Zhou Shi

• PhD
• Professor at Zhejiang University

While global efforts to operationalise soil spectroscopy are progressing, cooperation is needed to fully its potential for generating digital soil information to support sustainable soil management worldwide. The Global Soil Laboratory Network's soil spectroscopy initiative (GLOSOLAN-Spec), led by the Food and Agriculture Organization of the United...

Accurate and timely acquisition of soil information is crucial for precision agriculture, food security, and environmental protection. Proximal visible near-infrared reflectance (vis–NIR) spectroscopy has been widely employed for rapid and accurate soil measurement, but its point measurement nature limits its direct applicability for large-scale so...

The contamination of heavy metal has permeated many parts of China, especially in densely populated and industrialized southern China. This study focused on the degree of pollution in farmland soil heavy metals (HMs), and its spatial distribution characteristics and source apportionment. Meanwhile, we conducted an evaluation of the health risks att...

Digital soil mapping (DSM) is transforming how we understand and manage soil resources, offering high-resolution spatial–temporal soil information essential for addressing environmental challenges. The integration of environmental covariates has advanced soil mapping accuracy, while the potential of neighboring soil sample data has been largely ove...

Agriculture faces the dual challenge of sustainably increasing productivity to meet the food demand of a rapidly growing population and adapting to climate change. Despite significant efforts to develop more adaptive and productive crop cultivars and to improve water and nutrient management practices, the potential of crops to tackle this challenge...

Texture features have been consistently overlooked in digital soil mapping, especially in soil salinization mapping. This study aims to clarify how to leverage texture information for monitoring soil salinization through remote sensing techniques. We propose a novel method for estimating soil salinity content (SSC) that combines spectral and textur...

The direction and magnitude of soil organic carbon stock (SOCS) change following land use and land cover change (LULCC) are highly uncertain, largely due to the lack of relevant global soil data. Great efforts have been made to build SOCS database at regional, national and even sub-continental scales following LULCC; however, a comprehensive and op...

Soil visible-near-infrared (vis-NIR) spectroscopy offers a rapid, uncontaminated, and cost-efficient method for estimating physicochemical properties such as soil organic carbon (SOC). The development of soil spectral libraries (SSLs) and localized modeling methods has significantly improved the selection of appropriate modeling sets from SSLs for...

Soil organic carbon (SOC) is not a single and uniform entity, therefore understanding SOC fractions, particularly particulate organic carbon (POC) and mineral-associated organic carbon (MAOC), offers valuable insights into SOC dynamics. However, traditional laboratory measurements of SOC fractions are labor-intensive and costly. Therefore, leveragi...

Understanding and managing soil organic carbon stocks (SOCS) are integral to ensuring environmental sustainability and the health of terrestrial ecosystems. The information of soil bulk density (BD) is important in accurately determining SOCS while it is often missing in the soil database. Using 3,504 soil profiles (14,170 soil samples) that repres...

China’s imports of livestock feed, particularly protein-rich feeds, pose challenges to global environmental sustainability. Achieving protein self-sufficiency for food and feed in China without exceeding environmental boundaries requires integrated measures and optimization of China’s food system. Here we propose holistic food system innovation str...

Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD...

Straw return was extensively applied owing to its multiple positive impacts on improving soil fertility, impeding soil degradation, enhancing soil carbon sequestration and increasing crop yield. Yet, the understanding of effects of straw return on carbon sequestration, soil nutrients, and rice yield of farmland with acidic soil at large spatial sca...

Climate change affects soil salinization and is responsible for food production threats and unsustainable development. However, global salinization trend and its temporal response to climate remains unclear. Here we show global soil salinization changes from 2003 to 2022 at 500 m resolution estimated by a machine learning approach, remote sensing,...

Salinization is a threat to global agricultural and soil resource allocation. Current investigations of global soil salinity are limited to coarse spatial resolution of the available datasets (>250 m) and semi-qualitative classification rules (five ranks). Based on these two limitations, we proposed a framework to quantitatively estimated global so...

