A Soil Environmental Quality Assessment Model Based on Data Fusion and Its Application in Hebei Province

Data Fusion in Agriculture: Resolving Ambiguities and Closing Data Gaps

Acquiring useful data from agricultural areas has always been somewhat of a challenge, as these are often expansive, remote, and vulnerable to weather events. Despite these challenges, as technologies evolve and prices drop, a surge of new data are being collected. Although a wealth of data are being collected at different scales (i.e., proximal, aerial, satellite, ancillary data), this has been geographically unequal, causing certain areas to be virtually devoid of useful data to help face their specific challenges. However, even in areas with available resources and good infrastructure, data and knowledge gaps are still prevalent, because agricultural environments are mostly uncontrolled and there are vast numbers of factors that need to be taken into account and properly measured for a full characterization of a given area. As a result, data from a single sensor type are frequently unable to provide unambiguous answers, even with very effective algorithms, and even if the problem at hand is well defined and limited in scope. Fusing the information contained in different sensors and in data from different types is one possible solution that has been explored for some decades. The idea behind data fusion involves exploring complementarities and synergies of different kinds of data in order to extract more reliable and useful information about the areas being analyzed. While some success has been achieved, there are still many challenges that prevent a more widespread adoption of this type of approach. This is particularly true for the highly complex environments found in agricultural areas. In this article, we provide a comprehensive overview on the data fusion applied to agricultural problems; we present the main successes, highlight the main challenges that remain, and suggest possible directions for future research.

Potential Ecological Risk Assessment of Heavy Metals in Cultivated Land Based on Soil Geochemical Zoning: Yishui County, North China Case Study

Various human production activities have caused tremendous damage to the soil ecological environment of cultivated land. Regional ecological risk assessments and the safe use of cultivated land have received widespread attention. The ecological risk assessment of heavy metals based on soil geochemical zoning has not been reported in the past. Using 14,389 topsoil samples, considering comprehensive geological background information, Yishui County in northern China was divided into three soil geochemical areas and 14 soil geochemical sub-regions by means of principal component factor superposition. The results of environmental quality and risk assessments of eight heavy metals based on soil geochemical zoning show that the single pollution index was greater than 1.0 and the Nemerow pollution index was greater than 0.7 for Ni in a sub-region, indicating that Ni pollution had reached the early warning limit, which demonstrates that Ni has a certain enrichment trend. Meanwhile, the geoaccumulation index of Ni and Cr was greater than zero in some sub-regions, indicating a slight pollution level. In addition, the potential ecological risk factor of the measured heavy metals was greater than 40 in 9 sub-regions, indicating a moderate ecological hazard, and the risk index was greater than 150 in a sub-region, revealing moderate ecological intensity, in which Hg and Cd were leading contributors to potential ecological hazards with a contribution rate between 58% and 76%. This method is suitable for the evaluation of soil environmental quality and safety for medium and large scales, and can provide a scientific basis for further zoning and grading prevention and control of soil pollution in cultivated land.