Application of land use modes in the spatial prediction of soil organic carbon in urban green spaces
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Key Laboratory of Forest Management and Growth Modelling, National State Forestry and Grassland Administration, Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
Ecological Construction Investment Company Limited, Xiong'an Group, Xiong'an 071699, China
Industry Development and Planning Institute, NFGA, Beijing 100010, China
Final revision date: 2022-10-09
Acceptance date: 2022-10-24
Publication date: 2022-12-30
Corresponding author
Xianzhao Liu   

Key Laboratory of Forest Management and Growth Modelling, State Forestry and Grassland Administration, Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, China
Int. Agrophys. 2023, 37(1): 1–14
  • The spatial distribution pattern of soil organic carbon in Xiong'an New Area was predicted using four interpolation methods.
  • Land use modes are important factors affecting the spatial distribution of urban soil organic carbon.
  • Using land use type as an auxiliary variable can effectively improve the prediction accuracy of soil spatial distribution.
The challenge of predicting soil organic carbon distribution accurately has received great attention in order to support urban green space soil management during climate change. This study compared four geostatistical methods: kriging combined with land use, ordinary kriging, inverse distance weighting and radial basis function, to predict the spatial distribution patterns of soil organic carbon content and soil organic carbon density in the Xiong'an New Area, estimate organic carbon stocks, and assess the role of land use types in the spatial prediction of soil organic carbon stocks. The results showed that the soil organic carbon content decreased with increasing soil depth, and was significantly affected by different land use types (p<0.05). The correlation coefficient values of kriging combined with land use were on average 0.229 higher than those of other methods. The root mean squared error and the mean absolute error of kriging combined with land use were on average 0.148 and 0.139 lower than those of the other methods. Kriging combined with land use has a greater advantage over other methods in predicting the spatial distribution of soil organic carbon content, and also the spatial distribution of soil organic carbon density and the spatial distribution of soil organic carbon, the prediction results of the four interpolation methods were similar. The average soil organic carbon density was 2085 Gg (0-30 cm) and 1363 Gg (30-60 cm). In conclusion, land use type clearly influences the spatial distribution of soil organic carbon in urban areas, and by using land use type as auxiliary data, we can obtain a more accurate spatial distribution of soil organic carbon and predict the total storage capacity of the soil. This study may result in significant advances in the spatial prediction of soil organic carbon for urban areas.
The authors are grateful to the Fundamental Research Funds of CAF (CAFYBB2019ZB005).
This work was supported by the Chinese Academy of Forestry (CAFYBB2019ZB005; 2019-2022).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Allen D.E., Pringle M.J., Page K.L., and Dalal R.C., 2010. A review of sampling designs for the measurement of soil organic carbon in Australian grazing lands. Rangel. J., 32, 227-246,
Bao S.D., 2005. Soil agrochemical analysis. China Agriculture Press, Beijing, China.
Barreto M.S.C., Schellekens J., Ramlogan M., Rouff A.A., Elzinga E.J., Vidal-Torrado P., and Alleoni L.R.F., 2021. Effects of horticulture on soil organic matter properties in highly weathered tropical soils. Soil Tillage Res., 213, 105156,
Bhunia G.S., Shit P.K., and Maiti R., 2016. Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC). J. Saudi Soc. Agric. Sci., 17, 114-126,
Blais E., 2021. Carbon sequestration and the urban heat island effect. VCU Environmental Research Methods, QUBES Educational Resources,
Blanchet G., Libohova Z., Joost S., Rossier N., Schneider A., Jeangros B., and Sinaj S., 2017. Spatial variability of potassium in agricultural soils of the canton of Fribourg, Switzerland. Geoderma, 290, 107-121,
Boubehziz S., Khanchoul K., Benslama M., Benslama A., Marchetti A., Francaviglia R., and Piccini C., 2020. Predictive mapping of soil organic carbon in Northeast Algeria. Catena, 190, 104539,
Brovelli A., Batlle-Aguilar J., and Barry D.A., 2012. Analysis of carbon and nitrogen dynamics in riparian soils: Model development. Sci. Total Environ., 429, 231-245,
