Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (13): 2572-2583.doi: 10.3864/j.issn.0578-1752.2022.13.008


Geostatistical Characteristics of Soil Data from National Soil Survey Works in China

ZHANG WeiLi1(),FU BoJie2(),XU AiGuo1,YANG Peng1,CHEN Tao3,ZHANG RenLian1,SHI Zhou4,WU WenBin1,LI JianBing5,JI HongJie1,LIU Feng6,LEI QiuLiang1,LI ZhaoJun1,FENG Yao1,LI YanLi1,XU YongBing1,PEI Wei1   

  1. 1Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081
    2Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085
    3Northwest A&F University, Yangling 712100, Shaanxi
    4Zhejiang University, Hangzhou 310058
    5Cultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing 100125
    6Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008
  • Received:2021-09-02 Accepted:2021-10-18 Online:2022-07-01 Published:2022-07-08


【Objective】China carried out the second state soil survey from 1979 to 1987 and the soil nutrient investigation of farmland from 2005 to 2017. Both surveys covered the whole country with a huge amount of ground soil samplings. The data generated from the two surveys have become the most detailed spatial-temporal data for soil types and quality in China. The purpose of the study was to test and to evaluate the geostatistical characteristics of the data by geostatistical testing approach, so as to provide the reference for the use of these data to characterize the temporal and spatial distribution of soil features in different disciplines. 【Method】7 testing areas were selected to represent different regions in China. Soil organic matter (SOM) contents of 0-20 cm soil layer from soil profile sampled in 1979-1987 and from plough layer sampled in 2005-2017 were extracted from the corresponding data bases. The ground sampling for soil profiles in 1979-1987 was to give priority to typical soil types firstly and secondly to keep an evenly distributed sampling as possible. 100 000 soil profiles with about 1m soil deep were finally sampled. After integrated data processing and coordinate matching, 60 000 profiles obtained coordinates. Ground sampling for soil plough layer in 2005-2017 was in grid distribution. 10 000 000 plough layer soil samples with GPS positioning coordinates have been completed. For each testing area, the data set contained two groups, about 500-1 300 SOM values from soil profile data and 50 000-250 000 values from plough layer data. The data from two time groups of each testing data set were analyzed by ordinary Kriging approach separately. 80% of the data were randomly selected as the training sample set for modeling and 20% as the verification sample set. The linear regression between the predicted value and the measured value of the validation sample was carried out. R2 (coefficient of determination) and RMSE (root mean square error) were calculated to evaluate the reliability and uncertainty of the data sets in expressing the spatial distribution of the soil feature. 【Result】It was showed that the reliability of mapping SOM content by profile data of all of the 7 testing areas reached significant levels. However, the deviation between predicted values and measured values of the test data set was relatively great. The values of R2 were low, between 0.223-0.380 and RMSE were relatively high. Testing results by soil plough layer data sampled in 2005-2017 showed that through large sample size and grid sampling, the reliability and prediction accuracy of mapping SOM content were improved greatly, for R2 increased and RMSE decreased. The geostatistical test results of two periods with a time interval of 30 years showed that although there were some changes in the contents of soil organic matter, the overall spatial distribution of SOM content in each testing area expressed by the two data groups was similar. 【Conclusion】 The reliability and accuracy of soil maps were much better in terms of characterizing the spatial distribution of soil features, when the soil investigation was by means of a large sample size with grid sampling. It meant that the reliability and accuracy of the original large-scale soil thematic maps, such as maps of soil types, organic matter, pH value, soil nitrogen, phosphorus and potassium nutrient contents from second state soil survey, were better than maps generated by profile data, as these original large-scale soil thematic maps were derived from the large sample size with grid sampling. However, the data of 60 000 soil profiles from second state soil survey, which contained many soil features and could supply reliable soil thematic maps, were also of great importance for understanding spatial characteristics of these soil features. It has been showed that a large sample size was essential for a precise and accurate mapping of soil feature of the whole country. For mapping long-term changing or stable soil features such as soil types, texture and morphological features, it would be difficult to obtain reliable maps by a soil sample size much less than the second state soil survey. Considering the current requirements and the available data resources in China, the soil investigation in the future could be mainly focused in investigating data missing areas as well as some missing soil features for soil functions.