Aboveground biomass (AGB) is an important indicator for characterizing crop growth conditions. A rapid and accurate estimation of AGB is critical for guiding the management of farmland and achieving production potential, and it can also provide vital data for ensuring food security. In this study, by applying different water and nitrogen treatments...

Plain Language Summary Soil contains a lot of carbon, and its levels can change based on climate and how we manage the land. Our global soil research shows that when new carbon goes into the soil, about 25% of it leaves within a year, regardless of depth. After 30 years, only about 13% remains. Interestingly, most of the carbon in the soil is older...

Soil pH is one of the critical indicators of soil quality. A fine resolution map of soil pH is urgently required to address practical issues of agricultural production, environmental protection, and ecosystem functioning, which often fall short of meeting the demands for local applications. To fill this gap, we used data from an extensive survey of...

Water parameter estimation based on remote sensing is one of the common water quality evaluation methods. However, it is difficult to describe the relationship between the reflectance and the concentration of non-optically active substances due to their weak optical characteristics, and machine learning has become a viable solution for this problem...

Long-term exposure to high concentrations of fine particles can cause irreversible damage to people’s health. Therefore, it is of extreme significance to conduct large-scale continuous spatial fine particulate matter (PM2.5) concentration prediction for air pollution prevention and control in China. The distribution of PM2.5 ground monitoring stati...

Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD...

An accurate and fine map of soil organic carbon (SOC) plays a vital role in understanding the global carbon cycle and achieving soil carbon sequestration potential. Although global and national maps of SOC are already available with various spatial resolutions, limited sample size, and relative coarse resolution hinder its accuracy and application...

Co-optimization of multiple management practices may facilitate climate-smart agriculture, but is challenged by complex climate–crop–soil management interconnections across space and over time. Here we develop a hybrid approach combining agricultural system modelling, machine learning and life cycle assessment to spatiotemporally co-optimize fertil...

High-accuracy simulation of gross primary productivity (GPP) is crucial for the monitoring and evaluation of the ecosystem services and the adaptive management of grassland. The light use efficiency (LUE) model is one of the most widely-used methods to simulate GPP, given its simple structure and low input requirements. Current LUE models are less...

Visible near-infrared (vis-NIR) spectroscopy has gained widespread recognition as an efficient and reliable approach for the rapid monitoring of soil properties. This technique relies on robust machine learning models that convert soil spectra information to soil properties. In particular, memory-based learning (MBL) has emerged as a powerful local...

Soil microbes drive soil organic carbon (SOC) mineralization. Because microbial groups differ in metabolic efficiency and respond differently to temperature variation, it is reasonable to expect a close association of SOC mineralization and its temperature sensitivity (Q10 which is defined as the factor of the change of soil carbon mineralization i...

Surface Soil Moisture (SSM) information from different sources exhibits distinct error characteristics. Data merging offers an effective method to combine the advantages of multi-source data and to enhance SSM estimation accuracy. The Triple Collocation (TC) -based merging approach under the linear weighted average scheme was widely used for SSM da...

Long-term, high-resolution soil moisture (SM) is a vital variable for understanding the water-energy cycle and the impacts of climate change on the Qinghai-Tibet Plateau (QTP). However, most existing satellite SM data are only available at coarse scale (~25 km) and suffer a lot from data gaps due to satellite orbit coverage and snow cover, especial...

The critical prerequisite for the prevention and control of soil heavy metal (HM) pollution is the identification of factors that influence soil HM accumulation. The dominant factors have been individually identified and apportioned in existing studies. However, the accumulation of soil HMs results from a combination of multiple factors, and the in...

Soil salinization and the shortage of water resources have become important factors affecting the sustainable development of agriculture in the southern Xinjiang. Agricultural flooding in winter or spring is the main means to reduce the damage of secondary soil salinization in southern Xinjiang. However, the spatial heterogeneity of soil salinizati...

Unsustainable human management has negative effects on cropland soil organic carbon (SOC), causing a decrease in soil health and the emission of greenhouse gas. Due to contiguous fields, large-scale mechanized operations are widely used in the Northeast China Plain, which greatly improves production efficiency while decreasing the soil quality, esp...

