Color is the most striking visual feature of soil, is the first understanding of soil, it can indicate soil properties, processes and fertility, is an important indicator of soil diagnosis classification and quality evaluation. Shangshua Gong divides the Kyusong soil of the Central Plains into yellow soil, white soil, black graves, white graves, red-planted graves and Qingli.
Beijing Zhongshan Park social altar paved with five-color soil, the east for cyan, the south for red, the west for white, the north for black, the middle for yellow, perhaps the earliest expression of soil color distribution of totems. With the development of modern soil science, there is more understanding of soil color distribution in China, for example, according to soil classification, soil in the eastern part of China from south to north is roughly brick red soil – red soil – red soil – yellow soil – yellow brown soil – brown soil – dark brown soil and brown conifer forest soil and other regional distribution.
According to research, this classification is the world’s most color-named soil scheme. Naming soil by soil color is of course simple and reasonable to a certain extent, however, in fact, soil color in both horizontal direction and profile depth direction has a high degree of variability, soil scientists often find that in a color-named soil area there will be completely different (color) soil, but at home and abroad on soil color spatial variation research is very little.
Sun Yat-sen Park, Beijing.
China’s vast area, soil landscape complex and diverse, how to draw a more fine national soil color spatial distribution under the conditions of limited sparse soil survey samples, is a challenging problem. Conventional statistical interpolation method relies only on sample points for interpolation, it is difficult to reveal the details of soil color space changes, and its assumptions are harsh, the sample size and distribution are also high, not suitable for complex areas and sparse sample conditions. In response, Zhang’s team of researchers used the predictive soil mapping (Predictive Soil, PSM) method based on the theory of soil landscape relations to digitally map soil colors, which has not been reported in the world.
Munsell color data from nearly 5,000 soil survey profiles obtained in recent years by our Land System Survey and the China Soil Research Project were used as samples, and soil-forming environmental factors such as climate, maternal and topographical features were quantified using remote sensing and GIS technology to form a data set of soil-forming environment covering the whole country, using a collection of machine learning algorithm random forests (Random). Forest established a model of the relationship between soil color (dry and moisturizing) and soil-growing environmental conditions, and inferred soil colors at a total depth of 5,10,15,25,35,55,100,125cm, resulting in a three-dimensional distribution of soil colors across the country, using RGB and Monsell colors.
25cm depth soil Mensell color (run) map.
25cm depth soil color (run state) local detail map: Xi’an area (left) and Chengdu area (right)
5cm (left column) and 50cm (right column) depth soil color (run state) Menser tone (hue), lightness (value) and color (chorma) distribution.
This work is an important part of the construction of China’s soil information grid, providing China’s first consistent and detailed view of soil color, is the soil process model, soil fertility quality evaluation and space management of the key parameters, can serve the court soil physical evidence traceability research, but also to disseminate soil diversity to the public, enhance soil protection awareness of valuable tools. The results were published in geoderma, an internationally renowned soil journal (https://doi.org/10.1016/j.geoderma.2020.114556), with a spatial resolution of 1km and free download (https://dx.doi.org/10.11666/00072.ver1.db). The research was supported by the special “Survey of Our Land Department and the Preparation of the Chinese Soil Journal” (2008 FY110600 and 2014FY110200), the National Key Research and Development Program (2018YFE0107000) and the “One Three Five” cutting-edge research project of the Nanjing Soil Research Institute of the Chinese Academy of Sciences.