Cambardella C.A., Moorman T.B., Novak J.M., Parkin T.B., Karlen D.L., Turco R.F., and Konopka A.E., 1994. Field‐scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J., 58, 1501-1511,
Davidson E.A. and Janssens I.A., 2006. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 440, 165-173,
Delelegn Y.T., Purahong W., Blazevic A., Yitaferu B., Wubet T., Goransson H., and Godbold D.L., 2017. Changes in land use alter soil quality and aggregate stability in the highlands of northern Ethiopia. Sci. Rep., 7, 13602,
Deng X., Chen X., Ma W., Ren Z., Zhang M., Grieneisen M.L., Long W., Ni Z., Zhan Y., and Lv X., 2018. Baseline map of organic carbon stock in farmland topsoil in East China. Agric. Ecosyst. Environ., 254, 213-223,
Durdevic B., Jug I., Jug D., Bogunovic I., Vukadinovic V., Stipesevic B., and Brozovic B., 2019. Spatial variability of soil organic matter content in Eastern Croatia assessed using different interpolation methods. Int. Agrophys., 33(1), 31-39,
Gelaw A.M., Singh B.R., and Lal R., 2014. Soil organic carbon and total nitrogen stocks under different land uses in a semi-arid watershed in Tigray, Northern Ethiopia. Agric. Ecosyst. Environ., 188, 256-263,
Ghosh A., Bhattacharyya R., Meena M.C., Dwivedi B.S., Singh G., Agnihotri R., and Sharma C., 2018. Long-term fertilization effects on soil organic carbon sequestration in an Inceptisol. Soil Tillage Res., 177, 134-144,
Guan F., Tang X., Fan S., Zhao J., and Peng C., 2015. Changes in soil carbon and nitrogen stocks followed the conversion from secondary forest to Chinese fir and Moso bamboo plantations. Catena, 133, 455-460,
Hebei Statistical Bureau, 2021. Hebei Statistical Yearbook (in Chinese). China Statistics Press, Beijing.
Hopple A.M., Wilson R.M., Kolton M., Zalman C.A., Chanton J.P., Kostka J., Hanson P.J., Keller J.K., and Bridgham S.D., 2020. Massive peatland carbon banks vulnerable to rising temperatures. Nat. Commun., 11, 1-7,
James J.N., Gross C.D., Dwivedi P., Myers T., Santos F., Bernardi R., Faria M.F.D., Guerrini I.A., Harrison R., and Butman D., 2019. Land use change alters the radiocarbon age and composition of soil and water-soluble organic matter in the Brazilian Cerrado. Geoderma, 345, 38-50,
Janzen H.H., 2004. Carbon cycling in earth systems – a soil science perspective. Agric Ecosyst. Environ., 104, 399-417,
Jing L., Qingwen M., Wenhua L., Yanying B., and Zheng Y., 2014. Spatial variability analysis of soil nutrients based on GIS and geostatistics: a case study of Yisa township, Yunnan, China. J. Res. Ecol., 5, 348-355,
Johnston C.A., Groffman P., Breshears D.D., Cardon Z.G., Currie W., Emanuel W., Gaudinski J., Jackson R.B., Lajtha K., Nadelhoffer K., Nelson D.Jr., Post W.M., Retallack G., and Wielopolski L., 2004. Carbon cycling in soil. Front. Ecol. Environ., 2, 522-528,
Joss S., Cowley R., and Tomozeiu D., 2013. Towards the ‘ubiquitous eco-city’: an analysis of the internationalisation of eco-city policy and practice. Urban Research & Practice, 6, 54-74,
Keith H., Vardon M., Obst C., Young V., Houghton R.A., and Mackey B., 2021. Evaluating nature-based solutions for climate mitigation and conservation requires comprehensive carbon accounting. Sci. Total Environ., 769, 144341,
Kirschbaum M.U.F., 2000. Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry, 48, 21-51,
Lal R., 2004. Soil carbon sequestration impacts on global climate change and food security. Science, 304, 1623-1627,
Li M., Han X., Du S., and Li L.J., 2019. Profile stock of soil organic carbon and distribution in croplands of Northeast China. Catena, 174, 285-292,
Liu T.L., Juang K.W., and Lee D.Y., 2006. Interpolating soil properties using kriging combined with categorical information of soil maps. Soil Sci. Soc. Am. J., 70, 1200-1209,
Liu Y., He N., Zhu J., Xu L., Yu G., Niu S., Sun X., and Wen X., 2017. Regional variation in the temperature sensitivity of soil organic matter decomposition in China’s forests and grasslands. Glob. Chang. Biol., 23, 3393-3402,
Long J., Liu Y., Xing S., Zhang L., Qu M., Qiu L., Huang Q., Zhou B., and Shen J., 2020. Optimal interpolation methods for farmland soil organic matter in various landforms of a complex topography. Ecol. Indic., 110, 105926,
Long J., Liu Y.L., Xing S.H., Qiu L.X., Huang Q., Zhou B.Q., Shen J.Q., and Zhang L.M., 2018. Effects of sampling density on interpolation accuracy for farmland soil organic matter concentration in a large region of complex topography. Ecol. Indic., 93, 562-571,
Long J., Zhang L.M., Shen J.Q., Zhou B.Q., Mao Y.L., Qiu L.X., and Xing S.H., 2014. Spatial interpolation of soil organic matter in farmlands in areas complex in landform (in Chinese). Acta Petrol. Sin., 51, 1270-1281.
