The Three Rivers Source region is located in the high-altitude hinterland of the Qinghai-Tibet Plateau, and its ecological complexity and biodiversity render its ecological data invaluable. To address the issue of improving people's willingness to share data, an incentive system for ecological big data sharing based on contract theory and game theory is proposed in this paper. The combination of these two incentive mechanisms comprehensively considers various scenarios in actual situations and has a positive incentive effect on sharing ecological big data. The incentive mechanism based on contract theory formulates detailed contractual data sharing guidelines based on the quality, scarcity, and demand of shared data. This mechanism clarifies the accurate benefits and costs of data sharers and data demanders and effectively promotes the sharing of non-competitive data sets. Additionally, the incentive mechanism based on game theory designs the data sharing process as a game model. This approach maximizes the benefits between data sharers and data demanders, thus promoting the sharing of competitive data sets. Finally, the paper provides a specific implementation of the incentive system, and the results align with expectations.
Since Qinghai is located in the high-altitude Qinghai-Tibet Plateau region, the geomorphological types are complex and diverse, and the distribution of ground precipitation observation stations is sparse, improving the accuracy of precipitation data is critical for studying regional ecological change over time. In the paper, we study and construct a multi-source precipitation data fusion model based on neural networks, which consists of back propagation neural network (BPNN) and long short-term memory network (LSTM). The global precipitation measurement (GPM), fifth generation ECMWF atmospheric reanalysis (ERA5), digital elevation model (DEM), and normalized difference vegetation index (NDVI) data are selected as feature data and ground observation station data as label data for model training. The results show that the fused data generated by the BP-LSTM model reduces the root mean square error to 2.48mm and the overall relative bias to 0.25% compared with the original GPM, which is better than ERA5 on data accuracy. The precipitation event capture capability is improved, which is very close to the ERA5 data with strong precipitation event capture capability, and the probability of detection, false alarm rate, and missing event rate are 0.95, 0.53, and 0.04 respectively. Finally, the regional precipitation data is generated by the fusion model with resolution of 0.01°, 1h. The model proposed in the paper incorporates topographic factors and seasonal characteristics to solve the temporal and spatial correlation of precipitation data in Qinghai Province improve the accuracy of precipitation data, and provide reliable data support for the study of regional hydro-ecological spatial and temporal variation patterns.
The Three-River Source region is located at a high altitude in the hinterland of the Tibetan Plateau, the complexity of the region and its biodiversity make its ecological data of the region very invaluable. In order to realize data sharing and further processing of the Three-River Source’s ecological data, it is essential to formulate a unified data collection and management standard for ecological data. In the paper, a method based on DOI mechanism for ecological data collection and management of the Three-River Source is proposed, and the corresponding software model is implemented and verified. Specifically, for the collection and transmission of ecological data, the metadata-based data collection model and a TCP/IP protocol-based data transmission structure are adopted to ensure the effectiveness, integrity and availability of ecological data collection and transmission between different sites. In respect of data management and storage, the data identification method based on the Digital Object Unique Identifier (DOI) is adopted in the software, meanwhile MySQL is used to realize the storage of descriptive information under DOI flag data, so as to realize the efficient management of multi-source ecological data, as well as improve the accuracy of data retrieval by users. Through testing results, the specific software model implemented based on the design scheme proposed in the paper is consistent with the expected results and can meet the requirements.
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