. The reflectance values and vegetation indices were compared to the dry matter mass, LAI, and chlorophyll content determinations of the vegetation. From the images of the RGB-camera 3D-models were created to calculate crop volumes. Calculated volumes were compared to crop dry matter mass and LAI measurements. Linear regression analysis was used to examine the relationship between the variables calculated from the images and the parameters determined from the crops on the field. According to these results, the variables determined from the multispectral images explained the dry matter mass and leaf area index of the crop slightly less than the 3D-models determined from the RGB images. The strongest determined dependence of the data recorded by the multispectral camera was between the faba bean LAI and NDVI (R2 = 0,85). The relationship between the reflection/index data of multispectral camera and crop parameter was weak: average coefficient of determination for dry matter mass of the crop was 0.15, for chlorophyll content 0.14, and for LAI 0,21. The highest coefficient of determination for 3D model of crop volume was between the dry matter mass of oats (R2 = 0.91). The mean coefficient of dependence was 0.69 for the relationship between the plant dry matter masses and 3D model volumes. The mean coefficient of determination for the relationship between the leaf area index of plants and the 3D model volumes was 0.57. Based on these results, from the multispectral camera data, the NDVI index was best suited to determine the crops dry matter mass, leaf area index, and chlorophyll content. However, there were differences in the dependencies between different spectral bands/NDVI index and plant properties determined from different crops. 3D models produced stronger dependences for estimating crop dry matter mass and leaf area index than the quantities determined from multispectral images. Analyzing the data with more sophisticated calculation methods utilizing the values of several spectral bands and the indices in the same time would probably have been a more efficient method to analyzing the data than the current used linear regression used in this study. Removing errors, caused by external factors, from multispectral images was found to be very difficult. Especially reflectance values of dry soil differed clearly from vegetations values. Further studies are needed to develop vegetation indices that can reduce errors caused by external factors. In addition, data processing of images should be developed to utilize multiple spectral bands and vegetation indices to determine the relationship between crop characteristics and variables measured from images. In addition, different plant species imaging techniques should be investigated, as different plants have different reflection values.
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(2023)Dead wood is an integral part for forest biodiversity in boreal forests. 5000 (25 %) of Finland’s forest dwelling species depend on decaying dead wood during their life cycle. The loss of dead wood in forest ecosystems has been identified as the number one reason for species endangerment. Conventional dead wood mapping is done by counting and measuring dead wood from field plots or by aerial laser scanning, both of which can be timeand resource consuming. UAV-borne aerial imaging provides cost effective and high spatial and temporal resolution in comparison to conventional aerial imaging and satellite-based imagery. A convolutional neural network (CNN) is a deep learning algorithm that has shown promise in recognizing spatial patterns. The strengths of CNNs are end-to-end learning and transfer learning. CNNs have been used for mapping both standing and downed dead wood. This thesis aims to further investigate the usability of a method based on detecting downed coarse woody debris (CWD) in a coniferous boreal forest from RGB UAV-imagery using a CNN based segmentation approach. CWD was digitized from an orthomosaic created from UAV-imagery. CWD was digitized from 68 square shaped 100 x 100 m virtual plots surrounding 9 m radius circular field plots. The plots were divided into 57 training plots for training the CNN and 11 test plots for evaluating the CNN model performance. The effect of different loss functions and the effect of data augmentation on model segmentation performance was evaluated. The number of digitized and segmented CWD objects were compared to the number of CWD objects from the field plots and the effect of canopy cover and basal area on the detection rate was assessed. The CNN model segmented 324 m ² of CWD from the 11 virtual test plots, from which 469 m ² of CWD had been digitized, resulting in a 69 % segmented-to-digitized CWD ratio. The model with the best performance achieved a precision of 0.722, a recall of 0.500, a Dice-score of 0.591, and an intersection over union (IoU) of 0.42. The sample size of field measured CWD from the field plots was relatively small and neither canopy cover nor basal area was found to have a statistically significant (P = 0.05) effect on CWD detection rate. For the digitized CWD detection rate, canopy cover had a p-value of 0.059 and basal area a p-value of 0.764. For the model segmented CWD detection rate, the p-values were 0.052 and 0.884, respectively.