Luo Z., Luo Y., Wang G., Xia J., and Peng C., 2020. Warming-induced global soil carbon loss attenuated by downward carbon movement. Glob. Chang. Biol., 26, 7242-7254,
Mabit L. and Bernard C., 2010. Spatial distribution and content of soil organic matter in an agricultural field in eastern Canada, as estimated from geostatistical tools. Earth Surf. Process. Landf., 35, 278-283,
Minasny B., Malone B.P., McBratney A.B., Angers D.A., Arrouays D., Chambers A., Chaplot V., Chen Z.-S., Cheng K., Das B.S., Field D.J., Gimona A., Hedley C.B., Hong S.Y., Mandal B., Marchant B.P., Martin M., McConkey B.G., Mulder V.L., O’Rourke S., Richer-de-Forges A.C., Odeh I., Padarian J., Paustian K., Pan G., Poggio L., Savin I., Stolbovoy V., Stockmann U., Sulaeman Y., Tsui C.-C., Vågen T.-G., van Wesemael B., and Winowiecki L., 2017. Soil carbon 4 per mille. Geoderma, 292, 59-86,
Ministry of Natural Resources, People’s Republic of China, 2017. Current Land Use Classification: GB/T 2010-2017. China Zhijian Publishing House, Beijing, China.
Pan G., Xu X., Smith P., Pan W., and Lal R., 2010. An increase in topsoil SOC stock of China’s croplands between 1985 and 2006 revealed by soil monitoring. Agric. Ecosyst. Environ., 136, 133-138,
Pang S., Li T.X., Zhang X.F., Wang Y.D., and Yu H.Y., 2011. Spatial variability of cropland lead and its influencing factors: A case study in Shuangliu county, Sichuan province, China. Geoderma, 162, 223-230,
Panja P., 2021. Deforestation, Carbon dioxide increase in the atmosphere and global warming: A modelling study. Int. J. Simul. Model., 41, 209-219,
Robinson T.P. and Metternicht G.M., 2006. Testing the performance of spatial interpolation techniques for mapping soil properties. Comput. Electron. Agric., 50, 97-108,
Scharlemann J.P.W., Tanner E.V.J., Hiederer R., and Kapos V., 2014. Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manag., 5, 81-91,
Schiedung M., Tregurtha C.S., Beare M.H., Thomas S.M., and Don A., 2019. Deep soil flipping increases carbon stocks of New Zealand grasslands. Glob. Chang. Biol., 25, 2296-2309,
Stockmann U., Adams M.A., Crawford J.W., Field D.J., Henakaarchchi N., Jenkins M., Minasny B., McBratney A.B., Courcelles de V.R., Singh K., Wheeler I., Abbott L., Angers D.A., Baldock J., Bird M., Brookes P.C., Chenu C., Jastrow J.D., Lal R., Lehmann J., O’Donnell A.G., Parton W.J., Whitehead D., and Zimmermann M., 2013. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agric. Ecosyst. Environ., 164, 80-99,
Sun W.X., Shi X.Z., Yu D.S., Wang K., and Wang H.J., 2004. Estimation of soil organic carbon storage based on 1 : 1 M soil database of China (in Chinese). Sci. Geol. Sin., 24, 568-572.
