江西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，将江西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对江西各地区不同的地点，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 in this layer. This moisture gradient is critical for comprehending soil heat transfer processes, soil water evaporation, soil microbial activities, and other relevant agro-ecological processes. Most crop roots are primarily distributed within a specific 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 crop growth environments and enhance both crop yield and quality. Additionally, by integrating Geographic Information System (GIS) technology, in-depth integration and analysis can be performed on soil geographic data and moisture difference information for various locations across Jiangxi Province, and a location-moisture difference map can be generated to present the findings to users in an intuitive visual format.
1. Data Collection: At 12:00 noon daily, at various locations throughout Jiangxi Province, 3 soil sampling points are randomly selected within a 1-meter diameter circle, and soil moisture data at 10 cm and 20 cm depths are collected from each of the three points.
2. Data Preprocessing: Denoise, optimize, and complete the collected dataset.
3. Data Calculation: By subtracting the 10 cm depth soil moisture data from the 20 cm depth soil moisture data, the soil moisture differences of the 3 sampling points are obtained, which are denoted as RH1, RH2 and RH3 respectively. The average soil moisture difference RH4 of the location is calculated as RH4 = (RH1 + RH2 + RH3)/3.
4. Data Application: The average soil moisture difference RH4 can assist in understanding the moisture conditions of the crop root activity zone.

搜集汇总

数据集介绍

特点

该数据集记录了江西各地区土壤在10CM和20CM深度的湿度差数据，包含8067条记录，每日更新。数据通过多点土壤温湿度记录仪采集，并经过去噪、优化、补全等处理，用于研究土壤湿度垂直分布规律及其对作物生长的影响。