A soil colour map of China

	A soil colour map of China
	Liu, Feng; Rossiter, David G.; Zhang, Gan-Lin; Li, De-Cheng
刊名	GEODERMA
	2020
卷号	379
英文摘要	Soil colour can indicate soil physical, chemical and biological properties and processes, and is an important indicator for soil classification, soil quality evaluation and soil management. It varies in both horizontal and vertical dimensions, and thus regional maps of soil colour can reveal spatial patterns of these properties, processes, and indicators. However, although soil regions are sometimes named for their dominant soil colour, it is directly measured only at point support, i.e., during soil profile description, whereas it is desirable to know soil colour over the entire soilscape. To achieve this for China we used predictive soil mapping methods to produce soil colour maps (dry and moist colours) at 1 km(2) grid cell size and over multiple depths from a consistent dataset of approximately 4 600 full profile descriptions taken as part of a national survey to define soil series in Chinese Soil Taxonomy, and a set of environmental covariates covering the national territory. The covariates characterized soil forming factors including climate, parent materials, terrain, vegetation, land surface water and thermal conditions. Soil colour descriptions in the Munsell system were extracted from the genetic horizon descriptions at the selected depths and converted to the sRGB and Lab* colour spaces. Dry and moist colour separates were not well-correlated in either space (r < 0.76). Random forest models were constructed in both spaces, for dry and moist colours separately. Models in sRGB space were moderately successful (R-2 approximate to 0.43, RMSE approximate to 26/255) at 5 cm, with success decreasing with depth. Models smoothed the colour space and thus did not predict the more extreme values or chromas, nor the rarer hues. Models in Lab* space were less successful. The fitted sRGB models were used to produce predictive maps over all of China. Regional patterns as well as local detail are clearly shown. Solar radiation, wind exposure, regolith thickness, and Landsat TM bands 7 and 5 contributed most to the predictions, followed by elevation, mean annual precipitation, terrain wetness index, air temperature seasonality, precipitation standard deviation and standard deviation of NDVI. These suggest pedological processes acting on the development of soil colours, including weathering of parent materials, oxidation-reduction chemistry and biochemistry of the decomposing of organic matter. This study shows that predictive methods from points using suitable covariates are an alternative to spatial predictions over map units from their representative profiles.
内容类型	期刊论文
源URL	[http://159.226.73.51/handle/332005/19926]
专题	中国科学院南京地理与湖泊研究所
推荐引用方式 GB/T 7714	Liu, Feng,Rossiter, David G.,Zhang, Gan-Lin,et al. A soil colour map of China[J]. GEODERMA,2020,379.
APA	Liu, Feng,Rossiter, David G.,Zhang, Gan-Lin,&Li, De-Cheng.(2020).A soil colour map of China.GEODERMA,379.
MLA	Liu, Feng,et al."A soil colour map of China".GEODERMA 379(2020).