【 目的】以江西省泰和县为研究区域， 揭示县域尺度耕地土壤有机质（ SOM） 的空间分布规律。 【 方法】设计覆盖整个泰和县耕地的采样网络， 采集 361 个表层（ 0 ~ 20 cm） 土壤样品。 使用普通克里格插值法探究研究区耕地土壤有机质含量的空间分布特征， 利用随机森林模型结合经典统计方法探究泰和县耕地土壤有机质空间分异的主要影响因素。【 结果】研究区耕地土壤有机质含量均值为 31.05 g kg−1， 处于较丰富水平， 表明泰和县耕地土壤肥力水平较好。 泰和县耕地土壤有机质具有中等程度的空间自相关性， 具有中部低、 东西高的空间分布特征。 秸秆还田和海拔是耕地土壤有机质含量的主要影响因子， 解释率为 56.37% 和 18.73%。 土壤 pH、 成土母质、 施肥量和灌溉能力对土壤...

Soil health has gained increasing attention under the rapid development of industrialization and the requirement for green agriculture. Therefore, up-to-date soil information related to soil health is urgently needed to ensure food security and biodiversity protection. Previous studies have shown the potential of proximal soil sensing in measuring...

Soil, as the largest terrestrial carbon pool, has garnered significant attention concerning its response to global warming. However, accurately estimating the stocks and dynamics of soil organic carbon (SOC) remains challenging due to the complex and unclear influence mechanisms associated with biogeochemical processes in above- and belowground eco...

Revealing the spatio-temporal heterogeneity of cropland ecosystem services and identifying its main driving factors is a prerequisite for managing cropland and ensuring sustainable agriculture. The cropland ecosystem services are impacted by both cultivation practices and the natural environment, which lead to high heterogeneity. Therefore, making...

Ensemble modelling (EM) has been increasingly used in soil information prediction by spectroscopic techniques to enhance model robustness and improve model performance. This approach is usually implemented by fitting a new model using the predictions from several predictive models, and then outputting new predictions. Since the prediction error ass...

Soil organic carbon (SOC) plays an important role in soil functioning and also global C balance. Visible-near-infrared (Vis-NIR) spectroscopy can be regarded as a cost-effective alternative to monitor the SOC content. Previously, application of Vis-NIR spectroscopy in the quantitative estimation of SOC in arid and semi-arid regions has received rel...

Purpose Soil microbial communities and related key ecological processes play critical roles in timberline delineation and soil carbon balance in alpine ecosystems, which are highly vulnerable to climate change. Accordingly, understanding their geographical differentiation will facilitate recognition of ecosystem functions and improve soil carbon mo...

Soil organic matter (SOM) plays a critical role in terrestrial ecosystem functioning and is closely related to many global issues like soil fertility, soil health and climate regulation. Therefore, obtaining accurate information on the spatial distribution of SOM and its potential controlling factors is of global interest. However, this remains a g...

Soil inorganic carbon (SIC) is the primary component of the soil carbon pool in arid and semiarid regions and strongly impacts the global carbon cycle, ecosystem services, and soil functions. The global climate change and intensify of human activities, could substantially change SIC, which highlights the importance of monitoring SIC. Rapid and accu...

Remote sensing is an important tool for monitoring soil information. However, accurate spatial modeling of soil organic matter (SOM) in areas with high vegetation coverage, typically represented by agroecosystems, remains a challenge for field-scale estimation using remote sensing. To date, studies have focused on using single-period or multi-tempo...

Information about the nitrogen dynamic in wheat is important for improving in-season crop precision nutrient management and cultivated land sustainability. To develop unmanned aerial vehicle (UAV)-based spectral models for an accurate and effective assessment of the plant nitrogen content in the key stages (jointing, booting, and filling) of wheat...

Accurate detection and attribution of changes in global peak vegetation growth at the annual scale are prerequisites for characterising the productivity of terrestrial ecosystems and developing strategies for the sustainable management of ecosystems. This study examined the long-term global normalised difference vegetation index during the baseline...

