Achieving Land Degradation Neutrality (LDN) requires tools that identify persistent degradation hotspots for targeted action, moving beyond static monitoring. We present a novel Temporal Frequency Analysis (TFA) that quantifies the repeatability of degradation or improvement trends as a measure of landscape process persistence. It analyzes changes in the land productivity dynamics indicator—the most responsive SDG 15.3.1 component in drylands—across five consecutive five-year periods from 2001 to 2022, using a moving average and a dynamic baseline. This dynamic baseline serves as an analytical reference for temporal diagnostics, complementing rather than replacing the fixed historical baseline used for standardized national reporting. Applied to Turkmenistan's Dashoguz and Lebap provinces, TFA filters climatic noise to reveal spatially explicit, persistent degradation hotspots and improvement bright spots. We found that only a small fraction of the landscape (<1%) exhibits high repeatability of positive or negative trends, indicating that entrenched landscape degradation is hyper-localized. The analysis further reveals how soil-vegetation feedbacks and land-use practices interact to produce contrasting degradation trajectories across different landscape units—from irrigated croplands to desert pastures. The proposed TFA framework is scalable, offering a robust diagnostic tool that links global LDN reporting to local landscape process understanding. Beyond reporting, the framework directly informs the LDN response hierarchy by identifying where to avoid, reduce, or reverse degradation, thereby guiding integrated land-use planning and the LDN accounting mechanism. This provides actionable insights for adaptive land management in dryland regions worldwide. By distinguishing recurrent degradation from temporary variability, TFA strengthens the evidence base for applying the LDN response hierarchy, prioritizing restoration and sustainable land management, and accounting for losses and gains within integrated land-use planning.

The article presents the results of land degradation assessment for the Ryazan and Tula regions based on the concept of land degradation neutrality (LDN). For the first time the approaches were demonstrated for developing a methodology for assessing LDN sub-indicators for humid areas (using the moving average method and modified matrices of changes in land cover type). For forest lands, a matrix modified to take into account the dynamics of woody vegetation, including mutual transitions of coniferous, broad-leaved and small-leaved forests, is proposed. New data on land degradation trends for the studied territories were obtained. The possibility of using the LDN methodology to update official statistics, detail land productivity trends and land use changes is confirmed. Despite the decrease in the degradation rate, in the considered territories, degraded and moderately degraded lands in total still significantly prevail over improved ones, which requires active intervention in regulating land use conditions and the use of new methods. At the same time, the situation in the regions is somewhat different: if in the Tula region degraded lands are mainly confined to the forest-steppe subzone, then in the Ryazan region, foci of degraded lands are equally often found in forest areas. A high dependence of land degradation trends on even short-term (within 5–10 years) climate changes has been revealed. For the Ryazan and Tula regions, such reactions (improvement or deterioration) in individual areas and in the region as a whole can be very contrasting, which requires special consideration when developing measures to adapt to climate change.

Research on the Caspian region has been conducted for over 20 years under the auspices of the Framework Convention for the Protection of the Marine Environment of the Caspian Sea (Tehran Convention). It aims to protect not only the water area of the Caspian Sea, but also areas of land located directly adjacent to it from negative impacts. For the first time, based on the concept of Land Degradation Neutrality (LDN), this work presents the results of a comparative assessment of land conditions for the coastal areas of five states: the Republic of Azerbaijan, the Islamic Republic of Iran, the Republic of Kazakhstan, the Russian Federation, and Turkmenistan. The approach implemented made it possible to identify the main trends in land dynamics in the region under consideration, including for individual countries and regions for different periods of observation. The results are presented in cartographic form. It has been established that most regions of the Caspian region are characterized by a deterioration of the current situation associated with the intensification of degradation processes, and the main “hot spots” of desertification are described. At the same time, the dynamics of land degradation in the Caspian region are multidirectional in individual regions and observation periods. Selecting different comparison periods and baselines can help track changes in land conditions over time and identify peaks of improvement and deterioration.

