Cultivation of Christmas trees is not a very common activity in Estonia at the moment. There are about 290 000 hectares of former agricultural and pasture lands, which are out of use in Estonia (Aastaraamat Mets 2007, 2008). Taking into account the knowhow from Europe, the hypothetical plantation was established and calculation of profitability was made. Profitability of Christmas tree cultivation was compared to the other alternative possibilities of land use. Achieving the output of saleable Christmas trees at least 50%, cultivation of Christmas trees is very competitive compared to other possibilities of land use, but at same time it is also the most capital-intensive.

The paper includes economic research results on the second stage of land reform over the 10-year period (1996–2006) in the districts of Latgale region. The results explicitly stress the region's variability, therefore, the results are different, but common trends can be also observed. The number of land users has decreased, whereas that of land owners and the area of privatised land have increased. The total area of used and owned land has increased by 33.4% and exceeded a million hectares.

The aim of this research is to evaluate the spatial differences of the agricultural economy of Latvia during the First Republic by using spatial autocorrelation calculations. Morans’s I coefficient of spatial autocorrelation is used to describe the spatial relations of the analyzed indicators. The obtained results show that Moran’s I for more than half of the obtained parameters is greater than 0.5, which indicates a rather high spatial autocorrelation. It was observed that variations of the spatial autocorrelation values can be explained by what affects these parameters. Spatial autocorrelation is significantly higher for those parameters whose value depends mainly on the variety of natural factors (land use, specific crop share). Moran’s I value for those parameters whose values depend on the actions by the local government in rural parishes is considerably lower (for example, budget allocation, etc.) A large portion of the examined parameters characterizing the level of parish economic development show the biggest differences when comparing Latgale with the rest of Latvia. In the case of such regional differences, Moran’s I is usually within 0.5–0.7, indicating moderately close spatial autocorrelation. For many indicators regarding agriculture and land use many southern parishes within Jelgavas and Bauskas county show a very considerable difference from the rest of Latvia showing much higher rate of agricultural production.

The aim of this research is to evaluate the spatial differences of the agricultural economy of Latvia during the First Republic by using spatial autocorrelation calculations. Morans’s I coefficient of spatial autocorrelation is used to describe the spatial relations of the analyzed indicators. The obtained results show that Moran’s I for more than half of the obtained parameters is greater than 0.5, which indicates a rather high spatial autocorrelation. It was observed that variations of the spatial autocorrelation values can be explained by what affects these parameters. Spatial autocorrelation is significantly higher for those parameters whose value depends mainly on the variety of natural factors (land use, specific crop share). Moran’s I value for those parameters whose values depend on the actions by the local government in rural parishes is considerably lower (for example, budget allocation, etc.) A large portion of the examined parameters characterizing the level of parish economic development show the biggest differences when comparing Latgale with the rest of Latvia. In the case of such regional differences, Moran’s I is usually within 0.5–0.7, indicating moderately close spatial autocorrelation. For many indicators regarding agriculture and land use many southern parishes within Jelgavas and Bauskas county show a very considerable difference from the rest of Latvia showing much higher rate of agricultural production.

Ecological farming is relevant to protected areas. The aim of the study is to perform an analysis of farms applying organic farming measures as well as the analysis of the change of their areas in Aukštadvaris and Krekenava regional parks (RP). The object of the investigation - the farms of Aukštadvaris and Krekenava regional parks. The study is carried out to determine how many farms, forming the regional parks‘ territory, are managed according to the principles of organic farming. The change of the above- mentioned farming area for 2009-2011 is analyzed as well. Paluknys and Naujamiestis subdistricts, not incorporated into the territory of regional parks, were chosen for the comparison analysis. The analysis of the 2009 – 2011 period showed that the declared areas in Krekenava RP have decreased, and the area of farms applying organic measures has increased by 81.69 hectares (nearly 2.5 times). The number of organic farms increased by 1.5 times in Aukštadvaris RP over the period of 2009-2011, and the area has increased by 187.36 ha. The percentage calculations revealed that in 2011 the area of farms applying organic farming measures in Aukštadvaris RP made up 18.89 per cent of the total area declared, the number of farms - 6.61 per cent. The area of farms applying organic farming measures in Krekenava RP was only 1.71 per cent, measures were applied only by 1.89 per cent of all the declared.

