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As a result of the unique geographical characteristics, pastoral lifestyle, and economic conditions in Mongolia, its fragile natural ecosystems are highly sensitive to climate change and human activities. The normalized difference vegetation index (NDVI) was employed in this study as an indicator of the growth status of vegetation. The Sen’s slope, Mann–Kendall test, and geographical detector modelling methods were used to assess the spatial and temporal changes of the NDVI in response to variations in natural conditions and human activities in Mongolia from 1982 to 2015. The corresponding individual and interactive driving forces, and the optimal range for the maximum NDVI value of vegetation distribution were also quantified. The area in which vegetation was degraded was roughly equal to the area of increase, but different vegetation types behaved differently. The desert steppe and the Gobi Desert both in arid regions have degraded significantly, whereas the meadow steppe and alpine steppe showed a significant upward trend. Precipitation can satisfactorily account for vegetation distribution. Changes of livestock quantity was the dominant factor influencing the changes of most vegetation types. The interactions of topographic factors and climate factors have significant effects on vegetation growth. In the region of annual precipitation between 331 mm and 596 mm, forest vegetation type and pine sandy soil type were found to be most suitable for the growth of vegetation in Mongolia. The findings of this study can help us to understand the appropriate range or type of environmental factors affecting vegetation growth in Mongolia, based on which we can apply appropriate interventions to effectively mitigate the impact of environmental changes on vegetation.

Very high resolution (VHR) remote sensing change detection (CD) is crucial for monitoring Earth’s dynamics but faces challenges in capturing fine-grained changes and distinguishing them from pseudo-changes due to varying acquisition conditions. Existing deep learning methods often suffer from information loss via downsampling, obscuring details, and lack filter adaptability to spatial heterogeneity. To address these issues, we introduce Information-Preserving Adaptive Convolutional Network (IPACN). IPACN features a novel Information-Preserving Backbone (IPB), leveraging principles adapted from reversible networks to minimize feature degradation during hierarchical bi-temporal feature extraction, enhancing the preservation of fine spatial details, essential for accurate change delineation. Crucially, IPACN incorporates a Frequency-Adaptive Difference Enhancement Module (FADEM) that applies adaptive filtering, informed by frequency analysis concepts, directly to the bi-temporal difference features. The FADEM dynamically refines change signals based on local spectral characteristics, improving discrimination. This synergistic approach, combining high-fidelity feature preservation (IPB) with adaptive difference refinement (FADEM), yields robust change representations. Comprehensive experiments on benchmark datasets demonstrate that IPACN achieves state-of-the-art performance, showing significant improvements in F1 score and IoU, enhanced boundary delineation, and improved robustness against pseudo-changes, offering an effective solution for very high resolution remote sensing CD.

The complexity of land types and the limited spatial resolution of Synthetic Aperture Radar (SAR) imagery have led to widespread mixed-pixel contamination in radar backscatter images. The radar backscatter echo signals from a mixed pixel are often a combination of backscattering contributions from multiple endmembers. The signal mixture of endmembers within mixed pixels hinders the establishment of accurate relationships between pure endmembers’ parameters and the corresponding backscatter coefficient, thereby significantly reducing the accuracy of surface parameter inversion. However, few studies have focused on decomposing and estimating the pure backscatter signals within mixed pixels. This paper proposes a novel approach based on hyperspectral unmixing techniques and the microwave backscatter contribution decomposition (MBCD) model to estimate the pure backscatter coefficients of all Endmembers within mixed pixels. Experimental results demonstrate that the model performance varied significantly with endmember abundance. Specifically, high accuracy was achieved in estimating soil backscattering coefficients when vegetation coverage was below 25% (R2≈0.88, with 98% of pixels showing relative errors within 0–20%); however, this accuracy declined as vegetation coverage increased. For grass endmembers, the model maintained high estimation precision across the entire grassland area (vegetation coverage 0.2–0.8), yielding an of 0.80 with 83% of pixels falling within the 0–20% relative error range. In addition, the model performance is influenced by the number of endmembers.