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(2023)The island of Suur-Pellinki is located near the town of Porvoo in the southern Finland. The bedrock in the area consists of different rock types such as plutonic rocks and rock types that are rare in the southern Finland, for example agglomerate and different kinds of metavolcanites. The bedrock has undergone several tectonic events, of which Svecofennian orogenesis (1.9-1.8 Ga) has been the most notable. The orogenesis caused compression, extension and shearing of the bedrock, and signs of these stresses can be seen as fractures, folds, foliations and faults. The development of unmanned aerial vehicles, such as drones, has been significant in recent years. Thus, usage of them has increased in different fields of science, of which geosciences are not an exception as drones are used in data collecting. In this study, a drone was used to study outcrops of Suur-Pellinki. Four outcrops were photographed by a drone, and photographs were used to build three-dimensional models. The models were built in Pix4D and Metashape software using Structure-from-Motion photogrammetry. In addition, the models were exported to GeoVis3D software, in which orientation of fractures was studied. The aim was to study the bedrock with traditional fieldwork methods and technology that has not been used in the area. It was studied if three dimensional modelling can provide any significant additional benefits over traditional fieldwork methods. Moreover, the aim was to find ways to operate a drone efficiently and build three-dimensional models straightforwardly. The bedrock was found to be undergone extensional and differently oriented compressional events during the orogeny, and the maximum principal stress (σ1) orientations had been firstly NW-SE and later NE-SW. These stress orientations formed the main structures of the bedrock such as fractures, folds, and foliation, which is prevalent in metavolcanites of the area. In addition, some strike-slip faults were seen in the area, which have not been studied significantly in the previous studies. The three-dimensional models turned out to be useful in order to study the bedrock. Critically, building of the models was not fast and straightforward. The final resolution of the models is under three centimetres, which let to study even the smallest structures of the bedrock.
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(2020)The condition of Tahmelanlähde spring in city of Tampere has been under discussion for over two decades. Between 1906–1966, the spring was being used for municipal water supply and the water quality was good. The quality of discharging groundwater has since heavily deteriorated, bearing now high concentrations of iron, manganese, nitrogen, phosphorus and very low oxygen. The cause of this deterioration has remained unclear. The aims of this study were to increase the hydrogeological knowledge of Tahmela-Pispala area in order to get a better understanding of the regional groundwater flow patterns and sources of the groundwater discharging at the artesian spring area, to assess the cause for the spring deterioration and to give suggestions to a possible rehabilitation plan. Tahmelanlähde spring is located on a clay or silt soil under artesian circumstances, down the southern slope of Pispalanharju interlobate esker formation. The esker forms a longitudinal neck between Lake Näsijärvi and Lake Pyhäjärvi, rising up to 160 meters above sea level. The water level of Lake Näsijärvi is approx. 95 m a.s.l. and the water level of Lake Pyhäjärvi approx. 77 m a.s.l. Considering the distance of only a few hundred meters between these two lakes, the difference of 18 meters in the lake water levels is quite unusual in Finland’s geological context, especially because the lakes are separated by a major esker formation. For the assessment of the hydrogeological features in the study area we had two field campaigns including ground penetrating radar (GPR) survey, thermal infrared survey using unmanned aerial vehicle (UAV-TIR), measuring of water tables as well as water sampling from springs, surface water bodies, groundwater observation wells and groundwater discharging into the Lake Pyhäjärvi. 23 water samples were analyzed for main ion composition, stable isotopic (δ18O / δD) composition, pH, EC and trace elements such as iron and manganese. 14 samples were additionally analyzed for CODMn, N, P, O and microbial indicators. Some previous studies have suggested infiltration of Lake Näsijärvi water into the esker. Our results reveal that most of the groundwater in the Pispalanharju area contain a variable amount of surface water component. The samples east from the spring present good-quality groundwater and show nonexistent surface water impact. This and the complex sedimentology revealed by the GPR survey indicate that the regional groundwater flow patterns are not simple and there are at least two water components with different origins discharging at Tahmelanlähde spring. The results imply that the primary cause for the spring deterioration could be a major shift in the groundwater – surface water interaction in the northern esker area, probably driven by urbanization and the heavy construction during the last few decades. The study was a collaboration between the City of Tampere, Pirkanmaa Center for Economic Development, Transport and Environment (ELY Center) and University of Helsinki, Department of Geosciences and Geography.
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