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Background: Desertification is one of the main obstacles to global sustainable development. Monitoring, evaluating and mastering its driving factors are very important for the prevention and control of desertification. As one of the largest deserts in China, the development of desertification in Otindag Sandy Land (OSL) resulted in the reduction in land productivity and serious ecological/environmental consequences. Although many ecological restoration projects have been carried out, the vegetation restoration of OSL and the impact mechanism of climate and human activities on desertification remain unclear. Methods: Taking OSL as the research area, this paper constructs the desertification index by using the remote sensing images and meteorological and socio-economic data, between 1986 and 2016, and analyzes the spatio-temporal evolution process and driving factors of desertification by using trend analysis and spearman rank correlation. Results: The results showed that: (1) Desertification in the OSL has fluctuated greatly during the past 30 years. Desertification recovered between 1986 and 1990, expanded and increased between 1990 and 2000, reduced between 2000 and 2004, developed rapidly between 2004 and 2007, and recovered again between 2007 and 2016; (2) The desertification of OSL is dominated by a non-significant change trend, accounting for 73.27%. In the significant change trend, the area of desertification rising trend is 20.32%, which is mainly located in the north and east, and the area of declining trend is 6.41%, which is mainly located in the southwest; (3) Desertification is the result of the superposition of climate and human activities. Climate change is the main influencing factor, followed by human activities, and the superposition effects of the two are spatio-temporal differences. Conclusions: These results shed light on the development of desertification in OSL and the relative importance and complex interrelationship between human activities and climate in regulating the process of desertification. Based on this, we suggest continuing to implement the ecological restoration policy and avoid the destruction of vegetation by large-scale animal husbandry in order to improve the situation of desertification. [ABSTRACT FROM AUTHOR]

The services provided by grassland ecosystems are important and irreplaceable in maintaining the balance and stability of ecosystems. The spatiotemporal variations of grassland ecosystem service value (ESV) and its influencing factors in Inner Mongolia from 2000 to 2019 were studied in this paper. Based on the socio-economic data, remote sensing data, geographic data, and meteorological data, a dynamic ESV assessment method based on the equivalent factors was used to calculate the grassland ESV for each year. The spatiotemporal dynamic variation and future trend of grassland ESV were studied by coefficient of variation index (CV), Theil–Sen median trend analysis, Mann–Kendall test, and Hurst index, and the Geodetector was used to determine the main factors affecting the distribution of ESV. The results indicated that (1) the annual average grassland ESV of Inner Mongolia was higher in the northeast than in southwest, the average ESV was 2.0794 million CNY/km2, and the pixels were concentrated from 1 to 3 million CNY/km2, accounting for 75.46% of the study area; (2) during the study period, the average grassland ESV increased slowly with time at an annual growth rate of 0.2, and the total ESV decreased first and then increased with the change in grassland area; (3) the average volatility was 0.16, and pixels with CV values between 0.1 and 0.2 accounted for 69.2% of the study area, indicating the fluctuation of ESV was relatively stable during the study period; (4) 37.16% of the grassland ESV in Inner Mongolia decreased slightly and 41.77% increased slightly during these years, and the two parts showed opposite trends in the future; and (5) the single factor influencing the spatial distribution of grassland ESV was mainly normalized vegetation index (NDVI) and precipitation, and the multi-factor interactions were NDVI∩slope and NDVI∩precipitation. All influencing factors exhibited a stronger impact through the two-factor interaction. This study can provide reference values for the policymaking of natural resource conservation or restoration. [ABSTRACT FROM AUTHOR]

The Yellow River Basin (YB) acts as a key barrier to ecological security and is an important experimental region for high-quality development in China. There is a growing demand to assess the ecological status in order to promote the sustainable development of the YB. The eco-environmental quality (EEQ) of the YB was assessed at both the regional and provincial scales utilizing the remote sensing-based ecological index (RSEI) with Landsat images from 2000 to 2020. Then, the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test were utilized to evaluate its variation trend. Next, the optimal parameter-based geodetector (OPGD) model was used to examine the drivers influencing the EEQ in the YB. Finally, the geographically weighted regression (GWR) model was utilized to further explore the responses of the drivers to RSEI changes. The results suggest that (1) a lower RSEI value was found in the north, while a higher RSEI value was found in the south of the YB. Sichuan (SC) and Inner Mongolia (IM) had the highest and the lowest EEQ, respectively, among the YB provinces. (2) Throughout the research period, the EEQ of the YB improved, whereas it deteriorated in both Henan (HA) and Shandong (SD) provinces. (3) The soil-available water content (AWC), annual precipitation (PRE), and distance from impervious surfaces (IMD) were the main factors affecting the spatial differentiation of RSEI in the YB. (4) The influence of meteorological factors (PRE and TMP) on RSEI changes was greater than that of IMD, and the influence of IMD on RSEI changes showed a significant increasing trend. The research results provide valuable information for application in local ecological construction and regional development planning. [ABSTRACT FROM AUTHOR]

