The objective of precision beekeeping is to minimize resource consumption and maximize productivity of bees. This is achieved by detecting and predicting beehive states by monitoring apiary and beehive related parameters like temperature, weight, humidity, noise, vibrations, air pollution, wind, precipitation, etc. These parameters are collected as a raw input data by use of multiple different sensory devices, and are often imperfect and require creation of correlation between time data series. Currently, most researches focus on monitoring and processing each parameter separately, whereas combination of multiple parameters produces information that is more sophisticated. Raw input data sets that complement one another could be pre-processed by applying data fusion methods to achieve understanding about global research subject. There are multiple data fusion methods and classification models, distinguished by raw input data type or device usage, whereas sensor related data fusion is called sensor fusion. This paper analyses existing data fusion methods and process in order to identify data fusion challenges and correlate them with precision beekeeping objectives. The research was conducted over a period of 5 months, starting from October, 2019 and was based on analysis and synthesis of scientific literature. The conclusion was made that requirement of data fusion appliance in precision beekeeping is determined by a global research objective, whereas input data introduces main challenges of data and sensor fusion, as its attributes correlate with potential result.

Latvia University of Life Sciences and Technologies, Latvia Precision of the forest inventory planning is still one of the most important problems in the forestry nowadays. The aim of this research was to estimate the sample tree height results of the combined forest inventory (LiDAR CFI) and LiDAR (Light Identification Detection and Ranging) height data by calculating an average value from sample tree neighbouring pixel values in the ripening Scotch pine forest stands, comparing the results with the measurements of the height in the area. For the update of LiDAR calculated data and LiDAR CFI height results, the increment algorithms of the Latvian State Forest Research Institute ‘Silava’ were used, comparing the results with the sample plot measurements. Both results showed a close correlation – in the case of LiDAR CFI with R2 =0.82, LiDAR data with R2 =0.93, demonstrating a standard deviation: 2.40 and 2.75, accordingly and standard error: 0.11 and 0.13, accordingly. The results indicate that both technologies can be used in the forest management, offering reliable information about the forest inventory. Positive values were reached by minimizing the human error factor, which is problematic for the field inventory.

The share of the renewable resources used continues to grow due to environmental, economic and political reasons. Consequently, intensification of forest management is on-going and expected to continue in the future. Logging residues, such as treetops, branches and stumps, are a significant renewable energy source. Since the logging residues are noticeably richer in nutrients than conventionally harvested stems, there is a concern related to the negative impact of intensified harvesting on the ecosystems, productivity of the sites and sustainability of forestry in general. To evaluate the impact, this study has compared different intensity harvesting effect on the next rotation young stand productivity in eight sites in Latvia. In a nutrient-rich site, the productivity of Norway spruce was higher in the whole-tree harvest (WTH) subplot comparing to stem-only harvesting (SOH) subplot three years after the planting. Productivity of Scots pine in oligotrophic conditions was observed to be higher in SOH subplot comparing to WTH subplot two and three years after planting. Furthermore, in a site on a mineral soil relatively richer in nutrients no significant differences were observed. Comparing WTH to whole tree harvest + stump biomass (SB) extraction subplots, the productivity of Norway spruce was higher in WTH four to five years after the planting; in a mixed stand of Norway spruce and black alder no productivity differences of spruce were detected, but productivity of black alder was higher in WTH+SB subplot five years after the planting; in black alder stands a significantly higher productivity was observed in WTH subplot four and five years after the planting.

Conifer tree stumps are a prospective source of bioenergy, but there are considerable uncertainties and risks associated with this forestry practice, and environmental consequences of stump harvesting are little studied in the Baltic countries. One of the major concerns is related to the risk of nutrient leaching that may cause pollution of watercourses and decline of tree growth in the next forest generation. The main aim of the present study was to estimate the effect of stump harvesting on general soil and soil solution parameters in three clear-cut areas located in Hylocomiosa site type (dominant tree species prior to clearfelling – Picea abies L. (Karst.)) over a period of 6 years after the stump removal. Two types of treatments were compared: whole-tree harvesting with only above-ground biomass removed (WTH) and whole-tree harvesting combined with the stump removal (WTH+SB). We found no acidification effect of soil and soil solution. Soil C and N stocks six years after harvesting were similar in the plots with and without stump removal, and demonstrated similar pattern of change in both studied treatments (WTH and WTH+SB). Nutrient content and patterns of change varied with the site and year, suggesting that the effects are rather site- than treatment-specific.

Forests and woodlands provide a wide variety of ecosystem services that are usually classified within three categories: provisioning services, regulating (supporting) services and cultural services. While provisioning and regulating services are widely analysed, there is a lack of information about the cultural ecosystem services, particularly some sub-categories of these. In this study, we have focused on inspiration for creativity as a sub-category of cultural ecosystem services provided by forests and analysed the depiction of forest ecosystems in landscape paintings of Latvian artists. It may be concluded that forest ecosystems serve as an important source of inspiration for creativity and art, as may be seen in the landscape paintings of Latvian artists of the 20th century. Characteristic landscape features of birth and living places of the artists are reflected in their works. The performed analysis is the first of its kind in Latvia, and it may be further expanded, either by incorporating other aspects of creativity or adding economic dimension, for example, by surveying the art market.

