An analysis of the landscape spatial structure and diversity in the mountain ranges of Northeast Siberia is essential to assess how tundra and boreal landscapes may respond to climate change and anthropogenic impacts in the vast mountainous permafrost of the Arctic regions. In addition, a precise landscape map is required for knowledge-based territorial planning and management. In this article, we aimed to explore and enhanced methods to analyse and map the permafrost landscape in Orulgan Ridge. The Google Earth Engine cloud platform was used to generate vegetation cover maps based on multi-fusion classification of Sentinel 2 MSI and Landsat 8 OLI time series data. Phenological features based on the monthly median values of time series Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), and Normalized Difference Moisture Index (NDMI) were used to recognize geobotanical units according to the hierarchical concept of permafrost landscapes by the Support Vector Machine (SVM) classifier. In addition, geomorphological variables of megarelief (mountains and river valleys) were identified using the GIS-based terrain analysis and landform classification of the ASTER GDEM scenes mosaic. The resulting environmental variables made it possible to categorize nine classes of mountain permafrost landscapes. The result obtained was compared with previous permafrost landscape maps, which revealed a significant difference in distribution and spatial structure of intrazonal valleys and mountain tundra landscapes. Analysis of the landscape structure revealed a significant distribution of classes of mountain Larix-sparse forests and tundra. Landscape diversity was described by six longitudinal and latitudinal landscape hypsometric profiles. River valleys allow boreal–taiga landscapes to move up to high-mountainous regions. The features of the landscape structure and diversity of the ridge are noted, which, along with the specific spatial organization of vegetation and relief, can be of key importance for environmental monitoring and the study of regional variability of climatic changes.

In the Republic of Sakha (Yakutia), there are 63 territories of traditional land use of the Indigenous Minorities of the North within the boundaries of municipal districts and nasleg (lowest municipal division), as well as nomadic tribal communities. Almost 58 % of the republic’s territory is under the traditional land use status. The traditional use of natural resources and traditional lifestyles of indigenous peoples are inextricably linked to the resource potential and ecological state of natural landscapes. The paper is aimed to develop a standardized methodology for the design of a small-scale landscape map of traditional land use in the Republic of Sakha (Yakutia). Based on the review of atlas approaches to landscape structure mapping of protected natural areas, we propose to use a multi-thematic dataset of geospatial layers according to the criteria of the classification of typological, regional and basin categories of landscapes. The dataset includes layers from previously published landscape maps and permafrost-landscape regionalization maps, soil-vegetation maps, and global geospatial data for Hammond relief regions, GMTED2010 digital elevation model and HydroBASINS river basins. Methods for delineation of mapped units include overlay geoprocessing, zonal statistics, and relief analysis. For the basemap, the description of typological landscape units includes landscape subclass-genus-type(subtype) and terrain type. The methodology was tested for the Ust-Maiskij district with predominance of mountain taiga and mid-taiga landscapes and Eveno-Bytantaiskij national district with predominance of mountain-tundra, mountain-woodland and north taiga landscapes. The obtained landscape maps contain 36 typological units that synthesize 6 subclasses, 7 landscape types (subtypes) and 12 terrain types by 5 landscape provinces and large river basins (Lena, Yana, Omoloi and Aldan). Thus, the proposed landscape mapping methodology covers the holistic spatial structure of the leading components, allowing for a multidimensional approach to territorial planning and functional zoning of traditional land use.

In this article we present the results of landscape structure study in the Middle Lena valley (Erkeni, Ensieli and Tuimaada), made using GIS mapping based on Sentinel 2 satellite images and ASTER GDEM datasets. Alas complexes and croplands were identified using K-means image segmentation with different initial numbers. Three machine learning algorithms were tested for pixel-based land cover classification. The best result was achieved with the Support Vector Machine classifier. The mapping revealed the landscape structure of 20 spatial units, which were organized into groups of upland, alas, slope, valley and floodplain landscapes. The contrasting landscape structure of the Middle Lena valley was revealed. The northern Ensieli valley is characterized by the predominance of forest larch-pine landscapes, alas complexes mostly dry with steppe meadows are widespread in the watershed. The slopes are dominated by larch forests with patches of birch. The central Tuimaada valley is the most anthropogenically transformed, here steppe meadows and anthropogenic steppes dominate. The plateau part is mainly forested with croplands. The southern valley of the Erkeni is characterized by the smallest area of the valley part dominated by steppe meadows, the slopes of the main bank of the southern and south-eastern exposition are covered with xerophytic meadows. The landscape structure of valleys, floodplain and plakor parts largely determines the specifics of agricultural land use of the local population. The results obtained can be used for further research into the response of permafrost landscapes of the Middle Lena valleys to increased anthropogenic pressure in the context of climate change.

Understanding the dynamics of human-modified natural landscapes after the minimization of anthropogenic impact is an important aspect of dynamic landscape science. The problem of formation of abandoned rural settlements has background and tendencies to intensify in the conditions of urbanization.   The aim of this study is to identify the features of post-anthropogenic transformation of rural settlement landscapes for the abandoned village of Ust-Yudoma in the Ust-Maysky District of the Sakha Republic (Yakutia). The study region is in the middle taiga landscape zone with continuous permafrost. The landscape structure of the study area consists of 12 typological units mapped based on field studies and interpretation of remote sensing data. It is noted that anthropogenically-modified landscapes are divided into three types according to vegetation associations: young growth of pine, raspberry-hipberry mixed herbaceous communities and ivanchai-grass meadows. Multitemporal Landsat images were analyzed to identify key stages of post-anthropogenic landscape dynamics. Maps of the main landscape cover types were compiled using the Semi-Automatic Classification Plagin plugin according to the Random Forest algorithm. A significant part of the village territory is characterized by poorly disturbed pine lingonberry forests with participation of birch on permafrost-taiga loamy soils. The most anthropogenically disturbed territories of private homestead plots consist of raspberry thickets with participation of willow-grass meadows and pine overgrowth on permafrost-taiga loamy soils. Using the images from 1986 to 2024, the stages of pine forest regeneration in the non-forested areas of the village were established. The study of post-anthropogenic dynamics allows us to understand how natural landscapes recover after the cessation of human activity. This contributes to the development of theoretical models of natural processes, the development of effective land resource strategies, and helps to predict further changes in rural landscapes.