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中国高分辨率国家土壤信息格网基本属性数据集_90米土壤质地(2010-2018)

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国家地球系统科学数据中心2024-03-04 更新2024-04-21 收录
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https://www.geodata.cn/data/datadetails.html?dataguid=199621615162120&docId=3878
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资源简介:
土壤中各粒级占土壤重量的百分比组合,叫做土壤质地。土壤质地是土壤的最基本物理性质之一,对土壤的各种性状,如土壤的通透性、保蓄性、耕性以及养分含量等都有很大的影响,是评价土壤肥力和作物适宜性的重要依据。不同的土壤质地往往具有明显不同的农业生产性状,了解土壤的质地类型,对农业生产具有指导价值。本数据是全国范围的土壤质地高分辨率空间分布图,水平空间分辨率为90m,垂直方向包括六个土层深度:0-5, 5-15, 15-30, 30-60, 60-100, 100-200cm。 本数据集是基于2010-2018“我国土系调查与《中国土系志》编制项目”获得的土壤剖面样点,采用地理加权回归、随机森林等数字土壤制图方法生成的中国1公里分辨率100-200cm的土壤砂粒含量、土壤黏粒含量、土壤粉粒含量3项数据二次加工生成,质地分类使用美国制标准;

The combination of percentages of various particle sizes in soil relative to the total soil weight is called soil texture. Soil texture is one of the most fundamental physical properties of soil, which greatly affects various soil characteristics such as permeability, water and nutrient retention, tillability, and nutrient content, and serves as an important basis for evaluating soil fertility and crop suitability. Different soil textures often exhibit significantly different agricultural production characteristics, so understanding soil texture types has guiding significance for agricultural production. This dataset is a high-resolution spatial distribution map of soil texture across the entire country, with a horizontal spatial resolution of 90 meters, and covers six soil layer depths in the vertical direction: 0-5, 5-15, 15-30, 30-60, 60-100, and 100-200 cm. This dataset was secondarily processed from three datasets of soil sand content, clay content, and silt content at 100-200 cm depth with a 1 km resolution across China, which were generated based on soil profile sampling points obtained from the 2010-2018 "National Soil Series Survey and Compilation of China Soil Series Annals" project, using digital soil mapping methods such as geographically weighted regression and random forest. The soil texture classification follows the US standard.
提供机构:
中国科学院南京土壤研究所
创建时间:
2023-12-30
搜集汇总
数据集介绍
main_image_url
背景与挑战
背景概述
该数据集是中国2010-2018年土壤质地的高分辨率空间分布图,水平分辨率为90米,垂直方向覆盖0-200厘米的六个土层深度,基于全国5000多个土壤剖面样点,采用地理加权回归和随机森林等数字土壤制图方法生成,并使用美国制标准进行分类,具有较高的准确性和精细度,适用于土壤学研究和农业应用。
以上内容由遇见数据集搜集并总结生成
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