The lunar surface element distribution obtained from Chang'e-2 gamma-ray spectrometer has provided new insights into the thermal activity and element migration of the Moon. To further investigate lunar thermal evolution and geological activities, the heat production rate (HPR) distribution was selected as a breakthrough. An optimized inversion method for Chang'e-2 gamma-ray spectrum data, based on multivariate statistical analysis, was developed to effectively reduce the influence of time-varying factors by improving the background estimation and subtraction process. The results validated the utility of HPR for lunar research. The global HPR distribution maps not only provide a reference for assessing the thermal state of the lunar surface, demonstrating that radiogenic heat production can be reliably studied at a global scale, but also enable detailed investigations of regional geological processes. In the Imbrium Basin, HPR clearly reflects the effects of large-scale impact events and subsequent mare volcanic activity. High-HPR materials associated with impact ejecta can be distinguished from the lower-HPR mare basalts. Furthermore, by integrating HPR data with additional geological information, it is possible to assess and partially subdivide the structure of the Imbrium Basin, providing new quantitative insights into its evolution and compositional heterogeneity. (c) 2026 China University of Geosciences (Beijing) and Peking University. Published by Elsevier B.V. on behalf of China University of Geosciences (Beijing). Thi s is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

The background value is crucial in determining anthropogenic inputs and risk level of soil heavy metals (HMs). However, the spatial heterogeneity of the HMs frequently cause errors in the background value calculation, which further lead to underestimation or misjudgment of potential environmental risks. Here, we developed a sequential adaptive workflow utilizing expectation-maximization (EM) and Gaussian Process Regression (GPR) to eliminate spatial heterogeneity and improve the quality of HM risk assessments. This workflow operates through sequential diagnostic and application stages. It first conducts spatial variation driving factor analysis, which then guides the spatial heterogeneity identification of background values. This workflow integrated spatial variation driving factor analysis and spatial heterogeneity identification of background values for risk assessment. Spatial variation driving factor analysis is based on source apportionment and multiscale geographically weighted regression. Spatial heterogeneity identification is based on the correlation between the HMs background and the soil chemical composition. Methodological research was conducted using 3916 intensive sampling data points involving a dataset of element concentration data for 28 components. This workflow improves discrimination the HMs background from the anthropogenic inputs in the dataset, and applies the background values to risk identification and environmental bearing capacity assessment. To validate the proposed method, it was compared with the traditional methods. Comparison results demonstrated that the proposed method more effectively enhance the accuracy and reliability of regional environmental risk assessments by eliminating the spatial heterogeneity of the HMs background. The applicability analysis indicates that this workflow can be applied to geologically complex regions if sufficient sample quantities and analysis items can be obtained. The findings provide a robust tool for HMs background determination and offer accurate information and reliable evidence for soil pollution remediation projects.

Soil structure is an important index to maintain soil function, and the construction of stable soil aggregate structure is of great significance for the improvement of soil quality. Olivine, an abundant yet underutilized mineral resource in mining waste, holds application potential in soil amelioration. This study innovatively utilizes olivine-containing slag (a mining byproduct) to synthesize amorphous silica (APS), addressing the dual challenges of waste recycling and soil degradation. The prepared APS was characterized by X-ray fluorescence spectroscopy (XRF), scanning electron microscopy (SEM)-energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared (FT-IR) spectroscopy. The results showed that APS had amorphous nanostructures and high purity. The Si-OH bending vibration absorption peak and the-OH antisymmetric stretching vibration peak of the structural water reflected its sol characteristics. The effects of APS on soil composition were maintaining the acid-base balance, increasing cation exchange capacity (CEC) content, maintaining soil organic matter (SOM) stability, and enhancing the effectiveness of soil available silicon (SAS) in soil. The effect of APS on soil structure was reflected in the decrease of bulk density (BD), the increase of specific gravity (SG), the improvement of soil porosity (SP), and the water retention rate (WRR). At the same time, APS could significantly increase the percentage of non-water-stable aggregates (NWSAs) and water-stable aggregates (WSAs) in different types of soil, and the effect was the most obvious in aeolian sandy soils, reaching 24.29% and 12.24%, respectively. APS formed a more stable clay-cation-organic matter structure with soil particles, clay minerals, and organic matter to promote the formation of soil agglomeration structure and thereby improve soils.

