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Climate change has induced substantial shifts in vegetation boundaries such as alpine treelines and shrublines, with widespread ecological and climatic influences. However, spatial and temporal changes in the upper elevational limit of alpine grasslands ("alpine grasslines") are still poorly understood due to lack of field observations and remote sensing estimates. In this study, taking the Tibetan Plateau as an example, we propose a novel method for automatically identifying alpine grasslines from multi‐source remote sensing data and determining their positions at 30‐m spatial resolution. We first identified 2895 mountains potentially having alpine grasslines. On each mountain, we identified a narrow area around the upper elevational limit of alpine grasslands where the alpine grassline was potentially located. Then, we used linear discriminant analysis to adaptively generate from Landsat reflectance features a synthetic feature that maximized the difference between vegetated and unvegetated pixels in each of these areas. After that, we designed a graph‐cut algorithm to integrate the advantages of the Otsu and Canny approaches, which was used to determine the precise position of the alpine grassline from the synthetic feature image. Validation against alpine grasslines visually interpreted from a large number of high‐spatial‐resolution images showed a high level of accuracy (R2,.99 and.98; mean absolute error, 22.6 and 36.2 m, vs. drone and PlanetScope images, respectively). Across the Tibetan Plateau, the alpine grassline elevation ranged from 4038 to 5380 m (5th–95th percentile), lower in the northeast and southeast and higher in the southwest. This study provides a method for remotely sensing alpine grasslines for the first‐time at large scale and lays a foundation for investigating their responses to climate change. [ABSTRACT FROM AUTHOR]

Shrub encroachment into arid and semi-arid grasslands has elicited extensive research attention worldwide under the background of climate change and increasing anthropogenic activities. Shrub encroachment may considerably impact local ecosystems and economies, including the conversion of the structure and function of ecosystems, the shift in ambient conditions, and the weakness of local stock farming capacity. This article reviews recent research progresses on the shrub encroachment process and mechanism, shrub identification and dynamic monitoring using remote sensing, and modeling and simulation of the shrub encroachment process and dynamics. These studies can help to evaluate the ecological effect of shrub encroachment, and thus, practically manage and recover the ecological environment of degraded areas. However, the lack of effective measures and data for monitoring shrub encroachment at a large spatial scale severely limits research on the mechanism, modeling, and simulation of shrub encroachment, and the shrub encroachment stages can hardly be quantitatively defined, resulting in insufficient analysis and simulation of shrub encroachment for different spatiotemporal scales and stages shift. Improvement in remote sensing-based shrub encroachment dynamic monitoring might be crucial for analyzing and understanding the process and mechanism of shrub encroachment, and multi-disciplinary and multi-partnerships are required in the shrub encroachment studies. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) is a crucial parameter in ecology, agriculture, hydrology, and engineering studies. Research on non-invasive monitoring of SWC has been a long-lasting topic in these fields. Ground penetrating radar (GPR), a non-destructive geophysical technique, has the advantages of high resolution, deep detection depth, and high efficiency in SWC measurements at medium scale. It has been successfully applied in field investigations. This paper summarizes the recent progress in developing GPR-based SWC measurement methods, including reflected wave, ground wave, surface reflection, borehole GPR, full waveform inversion, average envelope amplitude, and frequency shift methods. The principles, advantages, limitations, and applications of these methods are described in detail. A comprehensive technical framework, which comprises the seven methods, is proposed to understand their principles and applicability. Two key procedures, namely, data acquisition and data processing, are emphasized as crucial to method applications. The suitable methods that will satisfy diverse application demands and field conditions are recommended. Future development, potential applications, and advances in hardware and data processing techniques are also highlighted. [ABSTRACT FROM AUTHOR]

Roots play a key role in plant anchorage, absorption and storage of soil resources (water, nutrients, carbohydrates) and biogeochemical cycles in terrestrial ecosystems. Studying the configuration of the root system and its distribution in the underground space is critical to understanding these effects of the root. For nearly two decades, ground penetrating radar (GPR) has been used as a non-destructive geophysical method to describe the spatial distribution of coarse roots under controlled conditions and field conditions. The detection effect of the ground penetrating radar on the root system depends mainly on the frequency of the radar antenna used and the degree of difference in the relative dielectric constant (ε) between the root and the soil. Nevertheless, the relative permittivity of soil varies greatly between summer and winter due to the effects of seasonal frozen soil. Using this seasonal variation, we evaluated the use of GPR with 900 MHz and 400 MHz antennas to nondestructively delineate the spatial distribution of the roots system of the same shrubs both in summer (August) and winter (January of the second year) under field conditions in the Xilingler shrub grassland ecosystem in Inner Mongolia, China. In summer, the relative dielectric constant difference between root and soil is greater due to the high water content of the roots, and more root signals can be obtained. However, as the soil moisture content is also high, the electromagnetic wave decays faster, which limits the detection depth of the radar, and only the shallow root signals were obtained. In winter, because of the existence of shallow frozen soil, the relative dielectric constant of the soil is low, which is conducive to the penetration of electromagnetic wave into the deep soil, so deeper root information can be obtained. However, the water content of roots will decrease due to the influence of low temperature, which resulting in a smaller difference in the relative dielectric constant between roots and soil. Therefore, the recognition effect on the shallow root system is relatively poor compared with results obtained in summer. Combined with the detection results of the two antenna frequencies (900MHz and 400MHz) in summer and winter, wealth and complete information of shrub root system distribution can be obtained. An effective GPR-based root measurement strategy is proposed by making full use of the seasonal changes of soil environment, which can further enhance the application of GPR in plant root research. [ABSTRACT FROM AUTHOR]