Farmland soil organic carbon temporal-spatial data acquisition method based on multi-source data assistance

Abstract

The invention relates to a farmland soil organic carbon temporal-spatial data acquisition method based on multi-source data assistance. According to the farmland soil organic carbon temporal-spatial data acquisition method, a small amount of sample point data is used as a basis; a multi-source data auxiliary processing method is designed, adopted and combined with resampling and interpolation analysis to obtain temporal-spatial scale high-resolution data quickly, the obtained data has the advantage of high reliability, the contradiction between the cost and the number of sample points is solved, namely, temporal-spatial scale expansion is carried out by utilizing the small amount of sample point data in a single period, soil sampling point data with higher temporal-spatial resolution is obtained, data support is provided for digital agriculture big data analysis, the technical blank that the current data is difficult to obtain is filled, the temporal scale data is rapidly expanded, thespatial scale sample point resolution is greatly improved, the farmland soil organic carbon temporal-spatial data acquisition method has the technical advantages of being high in data acquisition speed and reliable in data, the time and economic costs required by data acquisition can be greatly reduced by adopting the farmland soil organic carbon temporal-spatial data acquisition method, and temporal-spatial data with higher resolution is rapidly provided for digital agricultural soil quality monitoring.

Description

technical field [0001] The invention relates to a multi-source data-assisted spatio-temporal data acquisition method for farmland soil organic carbon, which belongs to the technical field of digital agricultural soil quality monitoring. Background technique [0002] Due to the complexity of soil morphology and evolution process, it is difficult to quantitatively describe soil morphology and properties, and the quantitative description of spatial variation characteristics and spatial correlation is more complicated. How to quickly obtain the key soil information required has become a challenge for scientific researchers. Hot Issues. [0003] In the field of soil monitoring, the current large-scale sampling survey process is very cumbersome. It is necessary to go to the specific location of the sample point to collect samples and bring the sample back to the laboratory for further analysis, which requires a lot of manpower and time. However, the cost of manpower and time is g...

AI Technical Summary

Problems solved by technology

Therefore, the direct survey and estimation method can obtain first-hand soil information data, but the temporal and spatial resolution is limited, and it is difficult to meet the current high spatial and temporal resolution data needs

The method of indirect estimation of soil organic carbon change based on the carbon cycle process model, its simulation accuracy is limited by the complexity of parameters, which in turn affects the estimation accuracy of simulated soil organic carbon

Images