Substantial heterogeneity in enhanced rock weathering (ERW) outcomes is often attributed to dissolution controls. However, we show that experimental boundary conditions – especially system openness – provide a primary explanation because dissolution products can be redistributed or exported beyond the sampled pool. We synthesise 81 peer-reviewed ERW studies (205 comparisons) using treatment-driven changes in exchangeable Ca and Mg as indicators of retained near-field weathering products. These retained exchangeable signals attenuated from incubations to pots/mesocosms and field trials, indicating constraints from hydrological connectivity and sampling boundary. Meta-regression reveals application rate is the principal controllable lever, whereas particle-size effects in controlled studies are not independently robust once correlated design choices are accounted for. Baseline soil pH is a consistent contextual filter, while hydroclimate sensitivities inferred from controlled systems are not reliably expressed in field datasets. A mass-balance conversion anchored to the 0–20 cm exchangeable pool yielded small apparent retained CO₂-equivalent signals (~0.03–0.06 t CO₂ ha⁻¹ yr⁻¹), best interpreted as near-field retention constraints rather than standalone CDR estimates. We propose a boundary-aware framework matching exchangeable signals to system openness and accounting scope before tuning application rate. Robust attribution requires longer field trials pairing exchangeable pools with deeper soil, export and water chemistry.

Contaminants of Emerging Concern (CECs), including per- and polyfluoroalkyl substances (PFASs) and organophosphate flame retardants (OPFRs), have raised global concerns due to their persistence, bioaccumulation potential, and toxicity. This study presents a comprehensive investigation of the occurrence, spatiotemporal distribution, potential sources, and the ecological and human health risks associated with 18 PFASs and 9 OPFRs in the surface waters of the upper Yangtze River, China. The water samples were collected from the main stream and five major tributaries (Min, Jinsha, Tuo, Jialing, and Wu Rivers) in 2022 and 2023. The total concentration of PFASs and OPFRs ranged from 16.07 to 927.19 ng/L, and 17.36 to 190.42 ng/L, respectively, with a consistently higher concentration observed in the main stream compared to the tributaries. Ultra-short-chain PFASs (e.g., TFMS) and halogenated OPFRs (e.g., TCPP) were the predominant compounds, likely originating from industrial discharges, wastewater effluents, and other anthropogenic sources. Ecological risk assessments indicated low-to-moderate risks at most sampling sites, with higher risks near wastewater discharge points. Human health risk evaluations suggested negligible non-carcinogenic risks but identified potential carcinogenic risks from OPFR exposure for adults at specific locations, particularly in Leshan city. This study highlights the importance of understanding the fate and impacts of PFASs and OPFRs in the upper Yangtze River, and provides valuable insights for developing targeted pollution control strategies and risk management measures.

The heat production of radioactive elements drives the thermal evolution of the Moon, and the heat production rate (HPR) based on Th, K, and U elements is also a crucial parameter constituting the current lunar heat flow. Exploring the distribution and source of HPR on the lunar surface can furnish evidence for the analysis of the Moon's evolutionary history and thermochemical structure, while the distinctive HPR states of the lunar basins that have undergone complex geological activities can provide more evolutionary information. Consequently, the data of heat producing elements in the gamma-ray spectrum of Chang'e-2 (CE-2) were inverted, and the HPR distribution status in lunar major basins, South Pole-Aitken (SPA), Smythii, Nubium, Humorum, Cognitum, Nectaris, Serenitatis, Crisium, Imbrium, and Orientale, was calculated and analyzed to reveal the causes of HPR anomalies and better describe the evolutionary history of lunar materials. There are three main sources of high HPR materials in lunar basins based on their HPR distribution patterns: 1) ejecta excavated by large-scale impact events; 2) magma with high HPR materials produced by volcanic activity within the basin itself; and 3) the high HPR materials carried to the lunar surface by the volcanic activity of Procellarum KREEP Terrane (PKT) and then transported and deposited into the surrounding basins. In addition, the distribution of high HPR materials in the lunar crust and asthenosphere is extremely uneven across the entire Moon, and they originate from different source than the Fe-Ti-rich magmas.