Despite the large number of different antierosion practices used in the country, the dynamics of the areas of eroded lands remains multidirectional and unstable. The goal of the work was to propose a methodological approach for semantic modeling of sustainable land management with a focus on antierosion measures, the methods for such modeling and land management in the areas prone to soil erosion in order to maintain and restore degraded lands. A variety of erosion control techniques, methods, approaches, technologies and activities described in different sources, including databases on best practices, educational and scientific literature serves as objects of the study. The study was based on the integration of several working hypotheses and approaches proposed by the authors in earlier publications. The methodological basis of these approaches is the concept of land degradation neutrality (LDN) and the principles for assessing the “sustainability” of environmental management based on it. Using the example of several sites, methods for semantic modeling of the sustainability of antierosion land management are considered. These methods are based on assessing the achievement of LDN using so-called “good” practices. For the assessment, the following parameters of the model were applied: “natural potential” (reflecting resource potential, adaptive potential and the ability to self-recovery of land), “expanded potential” (reflecting human improvements in natural potential and the sufficiency of socioeconomic conditions); “actual adverse impacts,” including natural processes and phenomena and those caused by human impact; and “potential adverse impacts,” including natural and anthropogenic risks. Model parameters can be combined in the required combination and reflect different modeling tasks in order to determine the adequacy of erosion control practices, including general approaches and techniques for regional models, methods and technologies for subregional and local ones, and specific activities and measures for local models implemented for individual land plots and farms. The proposed method for visualizing models, based on the construction of radar diagrams, is a flexible solution that provides opportunity to consider the sufficiency of practices, combine them into groups, and also generalize sustainability parameters depending on the goals of modeling.

The revised and updated scientific edition of the previously published glossary and reference book (Land Degradation and Sustainable Land Use, 2018) was prepared as a response to the rapidly expanding concepts in recent years on land degradation and sustainable land use, especially in regions prone to desertification and drought, and climate change. These concepts turn out to be closely intertwined terminologically, which requires the unification of many definitions, especially those borrowed from English-language literature. The edition contains about 800 definitions and terms. The terminology provided corresponds to such categories as: international terminology in the field of land degradation and desertification, including concepts related to the development of the modern approach of land degradation neutrality (LDN); terminology used for the concepts of sustainable land use and adaptation to climate change; concepts describing processes, types and forms of land degradation and their components. The updated edition includes additional terms that reflect a number of socio-economic and humanitarian aspects in the field of land degradation. For geographers, ecologists and other environmental specialists, as well as teachers, students and a wide range of readers interested in the problems of modern land use.

The paper overviews and summarizes the results of the developing a methodology for the land degradation neutrality (LDN) assessment basing on LDN-based studies at national, regional and local levels in Russia. The review of more one hundred available publications in Russian language over the past 6-7 years allowed for analysis on the following areas: development of LDN terminology, LDN assessment at the different levels, adapting transition matrix; application of global and national LDN indicators; using the LDN concept for economic valuation of land, estimating LDN baseline, and using LDN as an integral indicator for sustainable land management. With the LDN concept the issue of land degradation (LD) has gone beyond the limited scope of desertification and drylands, and enlarged the concept of “rational” or “effective” land use and land management dominated in Russia. The LDN concept has been broadened with the introduction of the LDN Index proposed to evaluate the rate of LDN achievement; proposal on reconstructing transition matrices and adding specific land cover sub-categories; approach of integrating traditional national sectoral systems for assessing land quality with an LDN add-on; justification for using additional and specific LDN indicators at national and subnational level (soil erosion, aridity, soil salinity, soil depletion, etc.); importance of factoring natural background trends like climate change, natural succession cycles linked with geological and geomorphological processes; need for using different site-specific LDN baselines, not only those time-based; approaches for LDN-based economic valuation of lands; and the LDN-based typology of SLM practices and models.

The concept of land-degradation neutrality (LDN) is officially adopted at the international level by the UN Convention to Combat Desertification (UNCCD), the methodology for LDN assessment is being implemented as part of assessing the achievement of Goal 15 of the 2030 Agenda for Sustainable Development and is being implemented in statistical systems of the countries of the world. One of the key aspects of creating favorable conditions for achieving LDN is harmonization of the system of national indicators for assessing the state and degradation of land with the system of global LDN indicators. This makes it possible to correct and verify the data of the global assessment of the country provided by the UNCCD, which, ultimately, allows obtaining adequate results that correspond to the actual picture. Based on the results of scientific research conducted in recent years and scientific publications, the article describes the features of the formation of national systems for the LDN assessment in countries that represent different stages of setting and achieving the LDN target: goals have been set, and a methodology for adapting indicators has been developed (Belarus, Kyrgyzstan); goals and indicators are under development (Russia); and goals have not been set, and development of national indicators is in the inception phase (Turkmenistan). The selection of countries is not random and allows tracing the difference in the methodology for adapting national and global indicators for national statistical systems in countries where the principles for assessing the state of land were developed on a single platform created in Soviet times. It was revealed that, despite the similarity of the methodological approaches used, each of the countries is constructing its own unique system of indicators for LDN assessment, taking into account national spatial, geographical, climatic, and other features. The final result of constructing such a system should be a GIS-based system of land-degradation indicators and the ability to interface it with global assessment data (Trends.Earth calculation module), with the land-information system of Belarus being an example of its implementation.