Key words: soil survey, geostatistics, soil organic matter, soil quality, reliability test, digital soil mapping

Table 1

Sampling and geostatistical characteristics of data obtained from soil surveys in China"

Covering region
Sampling principle
Sample size
Generated vector data
Geostatistical characteristic
Soil types and fertility
Whole land area
Under priority of typical soil types, evenly distributed sampling
100000 典型土壤剖面样本
Typical soil profile samplings
County soil documentation
Point data for soil profile with coordinates
Grid sampling
Observation profiles
County soil maps (paper)
Polygon maps for soil, soil organic matter, pH and available nutrients
2000000 (0-20 cm depth)
Top soil samplings
Maps of soil organic matter, pH and available nutrients (paper)
Soil available nutrient
Arable land
Grid sampling
10000000 (0-20 cm depth)
Soil samplings
Point data of ploughing layer with coordinates for soil organic matter, pH and available nutrients

Table 2

The 7 tested areas of geostatistical"

编号 Number 片区名
Regions for tested areas
County number
Profile sampling number
Top soil sampling number
Arable land ratio (%)
1 东北片区 Northeast 19 546 45182 72353 79
2 冀鲁豫片区 Hebei, Shandong & Henan provinces 64 881 256341 50071 88
3 江浙片区 Jiangsu and Zhejiang provinces 53 1312 51759 63003 84
4 湖北片区 Hubei province 10 515 60545 21044 29
5 四川片区 Sichuan province 39 1283 206682 98052 50
6 粤闽赣片区 Guangdong, Fujian & Jiangxi provinces 27 801 51759 58745 21
7 陕甘片区 Shaanxi & Gansu provinces 47 990 256341 109010 40

Table 3

Testing results of soil organic matter contents from soil profile data of 7 areas by geostatistical approaches1)"

Region for tested area
Profile sampling number
1 东北片区 Northeast 546 0.329** 14.769
2 冀鲁豫片区 Hebei, Shandong & Henan provinces 881 0.363** 5.649
3 江浙片区 Jiangsu and Zhejiang provinces 1312 0.334** 8.826
4 湖北片区 Hubei province 515 0.286** 20.213
5 四川片区 Sichuan province 1283 0.380** 9.201
6 粤闽赣片区 Guangdong, Fujian & Jiangxi provinces 801 0.223** 13.325
7 陕甘片区 Shaanxi & Gansu provinces 990 0.296** 7.202

Table 4

Testing results of soil organic matter contents from plough layer data of 7 areas by geostatistical approaches1)"

Region for tested area
Sampling number
1 东北片区 Northeast 45182 0.689** 6.324
2 冀鲁豫片区 Hebei, Shandong & Henan provinces 256341 0.429** 3.470
3 江浙片区 Jiangsu and Zhejiang provinces 51759 0.666** 4.050
4 湖北片区 Hubei province 60545 0.281** 11.093
5 四川片区 Sichuan province 206682 0.344** 7.080
6 粤闽赣片区 Guangdong, Fujian & Jiangxi provinces 51759 0.285** 6.420
7 陕甘片区 Shaanxi & Gansu provinces 256341 0.558** 2.480

Fig. 1

Testing area for Northeast region: soil organic matter content map and geostatistical test results"


Testing area for Hebei, Shandong & Henan provinces: soil organic matter content map and geostatistical test results"


Testing area for Jiangsu and Zhejiang provinces: soil organic matter content map and geostatistical test results"

Table 5

Soil survey years of some developed countries"

Soil survey years
Soil map scale
美国 USA[18] 1900—1990 1∶12 000—24 000
加拿大 Canada[19] 1935—1990 1∶25 000—500 000
英国 Britain[20] 1950—1990 1∶25 000—66 000
德国 Germany[21] 1930—1970 1∶5 000—10 000
荷兰 Netherlands[22] 1945—1995 1∶50 000
澳大利亚 Australia[23] 1960—1990 1∶100 000—250 000
法国 France[24-25] 1960—2000 1∶100 000—250 000
日本 Japan[26] 1950—1990 1∶50 000
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