Soda saline-alkali soils pose significant challenges to agricultural productivity due to high pH and excessive sodium content. This study investigated the removal of excess salts in soda saline-alkali soil through electrochemical treatment (ECT). Traditional ECT often led to uneven soil pH distribution, with acidic conditions near the anode and alkaline conditions near the cathode, which limited its effectiveness for soil improvement. We explored the impact of conditioning the catholyte pH coupled with approaching anode electrochemical treatment (AA-ECT) on soil pH distribution and the removal of soluble sodium ions in soda saline-alkali soil. The results demonstrated that AA-ECT was less effective than fixed anode electrochemical treatment (FA-ECT) in regulating soil pH, achieving a relatively uniform pH range of 7.31–8.44. Adding acetic acid further improved pH uniformity, narrowing the range to 7.32–8.02. Moreover, all experimental groups exhibited high removal of soluble sodium ions efficiency, and the acetic acid coupled with AA-ECT achieved an average removal efficiency of 91.90

ObjectiveThe correct processing and interpretation of geochemical exploration data are critical for regional mineral exploration. High backgrounds may be misjudged as anomalies or low and weak geochemical anomalies may be ignored, if a unified anomaly threshold is adopted for geochemical exploration data in lithologically complex regions due to different elemental abundances in different lithologies. Therefore, it is essential to identify geochemical backgrounds and anomalies in lithologically complex regions based on lithologic classification.MethodsHere, we propose a method for delineating geochemical anomalies based on a Gaussian mixture model of factor scores. The geochemical exploration data are subjected to factor analysis after a log-ratio transformation, and then the lithologic classification is completed by the Gaussian mixture model with factor scores. Subsequently, the standardization is performed to eliminate the lithologic background, and geochemical exploration anomalies are delineated with the processed data. This method is used to the geochemical exploration data of 1:200 000 stream sediments in Xupu, Hunan Province.ResultsThe results show that the contents of the metallogenic elements in various lithologies of the study area are partly different, and consequently, it would be unreasonable to adopt a uniform anomaly threshold. In contrast, the method advanced in this paper can accurately classify lithology, eliminate the background of different lithologies, and enhance low and weak anomalies, with the location of the anomalies corresponding to known deposits.ConclusionHence, the Gaussian mixture model enables effective delineation of geochemical exploration anomalies in lithologically complex regions and provides certain information for further mineral prospecting in this region.

Heavy metal pollution is a huge hazard to the water environment and modified clay adsorbents have been widely used to remove heavy metals from water. Degradable anionic chelating agents have a greater potential for the immobilization of heavy metals, so tetrasodium iminodisuccinate (IDS) was introduced to modify montmorillonite (Mt) for Pb(II) and Cd(II) adsorption from water in this study. IDS was bound with Mt by sonication, heating, and acidity to form IDS-Mt, and characterized by XRD, FT-IR, SEM, and zeta potential analyzer. The batch adsorption experiments revealed that IDS-Mt5 had excellent adsorption capacity of Pb(II) and Cd(II) up to 214.73 mg/L and 104.07 mg/L, respectively. The adsorption process of IDS-Mt on Pb(II) and Cd(II) was consistent with the Sips model and PSO model, indicating that the adsorption was heterogeneous and chemical. The adsorption capacities of IDS-Mt in the second cycle remained above 76 % for Pb(II) and 69 % for Cd(II) of the initial ones, respectively. IDS was immobilized on the interlayer and edge surfaces of Mt through interactions or forming hydrogen bonds facilitated by ultrasonic under acidic heating conditions. Pb(II) and Cd(II) were immobilized by IDS-Mt through cation exchange, negative charge attraction at the edge surface, and IDS chelation. IDS-Mt was an excellent adsorbent with strong dispersibility and swelling properties for Pb(II) and Cd(II) removal from contaminated water. This study provides a new solution for the anionic modification of Mt and a new material for the treatment of heavy metal wastewater.

Solar-driven sorption-based atmospheric water harvesting (SAWH) is an emerging freshwater production technology for alleviating increasing water scarcity. However, existing water vapor sorbents typically suffer from environmentally unfriendly synthesis processes or components. The development of efficient SAWH sorbents that are environmentally compatible is highly demanded but remains a challenge. Herein, a novel, eco-friendly, and degradable biomass-based SAWH sorbent is developed for the solar-driven SAWH via a green approach by integrating hygroscopic choline chloride (ChCl) and photothermal polydopamine into porous alginate matrices (denoted as D-sorbent). For the first time, biomass-based ChCl is rationally chosen as the hygroscopic component, which imparts the D-sorbent with a high water vapor sorption capacity of 0.72 g g(-1) at 25 C-degrees, 80% RH. The D-sorbent exhibits an ultralow desorption temperature of 35 C-degrees at which similar to 99% of sorbed water can be released. In addition, the D-sorbent shows highly stable water vapor sorption and solar-driven desorption performance after repeated use and recycling. More importantly, the D-sorbent is fully made of biomass resources, which can be completely degraded into nontoxic substances in the soil, avoiding the environmental burdens otherwise caused by the out-of-service sorbents.