The aim of the paper is to determine the relationship between meteorological drought and hydrological drought in the agricultural basin of the River Osa (northern Poland) in the years 1966-2015. Meteorological droughts appear as a result of insufficient amount or lack of atmospheric precipitation. As a consequence of meteorological droughts occurrences, there appear hydrological droughts which are characterized by low discharges of a river. Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) indicators were used for the identification of droughts at various accumulation periods, i.e. 1, 3, 6, 9 and 12 months. In the years 1966-2015, there were identified from 63 (SPI-1) up to 10 meteorological droughts (SPI-12), while hydrological droughts – from 22 (SPI-1) to 8 (SPI-6, 9 and 12). The strongest relationship between the two kinds of droughts occurred in the periods of accumulation from 9 to 12 months. The values of the correlation coefficient between the meteorological and hydrological droughts were above 0.5 in those cases. Those indicators can be used for a system of early drought warning, which is of particular importance for crop production in agricultural areas. Long-lasting meteorological droughts contribute to increase of water intake for irrigation purposes, thus deepening the hydrological drought. As a consequence of the prolonged and intense hydrological drought, further irrigation may be impossible due to too low river discharges.

Wet areas in agricultural lands are usually not fully or properly managed due to problematic accessibility by heavy machinery and are associated with lower crop yields. There are neither studies regarding spatial distribution of wet agricultural areas in Latvia nor large scale soil maps. Being aware of these wet areas, it would be possible to plan actions for effective management of these areas, starting with a scale of landscape. A geographic information system model could serve as an assistant for decision-making, such as, a direct support for the management of amelioration systems, change of land use and management patterns or granting support payments. Remote sensing data like Sentinel-2 satellite images and LiDAR (Light detecting and ranging) technology can be used to identify local wet areas. The focus of this article is to evaluate different remote sensing indices and methods that can be used to identify wet areas in agricultural lands using open access data and software. From 52 indices, which were analysed with soil moisture field measurements in 33 sample plots, only two of them showed statistical significance in linear regression model (p is less than 0.05): normalized height model in resolution of 25 meters (r2 =0.45) and visible blue spectral band in April (r2 =0.39). Results from this study help to focus on different aspects of remote sensing data usage and methodology for future improvements in order to fully implement LiDAR and Sentinel-2 data for identification of wet areas in agricultural lands.

The traditional valuation of real estate in the field of civil engineering did not include the uncertainty of human behaviour, which cannot be explained by the traditional approach. There are different valuation methods for real estate appraisal, which are basically classified into three groups as a classic, statistical and advanced. In this article, we estimated the different housing price models using the sample of 37 residential apartments in Riga, Latvia, October 2018. In order to evaluate if there is a possible association between the variables involved in relation to the property price, the analytical data were analysed by correlation analysis, analysis of variance (ANOVA), regression analysis, covariance analysis (ANCOVA), principal component analysis (PCA) and cluster analysis. The models estimation results show that using ANCOVA models for the prices forecasting the model fitting to data is less than 58%. The preliminary results of this study suggest that the estimated properties can be distributed in 4 groups, depending on number of rooms, area and age. In addition, the decision tree was created based on algorithms (J48) and a preliminary definition of the best rules was made. The decision tree presents an accuracy of 84% with 31 accepted instances for a total of 37 currently classified instances.

Society aims to develop frames for recognizing important geological and geomorphological sites and features or landscapes within their national and even transnational boundaries. Earth heritage sites educate the general public and preserve cultural and environmental matters. New trends of sustainable development, importance of site conservation are demanding that landforms and landscapes, rocks, minerals, fossils, soils should be protected legally, as they give understanding about the evolution of Mother Earth in local and regional context to generations. The Geopark concept was developed in cooperation with UNESCO and followed a large number of requests to UNESCO from all over the world, from geological institutions and geoscientists and non-governmental organizations, and it became extremely popular and influential to preserve those geological heritage areas, nowadays still recognized only nationally or not at all. This paper aims to give comprehensive overview of existing geoparks in the Baltic Sea Region, as well as analyse aspiring geoparks and unpublished initiatives of potential geopark (Livonia and Vooremaa) eventual establishment in frames of cultural and landscape preservation context. Criteria, requirements and earlier studies are given in context. The geoparks should mainly contain cultural and educational purpose while targeting the least possible damage in preservational aspect.

The research paper focuses on description of the pig (Sus scrofa domestica) farming tendencies in Latvia with the scope to give feeding characteristics in relation to emission outcome. In the recent years the concentration of pigs in farms with a herd size more than 10,000 has increased. With increase of the large farms the average feed consumption is more affected by one operator. Efficient utilization of nutrients content in feeding is crucial to meet environmental goals. It is one of the steps to achieve Nutrient Use Efficiency. There is relationship between crude protein and reduction of reactive nitrogen. Feed content not only affects excreted nitrogen, but also pH of manure and total ammonia Cal nitrogen. It is complex abatement measure to quantify reduction of the emission because of impact of various environmental factors. In Latvia, the most common are sows cross breeds (Yorkshire × Landrace) and on January 1, 2019 the biggest group accounted was fattening pigs with average dry feed consumption per day from 0.33 kg (live weight from 5 to 6 kg) up to 3.6 kg (live weight from 80 to 120 kg) with crude protein value from 163.5 g to 155.3 g per 1 kg feed dry matter. Excreted nitrogen (Nex) was calculated for these groups of pigs less than suggested values in guidelines for emission calculation. The highest calculated total NH3 emission is from fattening pigs group with live weight from 55 to 90 kg although the highest calculated Nex is for lactating sows. NOx also calculates as NO2 and the highest value was 3.23 g per one lactating sow.