For development planning and biodiversity management in China, it is crucial to understand the past and present patterns of biodiversity. Using satellite data has proven to be an effective means of characterizing the spatial distribution of species based on the species energy hypothesis, thereby supporting the conservation of biodiversity. This stu...

The prediction of soil properties at different depths is an important research topic for promoting the conservation of black soils and the development of precision agriculture. Mid-infrared spectroscopy (MIR, 2500–25000 nm) has shown great potential in predicting soil properties. This study aimed to explore the ability of MIR to predict soil organi...

Conservation priority zones (CPZs) are the most valuable critical areas for maintaining functions of ecosystem. Identifying CPZs and their driving factors of ecosystem services (ESs) is an essential foundation for preventing environmental degradation. The main aims of this study were to determine the CPZs according to the multi-year averaged ESs an...

Aim: This study aimed to infer the allocation of belowground net primary productivity (BNPP) to sequential soil depths down to 2 m across the globe at a 1 km resolution and assess underlying environmental drivers. Location: Global. Time Period: Contemporary (1932-2017). Major Taxa Studied: Terrestrial plants. Methods: Global datasets including...

Digital soil mapping has been increasingly advocated as an efficient approach to deliver fine-resolution and up-to-date soil information in evaluating soil ecosystem services. Considering the great spatial heterogeneity of soils, it is widely recognized that more representative soil observations are needed for better capturing the soil spatial vari...

The large-scale soil spectral library (SSL) can provide abundant information for predicting soil properties at a local scale, especially in places lacking data. However, since all the existing large-scale SSLs only contain dry spectra recorded under laboratory conditions, the challenge remains in using SSL for predicting soil information using in s...

Surface ozone (O3), a well-recognized air pollutant, exists in the atmosphere, which has a detrimental effect on public health and the ecological environment. It is reported that surface O3 has seen a significant increase in many cities from 2019 to 2021 (COVID-19 pandemic). In this study, we applied an innovative machine learning model (Deep Fores...

As a precious soil resource, black soils in Northeast China are currently facing severe land degradation. Visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm) and mid-infrared spectroscopy (MIR, 2500–25,000 nm) have shown great potential to predict soil properties. However, there is still limited research on using MIR in situ. The aim of t...

Purpose This study aims to explore the spatio-temporal variation of soil nutrients as well as soil organic matter (SOM), and clarify the role of environmental and soil management factors in determining soil nutrients and SOM in farmland over Jiangxi Province of Southern China. Materials and methods Between 2005 and 2012, we collected 16,504 surface...

In the context of increasing soil degradation worldwide, spatially explicit soil information is urgently needed to support decision-making for sustaining limited soil resources. Digital soil mapping (DSM) has been proven as an efficient way to deliver soil information from local to global scales. The number of environmental covariates used for DSM...

Accurate soil organic carbon (SOC) data are very important for management of agricultural production and climate change mitigation. Visible near-infrared diffuse reflectance spectroscopy is an inexpensive , non-destructive, efficient, and reliable technique for monitoring soil properties. Soil spectral libraries can contain large sets of diverse so...

Validation of satellite-based soil moisture products at the global scale using ISMN ground observations and triple collocation analysis

Robust soil organic matter (SOM) mapping is required by farms, but their generation requires a large number of samples to be chemically analyzed, which is cost prohibitive. Recently, research has shown that visible and near-infrared (vis-NIR) reflectance spectroscopy is a fast and accurate technique for estimating SOM in a cost-effective manner. Ho...

Plant root-derived carbon (C) inputs (Iroot) are the primary source of C in mineral bulk soil. However, a fraction of Iroot may lose quickly (Iloss, e.g., via rhizosphere microbial respiration, leaching and fauna feeding) without contributing to long-term bulk soil C storage, yet this loss has never been quantified, particularly on a global scale....

Potentially toxic elements in soils (SPTEs) from industrial and mining sites (IMSs) often cause public health issues. However, previous studies have either focused on SPTEs in agricultural or urban areas, or in a single or few IMSs. A systematic assessment of the pollution and risk levels of SPTEs from IMS at the national scale is lacking. Here, we...