The "background" is an essential index for identifying anthropogenic inputs and potential ecological risks of soil heavy metals. However, the lithology of bedrock can cause significant spatial variation in the natural background of soil elements, posing considerable difficulties in estimating background values. In this study, an attempt was made to calculate the natural background through regression analysis of soil chemical composition, and reasonably evaluate the impact of lithology. A total of 1771 surface soil samples were collected from the Songhua River Basin, China, for chemical composition analysis, and the partial least square regression (PLSR) method was employed to establish the relationship between heavy metals (As, Hg, Cr, Cd, Pb, Cu, Zn, and Ni) and soil chemical composition/environmental parameters (SiO2, Al2O3, TFe2O3, MgO, CaO, K2O, Na2O, La, Y, Zr, V, Sc, Sr, Li and pH). The result shows that As, Cr, Pb, Cu, Zn, and Ni have significant linear relationships with soil chemical composition. Each of these six heavy metals obtained 1771 regression background values; some were higher than the uniform background value obtained from the boxplot, while others were lower. The regression background values recognized not only subtle anthropogenic inputs and potential ecological risks in low-background regions but also spurious contamination in high-background areas. All these indicate that the PLSR method can effectively improve the determination accuracy of the natural background of soil heavy metals. More attention should be paid to the serious anthropogenic inputs appearing in some places of the study area.

Due to the complex characteristics of geological structures, identifying geochemical anomalies in valuable deposits using regional geochemical datasets of stream sediments is challenging. In this study, an effective combined method was proposed to solve the problem of anomaly identification in multibackground areas. First, samples were classified into different clusters through the k-means clustering method using major elements/minerals (such as SiO2 and Na2O) that can reflect the lithology and were chosen as classification indicators. Considering the double restriction of the contour coefficient and lithological background, each sample within the same cluster was considered to have the same background. Then, the residual value between each sample and the mean data of adjacent samples within the same cluster was calculated, and the original data of each sample were replaced with the ratio (a new parameter defined as the residual contrast value) of the residual value and the anomaly threshold obtained for the corresponding cluster. Finally, geochemical maps and anomaly maps were generated using the residual contrast values. A practical example involving a regional geochemical dataset of stream sediments in Hunan, China, was examined in detail to clarify the procedure. Moreover, a comparative analysis through success rate curves of the percentage of deposits correctly determined was performed between the traditional method, singularity method and new combined method. The results showed that the anomalies identified by the proposed method were closely associated with known deposits, and the residual contrast value, which considers the effects of the lithological background, random error, and structural anomalies, could eliminate the influence of lithology and enhance weak anomalies. Moreover, the geological significance of this method is clear, and the calculation procedure is simple. Thus, this method could be applied for identifying regional geochemical anomalies in multibackground areas and could be used as a guide for new exploration targets.

钒(V)是维持生物体正常生命活动的必需微量元素之一,也是联合国环境规划署列入环境优先污染物的有害元素之一.研究V在土壤—植物系统中的迁移富集规律,对于深入了解其生态地球化学行为、保障农产品安全与人体健康具有重要现实意义.本文以山东临沂某地普通农田为例,对土壤、植物进行系统的采样,分析测试土壤与植物中的V与伴生元素的含量.采用描述性统计、相关性分析、聚类分析等统计方法与单因子污染指数法、潜在生态风险指数法、生物富集系数法等分析方法对研究区内V进行来源分析、污染评价以及V在土壤—植物系统的迁移转换规律的研究.结果表明:V在研究区内分布较为集中,其含量随着 Fe、Ti含量的升高而升高,随 SiO2、Na2 O、Sr、CaO含量升高而下降.研究区内V主要来源于母岩风化,高含量部分与磁铁矿相关.根据单因子指数法与潜在生态风险指数法评价结果,V在研究区土壤内较为清洁,但区内伴生的Cd污染需引起注意.V在植物中主要富集在根部,植物对V的吸收能力总体上与土壤中Cu、Pb、Zn、Ni、Co、Cd、Cr的含量呈负相关,以Cr最为显著;与土壤中As的含量呈正相关.该研究丰富了V的生态地球化学理论,也为区域农业生产、环境质量评估和生态污染防治提供了科学依据.

