快速准确地获取区域尺度土壤可蚀性因子(K)对可持续农业发展和水土保持管理非常重要。以抚州市106个土壤样本数据为基础，选取遥感光谱指数、地形因子和气候变量作为辅助，通过构建随机森林模型预测研究区30 m空间分辨率的K因子分布。结果表明，研究区K因子具有一定离散性，分布范围在0。0131(t·hm2·h)/(MJ·hm2·mm)～0。0447(t·hm2·h)/(MJ·hm2·mm)之间;环境变量中以气温、地形对 K 因子分布的影响最大，随机森林适用于K因子空间制图，验证精度R2达0。68，RMSE为0。007 t·hm2·h)/(MJ·hm2·mm)。本研究为水土流失评价因子的优化提供了新思路。
Study on Extraction of Soil Erosion Factors in Fuzhou City Based on Digital Mapping
Rapid and accurate acquisition of the soil erodibility factor(K)at a regional scale is crucial for sustainable agricultural development and soil and water conservation management.This study used 106 soil sample data from Fuzhou City as a foundation,selecting remote sensing spectral indices,terrain factors,and climatic variables as auxiliary information.A random forest model was built to predict the spatial distribution of the K factor at a 30 m resolution in the study area.The results indicate that the K factor distribution in the study area has a certain degree of dispersion,ranging from 0.0131 to 0.0447(t·hm2·h)/(MJ·hm2·mm).Among the environmental variables,temperature and terrain had the greatest influence on the distribution of the K factor.The random forest model is suitable for spatial mapping of the K factor,achieving a validation accuracy of R2=0.68 and RMSE=0.007(t·hm2·h)/(MJ·hm2·mm).This study provides new insights for optimizing soil erosion evaluation factors.
Digital mappingK factorspatial distributionrandom forest
万方数据
维普