Dust emission is a common catastrophic weather phenomenon in Northern China. This phenomenon not only causes environmental problems, such as air pollution, but also has an important impact on the global dust cycle and climate change. On the basis of the dust weather observation data of 44 surface meteorological stations in the Tarim Basin from 1989 to 2021, combined with the dust aerosol optical depth (DAOD), dust surface mass concentration (DUSMASS) and wind speed data, this paper analyses the spatial and temporal dust weather characteristics in the Tarim Basin over the past 33 years. Results show that the frequency of dust weather in the Tarim Basin has declined in the past 33 years. Dust weather mainly consisted of floating dust, followed by blowing dust and dust storm. This weather had a significant seasonal change, with more dust in spring and summer and less in autumn and winter. The dust weather was mainly distributed along the south edge of the Tarim Basin and the desert hinterland of Tazhong. The spatial distribution of the dust intensity (DI) index was basically consistent with the dust weather days. Moreover, the DAOD was obviously affected by dust weather and had a significant positive correlation with the number of dust weather days and the DI, suggesting the vertical concentration of dust particles to a certain extent. Wind is also one of the most important factors affecting the release of dust. The frequency of strong wind weather decreases from the northeast to the southwest, which corresponds to the distribution of the DUSMASS.

The terminal branch orders of plant root systems have been proposed as short-lived ‘ephemeral’ modules specialized for resource absorption. The occurrence of ephemeral root modules has so far only been reported for a temperate tree species and it is unclear if the concept also applies to other woody (shrub, tree) and herb species. Fine roots of 12 perennial dicotyledonous herb, shrub and tree species were monitored for two growing seasons using a branch-order classification, sequential sampling and rhizotrons in the Taklamakan desert. Two root modules existed in all three plant functional groups. Among the first five branch orders, the first two (perennial herbs, shrubs) or three (trees) root orders were ephemeral and had a primary anatomical structure, high nitrogen (N) concentrations, high respiration rates and very short life spans of 1–4 months, whereas the last two branch orders in all functional groups were perennial, with thicker diameters, no or collapsed cortex, distinct secondary growth, low N concentrations, low respiration rates, but much longer life spans. Ephemeral, short-lived root modules and long-lived, persistent root modules seem to be a general feature across many plant functional groups and could represent a basic root system design.

The ecological system of the desert/grassland biome transition zone is fragile and extremely sensitive to climate change and human activities. Analyzing the relationships between vegetation, climate factors (precipitation and temperature), and human activities in this zone can inform us about vegetation succession rules and driving mechanisms. Here, we used Landsat series images to study changes in the normalized difference vegetation index (NDVI) over this zone in the Sahel region of Africa. We selected 6315 sampling points for machine-learning training, across four types: desert, desert/grassland biome transition zone, grassland, and water bodies. We then extracted the range of the desert/grassland biome transition zone using the random forest method. We used Global Inventory Monitoring and Modelling Studies (GIMMS) data and the fifth-generation atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5) meteorological assimilation data to explore the spatiotemporal characteristics of NDVI and climatic factors (temperature and precipitation). We used the multiple regression residual method to analyze the contributions of human activities and climate change to NDVI. The cellular automation (CA)-Markov model was used to predict the spatial position of the desert/grassland biome transition zone. From 1982 to 2015, the NDVI and temperature increased; no distinct trend was found for precipitation. The climate change and NDVI change trends both showed spatial stratified heterogeneity. Temperature and precipitation had a significant impact on NDVI in the desert/grassland biome transition zone; precipitation and NDVI were positively correlated, and temperature and NDVI were negatively correlated. Both human activities and climate factors influenced vegetation changes. The contribution rates of human activities and climate factors to the increase in vegetation were 97.7% and 48.1%, respectively. Human activities and climate factors together contributed 47.5% to this increase. The CA-Markov model predicted that the area of the desert/grassland biome transition zone in the Sahel region will expand northward and southward in the next 30 years.

Accurate estimation of vegetation Net Primary Productivity (NPP) has important theoretical and practical significance for ecological environment governance, carbon cycle research, and the rational development and utilization of natural resources. In this study, the spatial characteristics, temporal changes, and driving factors of NPP in the Conventional Lake Chad Basin (CLCB) were based on MODIS data by constructing a Carnegie Ames Stanford Approach (CASA) model and using a combination of Residual trends (RESTREND) and correlation analysis. The results showed that from 2001 to 2020, the NPP of the CLCB decreased annually (1.14 g C/m2), mainly because of overgrazing, deforestation, and large-scale irrigation. We conducted a driving factor analysis and found that the main influencing factor of the NPP of the CLCB is high-intensity human activities, including farmland reclamation and animal husbandry. Although the impact of climate change on NPP is not obvious in the short term, climate change may help recover NPP in the long term. The continued reduction in NPP has greatly increased the difficulty of regreening the Sahel; the increase in population density and rapid urbanization have led are major contributing factors to this. Our findings have important implications for the continued implementation of stringent revegetation policies. However, owing to limited data and methods, only the overall change trend of NPP was obtained, and comprehensive follow-up studies are needed.

