区县级土壤普查采样与检测数据管理系统

District and county-level soil survey sampling and testing data management system

关键词:  土壤普查  数据管理系统  空间分析  多源数据

Key words:  soil survey  data management system  spatial analysis  multi-source data

摘要:

【目的】 文章设计并实现集成多源数据空间分析、多样点数据横向对比、多源数据可视化和高效数据管理的土壤普查采样与检测数据管理系统，为助力区县级政府农业部门提升土壤资源保护与利用水平，提供坚实的数据支撑与决策依据。【方法】 系统采用B/S架构，使用PostgreSQL数据库存储和管理土壤数据，通过Geoserver发布地图服务，前端使用主流框架Vue实现可视化；后端通过WebService提供数据接口与业务处理服务，并结合J2EE技术栈封装核心业务逻辑。【结果】 （1）系统实现地图可视化、多样点对比、多条件查询与结果导出、地图工具、查询定位和数据管理六大核心模块，覆盖土壤普查数据管理、分析、应用全流程。（2）实现多源土壤空间数据一体化可视化叠加分析，支撑宏观掌握土壤类型分布与土地利用变化趋势；系统支持多样点多指标横向对比，直观揭示样点间土壤类型、立地条件、施肥用量和理化性状等核心指标差异。【结论】 系统能对土壤普查数据进行数字化管理以及可视化空间分析，帮助开展土壤类型分布和土地利用类型变化等分析工作，并为区县级政府农业部门在农业生产布局、土壤资源保护与利用和农产品供给等方面提供数据支撑与决策帮助。

Abstract:

[Purpose] Design and implement a soil survey sampling and testing data management system that integrates multi-source data spatial analysis，multi-sampling-point comparative analysis，multi-source data visualization，and efficient data management. This system will provide solid data support and a decision-making basis for district and county levels agricultural departments to enhance the protection and utilization of soil resources.[Method] The system adopted a B/S architecture，used a PostgreSQL database for storing and managing soil data，published map services via GeoServer，and implemented visualization in the front-end using the mainstream Vue framework. The back-end provided data interfaces and business processing services through Web services，and encapsulated core business logic with the J2EE technology stack.[Result] （1）The system established six core functional modules，namely map visualization，multi-sampling-point comparison，multi-condition query and result export，map tools，query and positioning，and data management，covering the entire process of soil survey data management，analysis and application. （2）The system realized integrated visual overlay analysis of multi-source soil spatial data to support the macroscopic grasp of soil type distribution and land use change trends. It supported horizontal comparison of multiple indicators across multiple sampling points，and intuitively revealed the differences in core indicators among the sampling points，including soil type，site conditions，fertilization application rate，and soil physical and chemical properties.[Conclusion] The system enables digital management and visual spatial analysis of soil survey data，facilitates the analysis of soil type distribution patterns and changes in land use types，and provides data support and decision-making reference for district and county levels agricultural authorities in areas including agricultural production layout optimization，soil resource protection and utilization，and agricultural products supply security.