黑龙江各地区土壤不同深度湿度差数据

研究10CM及20CM深度的土壤湿度差，可以揭示该层土壤湿度的垂直分布规律。这种湿度梯度对于理解土壤热传递过程、土壤水分蒸发、土壤微生物活动等具有重要意义。大多数作物的根系主要分布在土壤表层以下的一定深度范围内，研究该层土壤湿度差有助于了解作物根系活动层的湿度状况。通过调节土壤湿度，可以优化作物生长环境，提高作物产量和品质。另外可结合地理信息系统（GIS）技术，将黑龙江各地区各地点的土壤地理数据和湿度差信息进行深度整合和分析，绘制位置-湿度差地图，以直观的可视化形式呈现给用户。1数据采集：每天中午12：00对黑龙江各地区不同的地点，随机在方圆1米直径内选3个土壤点，3个土壤点各采集10CM及20CM深度土壤湿度数据；2数据处理：将数据去噪、优化、补全；3数据加工：通过将20CM深度土壤湿度与10CM深度土壤湿度数据进行相减，得出3个采样点的土壤湿度差，分别为RH1、RH2和RH3，则该地点的土壤湿度差平均值RH4=（RH1+RH2+RH3）/3；3数据应用：根据土壤湿度差平均值RH4有助于了解作物根系活动层的湿度状况。

Studying the soil moisture difference between 10 cm and 20 cm soil depths can reveal the vertical distribution pattern of soil moisture within this depth interval. This moisture gradient is of great significance for comprehending soil heat transfer processes, soil water evaporation, soil microbial activities, and other relevant ecological processes. Most crop roots are primarily distributed within a certain depth range below the soil surface; thus, investigating the soil moisture difference in this layer aids in understanding the moisture conditions of the crop root activity zone. Adjusting soil moisture can optimize the crop growth environment, thereby improving crop yield and quality. Additionally, by integrating Geographic Information System (GIS) technology, in-depth integration and analysis can be conducted on soil geographic data and moisture difference information of various sites in Heilongjiang Province, followed by the generation of a site-moisture difference map, which is presented to users in an intuitive visual format.

1. Data Collection: At 12:00 noon daily, at various sites across different regions of Heilongjiang Province, three soil sampling points are randomly selected within a 1-meter diameter circle, and soil moisture measurements at 10 cm and 20 cm depths are collected for each of the three sampling points.
2. Data Preprocessing: Denoise, optimize and impute the collected datasets.
3. Data Calculation: Subtract the 10 cm depth soil moisture data from the 20 cm depth data to derive the soil moisture differences of the three sampling points, denoted as RH1, RH2 and RH3 respectively. The average soil moisture difference for the site is then calculated as RH4 = (RH1 + RH2 + RH3)/3.
4. Data Application: The average soil moisture difference RH4 can facilitate understanding of the moisture status within the crop root activity zone.

搜集汇总

数据集介绍

特点

该数据集由杭州森安农林科技有限公司提供，记录了黑龙江各地区不同地点10CM及20CM深度的土壤湿度数据，通过计算湿度差（RH值）揭示土壤湿度的垂直分布规律。数据规模为7745条，每日更新，适用于农业研究和GIS技术应用。