Wheat is the most important food crop in Mongolia, most of the croplands are utilizing for wheat cultivating area in the central northern region of Mongolia. The Mongolian government has several policies on the agricultural sector with wheat production in the study region has been intensified to meet people’s food demands and economic development. Monitoring wheat-growing areas is thus important to developing strategies for food security in the region. In the present study, we aimed to develop an agricultural application method using remote sensing data. Sentinel-1 SAR and Sentinel-2 MSI analysis of time series data were carried out to monitor the wheat crop growth parameters. Time-series images were acquired during May 2019–September 2019 at different growth stages in Bornuur soum, Tuv province of Mongolia. The wheat crop parameters, i.e. normalized difference vegetation index, vegetation water content, backscatter value of VV, VH channels were estimated using remote sensing data with reference data as cadastre polygons of current cropland area. The results showed that provide timely and valuable information for agricultural production, management and policy-making. The agricultural application method will help to agriculture management and monitoring include crop identification and cropland mapping, crop growth monitoring, inversion of key biophysical, biochemical and environmental parameters, crop damage/disaster monitoring, precision agriculture, etc.

In the context of global climate change, a comprehensive understanding of the spatiotemporal impacts of drought on vegetation productivity is essential for assessing terrestrial ecosystem stability. Utilizing outputs from six global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), this study systematically assessed historical and projected drought probability, the drought vulnerability of Net Primary Productivity (NPP), and overall drought risk across the Mongolian Plateau under three Shared Socioeconomic Pathway scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Results revealed that the Standardized Precipitation Evapotranspiration Index (SPEI) exhibited a declining trend, whereas NPP showed an overall increasing trend. These changes were most pronounced under the SSP5-8.5 scenario, with the SPEI decreasing at a rate of −0.39/10a and NPP increasing at 25.8/10a. Drought severity exhibited strong spatial heterogeneity, intensifying from northeast to southwest, whereas NPP demonstrated an inverse spatial pattern. The spatial distribution of high-drought-risk zones varied markedly across scenarios: the southwestern region was most affected under SSP1-2.6, the northwestern region under SSP2-4.5, and the southeastern region under SSP5-8.5. Based on 12-month SPEI values and NPP derived from the Carnegie–Ames–Stanford Approach (CASA) model, SSP2-4.5 presented the highest overall drought risk, despite lower emissions. The annual mean NPP drought vulnerability ranked as follows: SSP2-4.5 (0.60 $\mathrm{g}\mathrm{C}{\mathrm{m}}^{-2}{\mathrm{y}\mathrm{r}}^{-1}$) > SSP1-2.6 (−1.03 $\mathrm{g}\mathrm{C}{\mathrm{m}}^{-2}{\mathrm{y}\mathrm{r}}^{-1}$) > SSP5-8.5 (−1.24 $\mathrm{g}\mathrm{C}{\mathrm{m}}^{-2}{\mathrm{y}\mathrm{r}}^{-1}$). Projections indicated a substantial increase in drought occurrence probability during the period 2061–2100, particularly under SSP2-4.5 and SSP5-8.5. Under higher emissions, the spatial extent of areas with negative drought vulnerability values was expected to expand 68%. Wind speed was the dominant factor influencing drought risk under SSP1-2.6 and SSP2-4.5, whereas precipitation became the primary driver (45.34%) under SSP5-8.5. These findings offer critical insights for early drought warning systems and for strengthening ecosystem resilience across the Mongolian Plateau.

