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The objective of this paper is to present new architecture of solution for object detecting and blurring. Our algorithm is tested on four data sets of panorama images. Percentage of accuracy, ie. successfully detected objects of interest is higher than 97 % for each data set. The proposed algorithm has a wide application- for images of different type, surveyed with various purposes and detection of different types of objects, as well.

DMA-based algorithm developed by the authors allows us to solve the main tasks of cyclostratigraphy: periodograms were constructed with further identification of repetitive cycles for carrying out geological reconstructions and correlations of sediments of the same age over a large area.

The study was conducted along the Luangwa River in Zambia. It combines low-cost instruments such as UAVs and and GPS kits to collect data for the purposes of water management. A novel technique which seamlessly merges the dry and wet bathymetry before application in a hydraulic model was applied. Successful implementation resulted in water authorities with small budgets being able to monitor flows safely and efficiently without significant compromise on accuracy.

The importance of the soil evaporation concerns our main life supports source. A simple to operate instrument made for soil evaporation measurement appears then suitable. Any measurement technique may perturb the monitored space affecting external conditions such as the air temperature or the wind. In order to perform a reliable measurement all these perturbations need to be estimated and corrected. A device and a protocol allowing soil evaporation corrected measurement is described

In this paper, we study the compensation method of the helicopter towed bird. We will affect the compensation results based on the geomagnetic gradient. Therefore, we build a compensation model based on the geomagnetic gradient, which is 6 % higher than the traditional model. When the helicopter towed bird system is used for magnetic target exploration, this method can be used to eliminate the interference generated by the helicopter towed bird system, and further accurately detect the target.

We have developed a towed magnetic gradiometer system for rapid acquisition of magnetic and magnetic gradient maps. This high resolution system is flexible and has applications to utility detection, archaeology, unexploded ordnance, or any other applications where high-resolution maps of the magnetic field or gradient are required. Processing of the data has been simplified as much as possible to facilitate rapid results and interpretations.

The quality control and validation activities performed by the Swarm Data Quality Team reveal the good quality LP. The analysis demonstrated that the current baseline plasma data products are improved with respect to previous baseline. The LP have captured the ionospheric plasma variability over more than half of a solar cycle, revealing the data quality depenndence on the solar activity. The quality of the LP data will further improve promoting their application to a broad range of studies.

Cosmic Ray Neutron Sensing (CRNS) is a non-invasive tool for measuring hydrogen pools like soil moisture, snow, or vegetation. This study presents a directional shielding approach, aiming to measure in specific directions only. The results show that non-directional neutron transport blurs the signal of the targeted direction. For typical instruments, this does not allow acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates is feasible.

We use the technical methods of instrument development, calibration experiments and numerical simulation to develop a new type of in-situ stress sensor group using fiber Bragg grating (FBG) sensing technology, which can calculate the in-situ stress state of surrounding rock mass by sensing the borehole wall strain. This sensor group lays an important theoretical and experimental foundation for the development and application of FBG hole-wall strain gauge.

Methods for reconstruction of winter long data gaps in snow depth time series are compared. The methods use snow depth data from neighboring stations or calculate snow depth from temperature and precipitation data. All methods except one are able to reproduce the average snow depth and maximum snow depth in a winter reasonably well. For reconstructing the number of snow days with snow depth ≥ 1 cm, results suggest to use a snow model instead of relying on data from neighboring stations.

Reduce the uncertainty in air quality assessment by imputing all missing pollutants in the monitoring stations and identify where more measurements can be beneficial. The proposed approach is based on spatial or temporal similarity between stations. We found that our proposed approach enables us to impute/estimate plausible concentrations of multiple pollutants at stations across the UK, and the modelled concentrations from the selected models correlated well with the observed concentrations.

Based on an analysis of the differences between DEM and point cloud data, including the corresponding acquisition methods, data structures and model construction methods, this paper proposes a 3D point set data model based on regular grid 2D data field for regional modeling. The feasibility of the model is tested through the upper and lower boundary modeling method.

This paper presents a brief description of the ground-based installation for the study of cosmic rays "CARPET". Today there is a network of such installations located in different parts of the world. For ground-based installations, meteorological effects must be considered as they affect the data. This paper shows a technique for eliminating barometric and temperature dependences based on data for 2019–2020.