Tang X., Xia M., Pérez-Cruzado C., Guan F., and Fan S., 2017. Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China. Sci. Rep., 7, 1-13,
Tripathi R., Nayak A.K., Shahid M., Raja R., Panda B.B., Mohanty S., Kumar A., Lal B., Gautam P., and Sahoo R.N., 2015. Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging. Arab. J. Geosci., 8, 10693-10703,
Vasenev V.I., Stoorvogel J.J., Vasenev I.I., and Valentini R., 2014. How to map soil organic carbon stocks in highly urbanized regions? Geoderma, 226, 103-115,
Viscarra Rossel R.A., Webster R., Bui E.N., and Baldock J.A., 2014. Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change. Glob. Chang. Biol., 20, 2953-2970,
Wang Q.B., Duan Y.Q., and Wei Z.Y., 2009. Spatial variability of urban soil organic carbon in Shenyang City (in Chinese). Chin. J. Soil Sci., 40, 252-257.
Whalen J.K., Willms W.D., and Dormaar J.F., 2003. Soil carbon, nitrogen and phosphorus in modified rangeland communities. Rangel. Ecol. Manag., 56, 665-672,
Wu H., Guo Z., and Peng C., 2003. Land use induced changes of organic carbon storage in soils of China. Glob. Chang. Biol., 9, 305-315,
Xu D., Liu C.H., Cai T.Y., and Zhang S.E., 2015. 3D spatial distribution characteristics of soil organic matter and total nitrogen in farmland (in Chinese). Transactions of the Chin. Soc. Agric. Machin., 46, 157-163.
Xu Y., Sun X., and Tang Q., 2016. Human activity intensity of land surface: Concept, method and application in China. J. Geogr. Sci., 26, 1349-1361,
Xue Z., Ma L., An S., and Wang W., 2015. Soil organic carbon density and stock at the catchment scale of a hilly region of the loess plateau (in Chinese). Acta Ecological Sinica, 35, 2917-2925,
Yan Y., Zhang C., Hu Y., and Kuang W., 2015. Urban land-cover change and its impact on the ecosystem carbon storage in a dryland city. Remote Sens., 8, 6,
Yang Y., Mohammat A., Feng J., Zhou R., and Fang J., 2007. Storage, patterns and environmental controls of soil organic carbon in China. Biogeochemistry, 84, 131-141,
Yao R., Yang J., Liu G., and Zou P., 2006. Spatial variability of soil salinity in characteristic field of the Yellow River Delta (in Chinese). Transactions of the CSAE, 22, 61-66.
Yao X., Yu K., Deng Y., Zeng Q., Lai Z., and Liu J., 2019. Spatial distribution of soil organic carbon stocks in Masson pine (Pinus massoniana) forests in subtropical China. Catena, 178, 189-198,
Ye J., Hu Y., Zhen L., Wang H., and Zhang Y., 2021. Analysis on land use Change and its driving mechanism in Xilingol, China, during 2000-2020 using the Google Earth engine. Remote Sens., 13, 5134,
Yu P.J., Li Q., Jia H.T., Li G.D., Zheng W., Shen X.J., Diabate B., and Zhou D.W., 2014. Effect of cultivation on dynamics of organic and inorganic carbon stocks in Songnen plain. Agron. J., 106, 1574-1582,
Zhang X.Y., Liu M.Z., Zhao X., Li Y.Q., Zhao W., Li A., Chen S., Chen S.P., Han X.G., and Huang J.H., 2018. Topography and grazing effects on storage of soil organic carbon and nitrogen in the northern China grasslands. Ecol. Indic., 93, 45-53,
Zhang Y., Li P., Lie X., Zhao B., and Peng S., 2019. Effects of topography and land use on soil organic carbon in hilly region of Loess Plateau (in Chinese). Acta Pedo. Sin., 56, 1140-1149.
Zhang Z., Zhou Y., and Huang X., 2021. Exploring the optimal sampling density to characterize spatial heterogeneity of soil carbon stocks in a Karst Region. Agron. J., 113, 99-110,
Zou Y. and Zhao W., 2018. Making a new area in Xiong’an: Incentives and challenges of China’s “Millennium Plan”. Geoforum, 88, 45-48,