Ecological environment monitoring is essential for ecological environment protection and supervision by providing reliable data. Effective integration and management of the monitoring data are fundamental for mining their potential value. However， the substantial volume， diverse sources， and high value of ecological environmental monitoring data present enormous challenges， such as differing standards and reference systems， which complicate data integration and sharing. In response to these issues， this paper proposes a mechanism of dual-layer embedding grid network hybrid indexing based on Geohash and administrative divisions. This approach promotes the integrated organization and management of various ecological environmental monitoring data and meets the storage and rapid retrieval needs of extensive， multi-source， and heterogeneous datasets. Based on this constructed mechanism， a grid automatic division software was developed to realize integrated organization， multi-dimensional retrieval， statistical analysis， and real-time display of ecological monitoring data. The software was validated with the 2021 national straw fire vector data， the August 2023 vector data for dust pollution sources in Jiangyan District， and the vector data for reservoirs in Jiangsu Province，demonstrating its functionalities and operational effectiveness. The results indicate that the proposed mechanism can efficiently complete grid construction and coding for massive ecological monitoring data. Furthermore， based on business requirements， it allows for the selection of optimal grids tailored to retrieval and statistical analysis across various spatial scales.