Linking the assessment of ecological engineering construction with zoning management in the typical agro-pastoral area of China: A perspective from quantity, quality and function.

Combatting land damage has become a global priority, and China has adopted a series of ecological engineering measures, especially in the agro-pastoral area with fragile ecological environment. The effectiveness of ecological engineering construction (EEC), from a comprehensive recognition encompassing its quality, quantity, and function, has remained largely unknown. To this end, Zhangbei County, a typical agro-pastoral ecotone of northern China, was chosen as our focal area.

Resilience patterns of human mobility in response to extreme urban floods.

Large-scale disasters can disproportionately impact different population groups, causing prominent disparity and inequality, especially for the vulnerable and marginalized. Here, we investigate the resilience of human mobility under the disturbance of the unprecedented '720' Zhengzhou flood in China in 2021 using records of 1.32 billion mobile phone signaling generated by 4.

Revisiting the gravity laws of inter-city mobility in megacity regions.

Inter-city mobility is one of the most important issues in the UN Sustainable Development Goals, as it is essential to access the regional labour market, goods and services, and to constrain the spread of infectious diseases. Although the gravity model has been proved to be an effective model to describe mobility among settlements, knowledge is still insufficient in regions where dozens of megacities interact closely and over 100 million people reside. In addition, the existing knowledge is limited to overall population mobility, while the difference in inter-city travel with different purposes is unexplored on such a large geographic scale.

Temporal and Spatial Variation of Aboveground Biomass of and Its Drivers in Shangri-La, CHINA.

Understanding the drivers of forest aboveground biomass (AGB) is essential to further understanding the forest carbon cycle. In the upper Yangtze River region, where ecosystems are incredibly fragile, the driving factors that make AGB changes differ from other regions. This study aims to investigate AGB's spatial and temporal variation of in Shangri-La and decompose the direct and indirect effects of spatial attribute, climate, stand structure, and agricultural activity on AGB in Shangri-La to evaluate the degree of influence of each factor on AGB change.

Identification of urban land use efficiency by indicator-SDG 11.3.1.

Inefficiency in urban land use is one of the problems caused by rapid urbanization. The UN Sustainable Development Goals (SDGs) indicator 11.3.

Spatial differentiation characteristics of internal ecological land structure in rural settlements and its response to natural and socio-economic conditions in the Central Plains, China.

Ecological land in rural settlements (ELRS) can directly provide many ecosystem services for rural residents that are related to their well-being. This study selects landscape pattern indices to describe the structural characteristics of ELRS at the county level in the Central Plains region (CP), China. Fragmentation of ELRS in the North China Plain (NCP) is higher than that in the marginal mountainous and hilly areas of the CP, and ELRS dominance is higher in the south than in the north.

Global urban expansion offsets climate-driven increases in terrestrial net primary productivity.

The global urbanization rate is accelerating; however, data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP). Here, using a high resolution dataset of global land use/cover (GlobeLand30), we show that global urban areas expanded by an average of 5694 km per year between 2000 and 2010. The rapid urban expansion in the past decade has in turn reduced global terrestrial NPP, with a net loss of 22.

Grazing alters the phenology of alpine steppe by changing the surface physical environment on the northeast Qinghai-Tibet Plateau, China.

The response of vegetation phenology to environmental changes is very complex. We used time-lapse digital cameras to monitor the phenology of an alpine steppe in four winter pastures with different grazing intensities during 2015-2017. The results showed that the beginning of the growing season (BGS) and the growing season length (GSL) of the alpine steppe separately presented advances or prolonged trends with the increase in grazing intensity.

A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography.

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix.

Post-Seismic Deformation from the 2009 Mw 6.3 Dachaidan Earthquake in the Northern Qaidam Basin Detected by Small Baseline Subset InSAR Technique.

On 28 August 2009, one thrust-faulting Mw 6.3 earthquake struck the northern Qaidam basin, China. Due to the lack of ground observations in this remote region, this study presents high-precision and high spatio-temporal resolution post-seismic deformation series with a small baseline subset InSAR technique.

Estimating soil organic carbon content with visible-near-infrared (vis-NIR) spectroscopy.

The selection of a calibration method is one of the main factors influencing measurement accuracy with visible-near-infrared (Vis-NIR, 350-2500 nm) spectroscopy. This study, based on both air-dried unground (DU) and air-dried ground (DG) soil samples, used nine spectral preprocessing methods and their combinations, with the aim to compare the commonly used partial least squares regression (PLSR) method with the new machine learning method of support vector machine regression (SVMR) to find a robust method for soil organic carbon (SOC) content estimation, and to further explore an effective Vis-NIR spectral preprocessing strategy. In total, 100 heterogeneous soil samples collected from Southeast China were used as the dataset for the model calibration and independent validation.