Small rivers are important in terms of water quantity and quality as these rivers collect and deliver water to medium and large rivers downstream. Due to low water flow and high connectivity to adjacent land, small rivers are highly vulnerable to changes caused by natural and anthropogenic factors. This paper aims to assess the chemical and ecological quality of two small rivers including the Slocene and Age as related to dominant land use cover in the contributing area of these water bodies. The effects of land-use patterns and concentrations of chemical substances TN, NO3**- -N, NH4**+ -N, TP and PO4**2- -P in river waters will be determined. The highest concentration of total nitrogen (TN) as measured in the Slocene River was 21 mg LE−1 in spring, while the lowest concentration of TN was 0.86 mg LE−1 in autumn. The highest concentration of total phosphorus (TP) in the Slocene River was 0.14 mg LE−1 in late summer, the lowest was 0.03 mg LE−1 in late autumn. Similarly, in the Age River, the highest concentration of TN was 4.90 mg LE−1 in spring, while TN the lowest concentration of TN was 0.51 mg LE−1 in late autumn. The highest concentration of TP in the Age River was 0.3 mg LE−1 in summer, while the lowest 0.05 mg LE−1 in autumn.

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 study represents results on remote sensing methods based evaluation of land use and land use changes in former and existing peat extraction areas in Latvia. The aim of the study is to elaborate activity data set for the National GHG inventory for the wetlands remaining wetlands for peat extraction. The study results provide sufficient data for application of the default emission factors for the peat extraction sites and flooded lands. Abandoned peat extraction fields, which are not yet afforested, flooded or rewetted, should be reported as peat extraction sites following a conservative approach in application of the emission factors. The study results can be used to report land use changes since 1990; however, linearized approach in calculation of the land use change may result in overestimation or underestimation of GHG emissions in certain periods of time. According to study results, the area of peat extraction sites is considerably bigger than currently reported in the National GHG inventory, mainly due to considerable areas of abandoned peat extraction fields. Flooded lands may be a significant source of emissions and should be introduced in the National GHG inventory to secure consistency of reporting. Methodology for calculation of GHG emissions from flooded lands should be also elaborated. It is also necessary to elaborate emission factors for fertile and no fertile peat extraction sites and continue work on separation of different soils in the inventory to increase accuracy of calculations.

Increase in use of biomass as renewable source of energy in Europe is tightly linked to the policies aimed at mitigation of climate changes i.e. reductions of greenhouse gas emissions. Both for assessment of the carbon sequestration and emissions as well as for assessment of potential amounts of biomass for renewable energy, information of land cover dynamics are essential. Therefore, the aim of our study was to improve accuracy of estimates of the land use changes in the time period between 1990 and 2014. Land use categories were determined in accordance to UNFCCC: wetland, cropland (arable land, bare field), forest, grassland, settlements (urban/suburban area), and other land. Combination of data from National forest inventory (NFI) sample plots and analysis of Landsat images were used. For the classification based on Landsat images vegetation index (NDVI) was estimated and linked to known information on the land use type from NFI sample plot data. In the analysed period, the most significant changes were found for forest lands – the total area of forest land during the last two decades had increased by 1% (64.5 thousand ha). Similar increase (1.2%) was observed also in the area of cropland. Both of these tendencies were primarily the result of marginal field area reduction (by 2.6%). Increase in forest area and thus annual increment has led to an increase in above-ground biomass by 10.2 m**3 haE-1.

Land use efficiency is based on agricultural production. Correct and effective land use could solve several problems – food production, improving the welfare and provision of social stability. The use of land and natural resources is an important issue in the development of the country; therefore, many researchers and scientists have analysed and studied the use of agricultural land and land use efficiency. Efficient land use has an impact on different types of factors, which are mutually contradictory. In the paper several authors researches are analysed, studying influencing factors of the use of agricultural land. Influenced by several factors the main problems associated with the use of agricultural land are the increase of unused agricultural land, the continued degradation of land, but the major problem of land use is the existence of a fragmented property structure. For the efficient use of agricultural land, there are several conditions that need to be met or improved to achieve effective land use. The main conclusion is that analysing the problems that are associated with the use of agricultural land is seen as interactive interaction, as the fragmented property structure is one of the reasons influencing the use of agricultural land, which leads to an increase in unused areas of agricultural land, while unused areas of agricultural land are often overgrown with shrubs while promoting degradation of land.