Desertification and land degradation represent some of the most pressing and complex environmental challenges facing Mongolia today. According to desertification assessments, approximately 77.8% of the country’s total territory shows signs of land degradation to varying degrees. The manifestation of desertification and degradation differs across natural zones and is influenced by multiple factors, including climate change, human activity, overgrazing, and water scarcity. For instance, in the forest steppe zone, major contributors include deforestation, intensive agriculture, and pasture overload; in the dry steppe zone, vegetation cover reduction and overgrazing are prevalent; while in the desert steppe, increasing wind erosion and sand movement, along with deteriorating vegetation, are common indicators.This study investigates the changes in land cover associated with drought, desertification, and land degradation between 1985 to 2022 in three representative soums across Mongolia’s forest steppe, dry steppe, and desert steppe zones. The research methodology was developed in accordance with international standards and adapted to the specific environmental context of Mongolia. It integrates satellite remote sensing data, ground-based observations, and socio-economic indicators to conduct spatiotemporal analysis. Key indicators used in the assessment include drought intensity and frequency, wind and water erosion, vegetation cover change, and the population and livestock density. The results reveal significant spatial disparities in land degradation across the studied regions. The case studies of Orkhon soum (Darkhan-Uul province), Rashaant soum (Bulgan province), and Govi-Sumber aimag highlight strong interrelations between drought variability, land cover change, vegetation degradation, socio-economic factors, and overall land degradation. The findings show that 83.9% of Orkhon soum, 49.8%, of Rashaant soum, and 99.02% of Govi-Sumber aimag have been affected to varying degrees by fluctuating and desertification and land degradation to some extent. This research is significant in that it focuses on the soum level representing localized areas within distinct ecological zones offering valuable insights for targeted policy and land management interventions. Since implementation of mitigation strategies at the soum level falls under a single administrative authority, the potential for effective decision-making and action is considerably enhanced. Монгол орны байгалийн ялгаатай бүсүүд дэх сумдын цөлжилт, газрын доройтлын асуудал ХУРААНГУЙ: Монгол улсад өнөөдөр хамгийн ноцтойгоор илэрч байгаа хүрээлэн буй орчны асуудлуудын нэг нь цөлжилт ба газрын доройтол юм. Цөлжилтийн үнэлгээгээр нийт нутаг дэвсгэрийн ойролцоогоор 77.8 хувьд ямар нэг хэмжээгээр газрын доройтол илэрч байна. Иймээс цөлжилт газрын доройтол нь байгалийн бүсүүдэд харилцан адилгүй бөгөөд уур амьсгалын өөрчлөлт болон хүний үйл ажиллагаа, мал аж ахуйн хэт ачаалал, усны хомсдол зэрэг олон хүчин зүйлээс шалтгаалж ялгаатай шинжээр илэрч байна. Жишээ нь хангайн бүсэд газар тариалан, ойн хомсдол, бэлчээрийн ачаалал их байхад хээрийн бүсэд ургамлан нөмрөг багсаж, бэлчээрийн даац хэтрэх, говийн бүсэд салхи шуурганы давтамж нэмэгдэж элсний нүүлт нэмэгдэх ургамлан нөмрөг муудах гэх мэт олон шинжээр илэрч байна. Энэхүү судалгаа нь Монгол орны байгалийн бүсүүд болох ойт хээр, хуурай хээр, цөлөрхөг хээрийн бүсийг төлөөлүүлэн 3 сумдын газар нутгийн 1985-2022 оны хоорондох ган, цөлжилт ба газрын доройтол газрын бүрхэвчийн өөрчлөлтийг судалж дүн шинжилгээ хийв. Судалгааны арга зүйг олон улсын стандартын дагуу Монгол орны онцлогт тохируулан боловсруулж, хиймэл дагуулын болон газрын мэдээлэл, нийгэм эдийн засгийн үзүүлэлт дээр үндэслэн цаг хугацаа, орон зайн дүн шинжилгээг хийсэн. Үнэлгээнд гангийн эрчим, давтамж, салхи усаар элэгдэх хөрсний эвдрэл, ургамлын бүрхэвчийн өөрчлөлт, хүн ам болон малын нягтшил зэрэг олон үзүүлэлтүүд багтсан. Судалгааны үр дүнд газрын доройтол бүс нутгийн хэмжээнд эрс ялгаатай байгааг харуулж байна. Дархан-Уул аймгийн Орхон сум, Булган аймгийн Рашаант сум, Говьсүмбэр аймгийн жишээ судалгаанууд нь гангийн хэлбэлзэл, газрын бүрхэвчийн өөрчлөлт болон ургамлан бүрхэвч, нийгэм эдийн засгийн үзүүлэлтүүд, газрын доройтол хоорондын хүчтэй уялдаа холбоог илэрхийлж байна. Нэгдсэн үр дүнгээр Орхон сумын нийт нутаг дэвсгэрийн 83.9%, Рашаант сумын 49.8%,...