The land structure in dry-steppe Zavolzh'e is complicated and includes irrigated and rain-fed croplands and pastures in natural steppe areas and on abandoned plow lands, which results in significantly incorrect assessment of the Land Degradation Neutrality (LDN) based on standard approaches elaborated to analyze the land status at the global and regional levels. The problem of interpreting the results of the assessment of the dynamics of land cover as one of the main global indicators of LDN proposed by the UN Convention to Combat Desertification is analyzed in this work. A method based on the analysis of seasonal series of Landsat satellite images, using Kohonen self-organizing neural networks implemented in the Scanex Image Processor software package was developed and applied for the study area. It is shown that this approach makes significantly greater the possibilities of assessing the LDN as a result of the detailed analysis and delineation of a larger number of cartographic areas and when using the transition assessment matrix based on the extended classification of the land cover. The application of the Change Detection module of the SAGA GIS software package enables us not only to identify the nature of restoration and degradation changes, but also to compare the trends for land categories. The combination of the proposed approaches in the form of a functional algorithm may be recommended for monitoring and evaluation of the achieving LDN at the local level.

The assessment of land degradation neutrality (LDN) is used to characterize the achievement of the UN Sustain-able Development Goal 15 (SDG), Target 15.3 — «to combat desertification, restore degraded lands and soils» by individual countries and regions. The article presents the calculation of land degradation neutrality for agricultural territories of the Samara region using global indicators (dynamics of land productivity, dynamics of land cover, dynamics of soil organic carbon) and regional ones, such as yield, erosion, content of mobile forms of potassium and phosphorus in the soil. The Trends.Earth tool presented on the Quantum GIS was used to calculate the first two global indicators platform. The evaluation of the remaining indicators was carried out using stock data and data from the agrochemical service. According to the results land degradation neutrality was not achieved in the agricultural territories of the Samara region. The indicator of SDG 15.3.1 («the proportion of land that is degraded over total land area») is 78,61%, and the LDN index is –57,22%. The main process leading to a negative LDN index is water erosion, which leads to a decrease in the levels of indicators such as land productivity and humus content.

The complex structure of the lands of dry steppe Trans-Volga is represented by both natural steppe areas and fallow lands (areas of irrigated and rainfed agriculture), as well as pastures. This is often the reason for the distortion of the results of assessing the land state when using a methodology of land-degradation neutrality (LDN). The concept of LDN was proposed by the United Nations Convention to Combat Desertification (UNCCD) as an international standard to conduct comparative assessments and to analyze the dynamics of land degradation. The work considers the peculiarities of differences in the results obtained using low- and high-resolution space images. Using a ground verification of changes in the soil cover, validation of the proposed method for assessing the land-cover dynamics at the local level is carried out. The method is based on the analysis of seasonal series of Landsat images using self-organizing neural networks realized in a Scanex Image Processor program complex.

On the example of complex analysis of rangeland systems of Kyrgyzstan located in different natural conditions (key objects “Balykchi (Kyok-Moynok),” “Kyok-Oy,” “Suu-Samir”) the possibility of applying the methodology of sustainable land management modeling for assessment and improvement of traditional mountain pastures is shown. The main parameters of sustainable pasture management models for the considered territories were defined including 3 main groups: land potential, adverse impacts (actual processes and phenomena), risk of degradation (potential processes), whose content is divided into 8 subgroups and includes natural conditions and expanded resource potential, ability to self-recovery and sufficiency of socioeconomic conditions, natural and anthropogenic impacts and risks defined for these groups. A systematic list of successful practices in the use of mountain rangelands in Kyrgyzstan has been compiled. The analysis of different practices and their role in maintaining the sustainability of specific models, depending on the baseline situation, biophysical and socioeconomic conditions, has been conducted. The results are summarized and presented in the petal diagrams’ form. It is shown that the effectiveness of sustainable rangeland management models is determined by a set of successful practices. The article reveals a natural growth of volume and diversity of applied practices as the growth of anthropogenic potential of rangeland systems. The proposed approaches can be used as part of the practical management of rangelands by pastoralist societies and are included as methodological recommendations for the development of rangeland legislation and the assessment of the effectiveness of rangeland livestock, taking into account the completeness of the set of practices and technologies applied in different natural conditions.

