【摘要】 针对黑土地大数据平台研究与实践过程中相关领域文献的系统性综述相对匮乏的问题，从数据采集、平台架构、典型应用等多个角度，系统综述了黑土大数据平台的发展现状，并对比分析了国内外同类平台的技术路线与核心特征。阐释了黑土大数据的多源异构、时空关联与多尺度特性，分析了“天-空-地-网”一体化数据采集体系的构成及其融合过程的核心挑战。在此基础上，梳理并对比了单体式、微服务化及智能体化等主流平台架构的演进路径与优劣，指出当前平台在“决策-控制”闭环中的技术断层是实现全链路智能化的主要瓶颈。通过评估黑土地质量监测评价、精准施肥、退化成因分析、灾害预警与政策模拟等典型应用场景，揭示了平台在数据驱动决策中的潜力与局限。进而识别了数据壁垒、模型可解释性不足与应用推广困难等平台发展过程中的多重挑战，并提出人工智能与知识图谱深度融合、“人-机-物”智能协同、跨平台标准互认等平台关键发展方向。研究结果可为黑土地大数据平台的后续研究、构建与规模化应用提供理论参考与实践指导。更多还原

【Abstract】 Addressing the notable gap in systematic reviews within the field of black soil big data platform research and practice, comprehensive analysis of the current state of these platforms from the perspectives of data acquisition, platform architecture, and typical application scenarios were provided. A comparative assessment of the technical approaches and defining characteristics of similar domestic and international platforms was also conducted. Firstly, the multi-source heterogeneity, spatiotemporally correlated and multi-scale attributes of black soil data were expounded, and the structure of the integrated “space-air-ground-network” data acquisition system and the fundamental challenges inherent in its data fusion processes were analyzed. Subsequently, the evolutionary pathways, comparative advantages and limitations of mainstream platform architectures,including monolithic, microservice-based and agent-oriented paradigms,were examined and contrasted. The analysis identified a critical technical discontinuity within the “decision-control” closed-loop as the primary bottleneck hindering the achievement of end-to-end platform intelligence. Through an evaluation of key application areas, such as land quality monitoring, precision fertilization, degradation diagnostics, disaster early warning and policy simulation, both the potential and the constraints of these platforms in enabling data-driven decision-making were delineated. Furthermore, multiple persistent challenges, including data silos, insufficient model interpretability and difficulties in practical adoption and scaling were pinpointed. Several pivotal directions for future development were proposed, such as emphasizing the deep integration of artificial intelligence with knowledge graphs, the advancement of “human-cyber-physical” intelligent collaboration, and the establishment of cross-platform standards and mutual recognition frameworks. Above results offered both theoretical reference and practical guidance for subsequent investigation, system development and the scaled deployment of black soil big data platforms.更多还原