%0 Journal Article %T Quantitative Evaluation of Mapping Precision of Historical Soil Maps with Landscape Indices %A HUANG,Jingjing %A YU,Yinxia %A YU,Dongsheng %A PAN,Yue %A LU,Xiaosong %A XU,Zhichao %J ACTA PEDOLOGICA SINICA %@ 0564-3929 %V 56 %N 1 %D 2019 %P 44-54 %K Landscape index; Soil type map; Mapping precision; Soil taxonomical level %X 【Objective】It is a precondition for making proper use of these precious data like soil maps to judge mapping precision of historical soil type maps.【Method】A map marked as 1: 250 000 scale Fujian Province soil map plotted on the basis of the soil survey data of the Second National Soil Survey, was collected and digitized into a vector soil map, which was rasterized by taxonomical hierarchy. From each level of the hierarchy, 50 raster grains, varying in interval from 30 m to 8 000 m, were selected for calculation of 15 landscape indices of each grain in three taxonomical levels, i.e. great group, subgroup and family, separately, using Fragstats 4.2, a software for landscape pattern analysis, and further for analysis of responses of the landscape indices to variation of the raster grains. Five landscape indices, i.e. TA, PR, PRD, SHDI and SHEI, were selected as indices to quantitatively evaluate soil mapping precision. The landscape indices corresponding to grains 30 m×30 m in size were set as benchmarks. Comparison was made of landscape indices corresponding to grains of various sizes with the benchmarks. Given that when the absolute values of relative variability (VIV, %) of all the selected landscape index are less than 1%, the corresponding maximum grain size is deemed as the optimal characterization grain size for data conversion from parent vector soil map to raster soil map. Then based on the functional relationship, y= -0.80×10-6x2 + 0.0 228x + 0.0 211(R2 = 0.9994,P< 0.05), between optimal characterization grain size and soil mapping scale, soil mapping scales could be deduced and mapping precision of the map quantitatively evaluated. 【Result】Results show that landscape index is obviously grain-size dependent, and based on the trend of landscape indices varying with rising grain size, grain-size dependence of landscape indices could be divided into four types, i.e. Type I: landscape indices increasing with rising grain size, such as PAFRAC and AREA_SD; Type II: landscape indices declining with rising grain size, such as TE, LSI, COHESION and AI; Type III: landscape indices varying irregularly with rising grain size, such as LPI, DIVISION, MESH and SPLIT; and Type Ⅳ: landscape indices remaining almost unchanged or fluctuating later on with rising grain size, such as TA, PR, PRD, SHDI and SHEI. The optimal characterization grain size at the soil great group level, subgroup level and family level is 4.00 km×4.00 km, 3.45 km×3.45 km and 1.90 km×1.90 km, respectively, and their corresponding soil map scale, 1: 1 800 000, 1: 1 600 000 and 1: 850 000, respectively, which all differ significantly from the marked map scale 【Conclusion】This study provides a novel and effective way and method to judge mapping precision of historical soil maps, which is of great value to correctly judge and utilize precious historical soil data. %R 10.11766/trxb201803070048 %U http://pedologica.issas.ac.cn/trxben/home %1 JIS Version 3.0.0