A scientific approach to the assessment of trends in land changes based on the novel concept of Land Degradation Neutrality (LDN) was applied to monitor the sustainability of irrigated farmlands in test areas in Uzbekistan (the Andijan, Namangan, Fergana, and Syrdarya regions). The tool "Trends.Earth", which was recommended by the UN Convention to Combat Desertification and developed as a special plugin for the Quantum GIS platform, was used to describe the dynamics of land degradation in the period 2001-2020. This study demonstrates the results of monitoring land productivity dynamics that reflect the investments in irrigation improvement during the last 10-15 years. A comparison between changes in land productivity measured via Normalized Difference Vegetation Index and its average value for the entire observation period is more informative than comparison with the initial 5-year period. More details could be noted through application of the "moving average" calculation method. The described trends demonstrate that the use of sustainable land management practices in the last decade led to a decreasing proportion of degraded lands compared to the average figure for the period 2001-2020 (from 25-40% to 10-20%). This trend is confirmed by reviewing state statistics and indicates the success of national policies and approaches to adaptation. However, the dynamics of land productivity in the study areas is diverse and includes "dry" and "humid" extremes, depending on climate fluctuations. Despite the generally positive trends identified across regions, the high dynamics of degraded hotspots and improved lands within certain areas confirm the instability of ongoing changes.

The active development of the concept of sustainable land management (SLM) is inextricably linked with approaches to land degradation neutrality (LDN). It is considered that so-called good land management practices make it possible to prevent or reduce the risk of land degradation and reverse it while maintaining the productivity potential and ecosystem functions. Based on analysis of the correspondence of good practices to SLM parameters and the hierarchy and typology of land management developed on this basis (with the categories of practice, model, type, class), it is shown that individual practices and technologies do not always lead to the achievement of land degradation neutrality and, conversely, it is not always achieved by sustainable land management approach. SLM modeling using qualitative rating scales and radar charts has shown high effectiveness in visualizing the integrity of models and adjusting them to achieve the best result. An improved typology is proposed with three main classes of land management: simple, supported, and expanded. Particular attention is paid to the other forms class, which includes natural functioning, long-term abandonment of land, and destructive land management. An algorithm scheme to recognize sustainable land management in the case of land degradation is proposed, as is an inverse algorithm to achieve land degradation for different land management models. A hypothesis has been put forward about the landscape‒ecological framework of SLM, which makes it possible to explain the causes of the discrepancy between the estimates of LDN for objects of different scales: achieving land degradation neutrality in a certain territory is possible not so much by continuous coverage of this territory with good SLM practices as by preserving the framework of SLM models, types, and classes.

Determination of national goals for achieving a land degradation neutrality (LDN) and the creation of systems of indicators for monitoring is an important strategic task for combating desertification and preventing land degradation in Turkmenistan, due to the implementation of target 15.3 of the UN Sustainable Development Goals for the period up to 2030. This paper analyzes the possibility of integrating global indicators of the LDN into the National System for Land Monitoring of Turkmenistan, which is currently being developed, and provides statistical and geoinformation data for the entire territory of the country. It has been found that, despite the new important data obtained using global approaches, reliable monitoring of the LDN based on national data is not fully feasible at present due to the fact that global indicators are not sufficiently confirmed by the available national data and do not correspond to global proxy indicators of dynamics of land cover, productivity, and stocks of soil organic carbon. This article proposes a working list of national analogue indicators and ways to validate them, as well as options for using lists of land use types to compile a matrix of negative and positive transitions with changes in land cover. It is recommended to use cartographic and fund data collected and processed in the late 1980s–90s as a “baseline” for monitoring land degradation, as well as materials on the assessment of the state of specially protected natural areas. Additional and alternative indicators of the LDN, which are of particular importance for Turkmenistan: salinization of soils and lands, soil deflation, climate aridity, and dust storms, are proposed.

In 2013, the United Nations Convention to Combat Desertification (UNCCD) established a science–policy interface (SPI) to address Parties’ need for demand-driven, timely, interdisciplinary science and technical knowledge to tackle problems of desertification, land degradation and drought. Since then, a comprehensive assessment of the SPI’s impacts on policy decision-making has been lacking, despite perceptions that the SPI is vital to the Convention’s success. Addressing this gap, this paper evaluates whether the SPI and its processes and outputs have provided the necessary scientific and technological knowledge and advice to Parties to support timely, evidence-informed decision-making. It applies an analytical framework to assess performance metrics, considering associated documents and evidence of societal relevance and social quality. The findings indicate that SPI outputs have improved implementation of the UNCCD since 2015, particularly in the context of Sustainable Development Goal Target 15.3. SPI outputs have supported scientific cooperation between the Convention and its strategic partners while enhancing its science and technology profile in line with Article 16 and Article 17. The findings indicate that further formalization of the SPI’s status within the UNCCD is vital to improve its functions, undertake its work, and enable the UNCCD to maintain its global lead in providing knowledge and advice on combating desertification, land degradation and drought.