The identification of clay minerals is an essential step in soil research. However, many traditional methods have the limitations of tedious steps, slow speed, complicated preprocessing, and poor discrimination. A novel scheme for rapid and accurate identification of clay minerals in soils was proposed based on the chemical composition and structure information of kaolinite, talc, illite, vermiculite, montmorillonite, chlorite, and sepiolite obtained by combining different optical analysis methods. In this scheme, the chemical index of alteration (CIA) values was first calculated from the X-ray fluorescence spectroscopy (XRF) data for the overall classification, and then the main clay minerals were identified by the characteristic peaks of X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), or Raman spectroscopy (Raman). Furthermore, the 15 certified reference materials (CRMs) distributed in various regions of China and an actual chernozem sample (E125 $^{\circ }6.744'$ , N44 $^{\circ }25.018'$ ) were analyzed to validate the accuracy and applicability of the scheme. The results showed that there were significant latitudinal differences in the main clay minerals of soils with a gradual transformation of montmorillonite and vermiculite to kaolinite from north to south in China, and the major clay minerals of chernozem sample located in northeast China were montmorillonite and vermiculite, which were consistent with previous reports and actual situations. Therefore, the novel scheme proposed here greatly improves the accuracy and convenience of identifying clay minerals in soil by combining four optical instruments, which can provide strong technical support for the study of the formation and transformation mechanism of clay minerals.

Gold mining is the most important anthropogenic source of heavy metal emissions into the environment. Re-searchers have been aware of the environmental impacts of gold mining activities and have conducted studies in recent years, but they have only selected one gold mining site and collected soil samples in its vicinity for analysis, which does not reflect the combined impact of all gold mining activities on the concentration of potentially toxic trace elements (PTES) in nearby soils at a global scale. In this study, 77 research papers from 24 countries were collected from 2001 to 2022, and a new dataset was developed to provide a comprehensive study of the distribution characteristics, contamination characteristics, and risk assessment of 10 PTEs (As, Cd, Cr, Co, Cu, Hg, Mn, Ni, Pb, and Zn) in soils near the deposits. The results show that the average levels of all 10 elements are higher than the global background values and are at different levels of contamination, with As, Cd, and Hg at strong contamination levels and serious ecological risks. As and Hg contribute to a greater non-carcinogenic risk to both children and adults in the vicinity of the gold mine, and the carcinogenic risks of As, Cd, and Cu are beyond the acceptable range. Gold mining on a global scale has already caused serious impacts on nearby soils and should be given adequate attention. Timely heavy metal treatment and landscape restoration of extracted gold mines and environmentally friendly approaches such as bio-mining of unexplored gold mines where adequate protection is available are of great significance.

To improve the main shortcomings of insufficient nutrients, high salinity and low productivity in saline-alkali soils, this study collected saline-alkali soil samples from Da'an City of Baicheng and sediment samples from the adjacent Qianguo irrigation district, measured their pH values and major element contents, designed and verified the improvement scheme of saline-alkali soil based on geochemical engineering principles. Results indicated that the pH value and various element contents of saline-alkali soil could be adjusted by adding sediment to make it close to reference soil. Both theoretical calculation and experimental determination (soil pH, mineral composition, functional group composition and crop growth) revealed that the optimal mixing ratio of saline-alkali soil and sediment was 2:1. The saline-alkali soil amelioration with sediment of adjacent irrigation areas was effectively, low-cost and environment-friendly. The geochemical engineering principle was applicable to the amelioration of saline-alkali soil, but the mixing ratio of saline-alkali soil and sediment in different areas should vary with the local conditions. Meanwhile, theoretical calculation could basically replace the experimental determination to simplify the actual engineering application process. This saline-alkaline soil amelioration method makes full use of the surrounding natural waste and has the advantage of adapting measures to local conditions.

Determining the geochemical background for heavy metals is vital in soil management activities. Although many statistical methods for geochemical background determination have been proposed, the multi-population problem of geochemical data, primarily regional ones, derived mainly from mixing multiple populations belonging to various geological sources or processes, needs to be better addressed. In this study, the Expectation–Maximization (EM) algorithm was employed to separate multiple populations in a 1:250,000 scale regional geochemical data set of soils in a lithologically complex region in the north of Changchun, China. The data set included 3746 surface soil samples analyzed for SiO2, K2O, Al2O3, CaO, La, Rb, Y, Ti, Ce, V, Cr, and As. The potential high-risk areas of As and Cr were determined before and after the separation of multiple populations. The comparison results show that the EM clustering method can efficiently separate multiple populations and determine soil geochemical background more reasonably, thus eliminating false contamination that is easily misidentified and better revealing concealed contamination that is challenging to detect.