The Inner Mongolia section of the Yellow River is a primary alluvial segment of the main channel. The variations in water and sediment not only alter the cross-sectional morphology and flow capacity of the river but also impact the scheduling of upstream cascade reservoirs. Based on runoff and sediment load data and topographic information from typical hydrological stations, the characteristics of runoff and sediment load variations and the evolutionary pattern of siltation in the Inner Mongolia River section were analyzed via trend analysis methods, Mann–Kendall test methods, the sediment load transport rate method, and the water level–flow relationship. The results showed that the water and sediment loads at the hydrological stations in the Inner Mongolia River section significantly changed from the 1960s to after 2000, with runoff decreasing by approximately 22% to 32% and the sediment load decreasing by approximately 65% to 73%. Sedimentation in the river section generally increased, and the average annual siltation amount reached 0.144 billion t. The joint utilization of the Longyangxia and Liujiaxia reservoirs in 1987 was the main reason for the rapid increase in siltation, and siltation in the Inner Mongolia River section was slightly reduced after 2005. In addition, the critical sediment load coefficients of the Bayangaole–Sanhuhekou and Sanhuhekou–Toudaoguai River sections were 0.0073 and 0.0051 kg·s/m6, respectively, from 1952 to 1968, and 0.0053 and 0.0037 kg·s/m6, respectively, from 1969 to 2020. This study could provide technical support for river flood control and reservoir water sediment regulation in Inner Mongolia. [ABSTRACT FROM AUTHOR]

Detailed information from global remote sensing has greatly advanced our understanding of Earth as a system in general and of agricultural processes in particular. Vegetation monitoring with global remote sensing systems over long time periods is critical to gain a better understanding of processes related to agricultural change over long time periods. This specifically relates to sub-humid to semi-arid ecosystems, where agricultural change in grazing lands can only be detected based on long time series. By integrating data from different sensors it is theoretically possible to construct NDVI time series back to the early 1980s. However, such integration is hampered by uncertainties in the comparability between different sensor products. To be able to rely on vegetation trends derived from integrated time series it is therefore crucial to investigate whether vegetation trends derived from NDVI and phenological parameters are consistent across products. In this paper we analyzed several indicators of vegetation change for a range of agricultural systems in Inner Mongolia, China, and compared the results across different satellite archives. Specifically, we compared two of the prime NDVI archives-AVHRR Global Inventory Modeling and Mapping Studies (GIMMS) and SPOT Vegetation (VGT) NDVI. Because a true accuracy assessment of long time series is not possible, we further compared SPOT VGT NDVI with NDVI from MODIS Terra as a benchmark. We found high similarities in interannual trends, and also in trends of the seasonal amplitude and integral between SPOT VGT and MODIS Terra (r > 0.9). However, we observed considerable disagreements in NDVI-derived trends between AVHRR GIMMS and SPOT VGT. We detected similar discrepancies for trends based on phenological parameters, such as amplitude and integral of NDVI curves corresponding to seasonal vegetation cycles. Inconsistencies were partially related to land cover and vegetation density. Different pre-processing schemes and the coarser spatial resolution of AVHRR GIMMS introduced further uncertainties. Our results corroborate findings from other studies that vegetation trends derived from AVHRR GIMMS data not always reflect true vegetation changes. A more thorough understanding of the factors introducing uncertainties in AVHRR GIMMS time series is needed, and we caution against using AVHRR GIMMS data in regional studies without applying regional sensitivity analyses. [ABSTRACT FROM AUTHOR]

In the context of global warming, timely and accurate drought monitoring is of great importance to ensure regional ecological security and guide agricultural production. This study established the Drought Severity Index (DSI), based on the potential evapotranspiration (PET), evapotranspiration (ET) and normalized difference vegetation index (NDVI) data from 2001 to 2020, to compensate for the low accuracy of drought spatial and temporal evolution due to the uneven distribution of stations. The DSI index was established to reveal the spatial and temporal variation of droughts in Inner Mongolia in the past 20 years, using trend analysis, gravity shift and geographic probes, and to explore the influence of different factors on the DSI. The results were as follows. (1) The results showed that the spatial distribution of DSI in Inner Mongolia during 2001–2020 had strong spatial heterogeneity, and generally showed distribution characteristics of drought in the west and wet in the east. In addition, the changes in DSI all exhibited a rising tendency, with the highest tendency in deciduous broadleaf forests (DBF) and the lowest tendency in grassland (GRA). (2) The center of gravity of wet, normal and arid areas showed a migration trend from northeast to southwest, with migration distances of 209 km, 462 km and 826 km, respectively. (3) The four combinations of temperature and elevation, temperature and slope, temperature and land use, and temperature and rainfall contributed the most. The results obtained in this study are important for the scheduling of ecological early warnings and drought prevention and control. [ABSTRACT FROM AUTHOR]