Barriers, which are normally used as highway safety instruments, cause adverse sand deposition damage to pavements along desert highways. To select a suitable barrier type for desert highways, this study conducted wind tunnel experiments and field test to measure the velocity field and sediment deposition morphology for different types of barriers. The results indicate that the velocity decreases in the foot of the subgrade, and the smooth air flow is maintained along the pavement. Wind velocity decreases slightly under the W-beam bottom, and the maximum velocity reduction is in the lee of the W-beam barrier. Wind velocity considerably decreases before and after the concrete barrier because of the dense structure of the barrier. Cable barriers slightly disturb the air flow and marginally decrease its velocity. Sediment deposition characteristic measurements demonstrate that for W-beam median barrier, sand is deposited on pavement in the lee of the barrier; further, for both W-beam roadside barrier and median barriers, sand is easy to be deposited in the front and back of the barrier, mainly on the windward pavement. For concrete barriers, considerable amount of sand is deposited in the front and back of the barriers, which induces the serious sand deposition damage on the pavement. The cable barrier causes minimal sand deposition, and it is a recommended structure for the barrier selection of desert highways. Further, small wind incidence angles are also favorable when designing desert highways.

The Tarim Basin is regarded as one of the most highly erodible areas in China. Desert comprises 64% of the land use in the Basin, but the desert–oasis ecotone plays a prominent role in maintaining oasis ecological security and stability. Yet, little is known concerning the magnitude of windblown sediment transport in a desert-oasis ecotone. Therefore, aeolian sediment transport and loss was assessed from a desert-oasis experimental site located near Alaer City in the northwestern Tarim Basin. Sediment transport and factors governing transport were measured during three high wind events in 2012 and four events in 2013. Sediment transport was measured to a height of 10 m using passive aeolian airborne sediment samplers. The mass flux profile over the eroding surface was well represented by the power-law (R 2  > 0.77). Sediment loss from the site ranged from 118 g m −2 for the 20–24Apr 2012 wind event to 2925 g m −2 for the 31Mar–11Apr 2012 event. Suspension accounted for 67.4 to 84.8% of sediment loss across all high wind events. Our results indicate the severity of wind erosion in a desert-oasis ecotone and thus encourage adoption of management practices that will enhance oasis ecological security.

Oasis landscape change and its pattern dynamics are considered one of the vital research areas on global land use and landscape change in arid regions. An agricultural oasis is the main site of food security and ecosystem services in arid areas. Recently, the dramatic exploitation of agricultural oases has affected oasis stability, inducing some ecological and environmental issues such as water shortage and land degradation. In this study, the Qira oasis on the southern margin of Tarim Basin, Northwest China, was selected as a study area to examine the spatiotemporal changes in an agricultural oasis and the influence on oasis landscape pattern. Based on the integration of Thematic Mapper, Enhanced Thematic Mapper Plus, and GF-1 images, the agricultural Qira oasis has rapidly increased, with annual change rates of −0.3%, 1.6%, 3.7%, and 1.5% during 1970–1990, 1990–2000, 2000–2013, and 2013–2016, respectively. With the agricultural oasis expansion, the agricultural land has increased from 91.10 km2 in 1970 to 105.04 km2 in 2016. The percentage of farmland area has increased by 15.3% in 2016 compared with that in 1970. The natural vegetation is decreasing owing to the reclamation of desert–oasis ecotone. The oasis landscape change and pattern are mainly affected by agricultural expansion under water-saving technological utilization, land use policy, and regional economic development demand. The expansion of agricultural oasis is alarming due to human overexploitation. Thus, the government should adjust the layout of agricultural development and pay considerable attention to the oasis environment sustainability. This study can provide a valuable reference on the impact of climate change and human activities on a landscape.