Lease of farm lands is the most important process of proprietorial changes in the state’s agriculture sector. As an effect of turbulent socio-economic conditions and legal solutions resulting from country’s agricultural politics, its share in land’s management has significantly shrunk. Currently there is around 1.1 million ha of land in lease, which makes up for 23% of the land acquired by the Agricultural Property Agency of the State Treasury. After 23 years of 3.2 million ha of lands acquired by the Resource (68.5%) has already been managed permanently and 2.5 million ha (53%) have been sold. Lease allows fast temporary management of the farm lands acquired by the State’s Treasury, and a buying- out, mostly by the hitherto leaseholders, afterwards. The range and the structure of area of sales agreement of farm lands indicates that it was acquired by a relatively small group of buyers. Such a structure of permanent management of the State’s Treasury’s farm lands might bring some hesitations and questions on rationality of the proprietorial changes from the social interest view and ethics.

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.

According to EU Water Framework Directive, anew model of land reclamation management and financing will be developed. Taking into consideration the high vale of state investment required to ensure a steady work of land reclamation systems, it is important to reject the funds allocated on an equality principles and to give preference to the regions where the maintenance, rehabilitation and repair of these structures is more effective. The discussion concerning the allocation of state funds is elaborated in this paper. On the basis of statistical analysis, natural and economical regional differences were evaluated. Four scenarios of the allocation of special subsidies from state budget are submitted for approval. When modelling the financing results based on the regional distribution methodology, the changes in base financing indices are under discussion.