Peer-Reviewed Journal Details
Mandatory Fields
Sun, XL,Wu, YJ,Lou, YL,Wang, HL,Zhang, C,Zhao, YG,Zhang, GL
2015
November
European Journal Of Soil Science
Updating digital soil maps with new data: a case study of soil organic matter in Jiangsu, China
Published
()
Optional Fields
BAYESIAN MAXIMUM-ENTROPY VARIABILITY PATTERNS REGION CARBON AREAS
66
1012
1022
The rapid developments in the acquisition of data on soil should enable pedologists to update existing digital soil maps readily. The methods by which that is done must take into account temporal change in soil properties and local differences in spatial variation. The common mapping techniques will have to be modified to make full use of digital data. We show what can be achieved with a case study on updating maps of soil organic matter (SOM) in Jiangsu Province, China, with three sets of soil data collected in the 1980s, 2000 and 2006. Our results showed that temporal changes in SOM between the three sampling periods occurred in only very small parts of the regions. Models of spatial variation of SOM based on the data collected in the 1980s and 2006 for the whole region differed somewhat, whereas models based on the data collected in the 1980s, 2000 and 2006 for the Taihu region (south Jiangsu) were significantly different. As updating with Bayesian maximum entropy continued, the accuracy of prediction increased and that of the prediction variance decreased. Finally, our study leads us to suggest improved technologies for updating digital soil maps with new data.
10.1111/ejss.12295
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