The rational utilization of solid waste has always been a worldwide concern. In this study, coal fly ash (CFA) and red mud (RM) were used in combination to synthesize efficient heavy metal adsorbents. A new way of resource recycling was provided with the collaborative reuse of CFA and RM. To obtain the modified composite materials, CFA and RM were mixed and melted in three ratios. After modification, these materials were then utilized to adsorb Pb, Cu, and Cd in water in both single and ternary systems. The physicochemical properties of CFA, RM, and three modified composite materials were measured by X-ray diffraction analysis, energy dispersive X-ray spectroscopy, scanning electron microscope, Fourier transform infrared spectroscopy, vibrating sample magnetometer, surface area analyzer, and porosity analyzer. In the single and ternary systems, the effects of the modified composite material dosage, solution pH, initial concentration of heavy metals, and adsorption time were discussed, and the results were better fitted with the Langmuir isotherm and the pseudo-second-order kinetic. It was discovered that the modified composite materials had a greater specific surface area (63.83 m2/g) than CFA and RM alone, as well as superior adsorption capacity and magnetic characteristics. The adsorption capacities of C1R4 for Pb, Cu, and Cd were 149.81 mg/g, 135.96 mg/g, and 127.82 mg/g in the single system, while those of Cu and Cd decreased slightly in the ternary system, and the preferential adsorption order of the modified composite materials for heavy metal ions was Pb > Cu > Cd. Among the three modified composite materials, C1R4 had the best adsorption capacity.

Lead contamination in soil has emerged as a significant environmental concern. Recently, pulse electrochemical treatment (PECT) has garnered substantial attention as an effective method for mitigating lead ions in low-permeability soils. However, the impact of varying pulse time gradients, ranging from seconds to hours, under the same pulse duty cycle on lead removal efficiency (LRE) and energy consumption in PECT has not been thoroughly investigated. In this study, a novel, modified PECT method is proposed, which couples PECT with a permeable reaction barrier (PRB) and adds acetic acid to the catholyte. A comprehensive analysis of LRE and energy consumption is conducted by transforming pulse time. The results show that the LREs achieved in these experiments were as follows: PCb-3 s (89.5%), PCb-1 m (91%), PCb-30 m (92.9%), and PCb-6 h (91.9%). Importantly, these experiments resulted in significant reductions in energy consumption, with decreases of 68.5%, 64.9%, 51.8%, and 47.4% compared to constant voltage treatments, respectively. It was observed that LRE improved with an increase in both pulse duration and voltage gradient, albeit with a corresponding rise in energy consumption. The results also revealed that corn straw biochar as a PRB could enhance LRE by 6.1% while adsorbing migrating lead ions. Taken together, the present data highlights the potential of modified PECT technology for remediation of lead-contaminated soil, which provides an optimal approach to achieve high LRE while minimizing energy consumption.

农业地质是地质科学与现代农业生产发展相结合的边缘学科.面向土地质量评价的农业地质调查涵盖了各种调查比例尺、不同调查对象、多种评价方法,产生各类多源、异构、多尺度和海量基础数据,文章从土地质量评价视角出发,围绕农业地质大数据应用平台的开发进行探索实践.文章采用面向服务架构和B/S网络结构,基于ArcGIS软件平台和WebService形式的OLAP技术,借助C#和JavaScript开发地理信息共享系统,采用关系型数据库系统SQL Server和Geodatabase进行数据管理,构建省级农业地质大数据平台.该平台集成了以往基础地质、农业地质、区域化探资料,挂接"地质云"(全国地质资料馆)公开馆藏资料,以地图结合图表的形式,直观、动态地展示了农业地质大数据信息.实现山东省农业地质"一张图"、大数据可视化、土壤监测预警、名特优产地环境辅助决策等典型应用.本次大数据平台针对农业地质典型应用进行了探索的研发,实现农业施肥精准化指导,对名特优产品的实现动态监测;面对不同尺度、不同时间的同源异构数据进行可视化对比、网格化比较,对地球化学指标周期性变化的观测,实现对土壤质量现状监测、对土壤环境污染预警的作用.还通过分布式数据挖掘和多维数据分析,实现了省级多目标区域化探、中大比例尺土地质量调查及农业地质相关同源异构数据的叠加分析,即对格网数据时间变化走势的展现,构建了基于地学思维的农业地质检测应用接口,为今后的科技创新提供了决策依据.