Anthropogenic development of forest-steppe landscapes has a long-term character. For the landscape-geochemical systems of the forest-steppe, under the conditions of the prevalence of vertically directed geochemical flows, the main limiting factor of functioning is the presence of a sufficient amount of atmospheric precipitation. Geochemical monitoring is carried out on the territory of the Kursk Biosphere Station, one of the purpose of which is to study the atmogeochemical component of forest-steppe landscapes. It is shown that atmogeochemical indicators - dustiness of the atmosphere, pollution of atmospheric precipitation, snow cover - can act as indicators of geochemical degradation of landscapes. For the assessment of atmospheric pollution of the natural landscape and definition of air routes of migration of the elements of a permanent atmogeochemical monitoring is required.

<p>Specific features of current semiarid landscape along the Eastern Caucasus foothills (so-called Dagestan extra-mountain region) are badlands formed on loess and clay deposits. The active piping, erosional and gravitational processes present a direct hazard for extensive grazing activities and infrastructure facilities accommodated here. The badlands topography is complicated with the abundance of diverse pseudokarst forms such as blind valleys, caverns, different sized and shaped sinkholes. Such typical patterns as chains of elongated sinkholes, marking the direction of underground flow along the bottoms of erosional forms, are rather distinguishable on satellite imagery with submeter spatial resolution. However, the real density and morphometric analysis of surface pseudokarst forms can be well mapped and analyzed only by means of remote sensing data with ultrahigh spatial and vertical resolution (about several decimeters). For the area in study we used UAV-derived data from 100 m altitude of survey to produced Digital Terrain Model (DTM) with resolution of 20 cm. The automatic extraction of DTM’s for semiarid badland with sparse desert steppe vegetation was rather simple but there is obvious limitations of using UAV data for morphometric analysis of the badland were manifested in the formation of the so-called "dead zones" in case of the large and deep sinkholes. For a complete three-dimensional reconstruction of the badland topography, the terrestrial laser scanning data were additionally involved.</p><p>As a result of the analysis of the DTM with very high resolution, derived highly-detailed morphometric and hydrological models were built, reflecting the complex structure and genesis of the badland topography. Automatic identification and mapping of sinkholes reveal the prevalence of large sinkholes with a diameter of 5-15 m and a depth of 1-3 m along the erosional valleys for the study area. Along the slopes more smaller sinkholes forms (up to 0.3 m in diameter and up to 1 m in depth) were identified, the complex network of gullies and micro-terraces pattern were clearly reconstructed. Identification and mapping of sites with high susceptibility to current processes of different genesis was done: in particular, the identified closed catchment micro-basins are areas of predominance of piping processes, while the escarpments in the upper parts of the steep slopes of the badlands are most affected by erosional processes with formation of micro-gullies.</p><p>Under regular monitoring of piping, erosional and gravitational processes remodeling the badland topography, it is necessary to carry out multitemporal UAV surveys at low altitudes along with terrestrial laser scanning data. Such complex approach will make it possible to identify more reliably the current ratio of surface and groundwater runoff, and to early allocate and warn the hazardous geomorphological processes.</p>

The algorithms for quantitative estimates of various structural and functional parameters of forest ecosystems, particularly boreal forests, on high resolution remote sensing data are actively developing since the mid-2000s. For monitoring of forest ecosystems located at the Northern limit of distribution, effective not only lidar data but also the optical data obtained by unmanned aerial vehicles (UAV's) with ultra-low altitude photography and derived products resulting from modern algorithms for the photogrammetric processing.High-detail remote sensing from UAV's is a key level of monitoring of Northern forests at a large-scale level, ensuring the correct transition from sub -satellite ground-based studies to thematic products obtained from multi-time Hyper-and multispectral data of medium and relatively high resolution (MODIS, LANDSAT, Sentinel-2).When planning and conducting specific case studies based on UAV data, special attention should be paid to the justification of the survey methodology. In particular, the choice of a strictly defined high-altitude echelon of the survey determines the recognition of the objects of study and the possibility of reliable determination of its properties and features. To study the parameters of forest ecosystems at the level of individual trees and at the level of forest plantations, we selected two different-height echelons of survey from ultra-low altitudes: from 50 m, which allowed us to obtain ultra-high-detailed data for each sample area provided by detailed ground-based studies with sub-tree account, and from 100 m-to obtain derived characteristics of forest communities within the area equivalent to 3 pixels of thematic MODIS products with a spatial resolution of 250 m. The data of optical survey with UAV were obtained in July 2018 for 22 plots located in the central part of the Kola Peninsula and representative of different types of North taiga stands and their dynamics under climate change.At the stage of preprocessing images were obtained dense point clouds, characterizing both vertical and horizontal structure of stands. Digital terrain and terrain models and tree canopy models were obtained after cloud filtering and classification. Algorithms of automated segmentation and classification have been developed and tested to obtain such characteristics of stands as the height of individual trees, the area of crown projections, the projective cover of the treeshrub layer. The obtained characteristics are aggregated by cells of a regular network with the dimension corresponding to the spatial resolution of Sentinel-2 and Landsat -8 data.The main results of the works are digital spatial datasets for 22 sample plots: raw data with very high resolution imagery (optical images with very high resolution, dense point clouds, RGB-orthophoto) and create based on a thematic derivative products (digital terrain model, topography, tree canopy cover; map of the heights and projections of the crowns of trees, percent cover of tree and shrub vegetation).