地理空间分析综合应用

江浙典型茶园土壤有机质空间异质性分析

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  • 1. 南京师范大学新型城镇化与土地问题研究中心, 南京210023;
    2. 江苏省地理信息资源开发与利用协同创新中心, 南京210023;
    3. 江苏省物质循环与污染控制重点实验室, 南京210023
徐云鹤(1990-),男,江苏灌南人,硕士生,研究方向为土地资源管理。E-mail:jslygxuyunhe@126.com

收稿日期: 2014-11-13

  修回日期: 2015-01-08

  网络出版日期: 2015-05-10

基金资助

国家自然科学基金项目"优质农产品地理特征指标的测度研究——以江浙地区优质茶叶为例"(41271189)。

Study on Spatial Heterogeneity of the Soil Organic Matter in Typical Tea Gardens of Jiangsu Province and Zhejiang Province

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  • 1. New Urbanization and Rural Land Problem Research Center, Nanjing Normal University, Nanjing 210023, China;
    2. Geographic Information Resources Development and Collaborative Utilization Innovation Center in Jiangsu Province, Nanjing 210023, China;
    3. Materials Cycling and Pollution Control Key Laboratory in Jiangsu Province, Nanjing 210023, China

Received date: 2014-11-13

  Revised date: 2015-01-08

  Online published: 2015-05-10

摘要

茶园土壤有机质分布有明显的空间性,如何凭借有限的采样点数据预测研究区的有机质分布,对了解茶叶种植区土壤状况、指导茶园经营管理、提高茶叶品质和产量有重要意义。本文对江浙4种名茶种植区,利用描述性统计,以及地统计学中的半方差函数模型、空间插值等方法对比分析了茶园土壤有机质的空间异质性。研究结果表明:(1)4个研究区的土壤有机质平均水平均较高,适合茶叶生长,且浙江省2个茶叶种植区的有机质平均水平高于江苏省2个茶叶种植区的有机质水平;(2)半方差函数模型拟合表明,溪龙乡种植区有机质含量表现出中等空间相关性,而其他3个种植区表现出强烈的空间相关性;(3)各种植区土壤有机质的空间分布以结构性因子(土壤理化性质、地形地貌)为基础,受人类活动、经营模式、茶园管理等随机性因子影响,整体趋势上表现出局部变异的特征。

本文引用格式

徐云鹤, 方斌 . 江浙典型茶园土壤有机质空间异质性分析[J]. 地球信息科学学报, 2015 , 17(5) : 622 -630 . DOI: 10.3724/SP.J.1047.2015.00622

Abstract

The distribution of organic matters in tea garden soil shows an obvious spatial pattern. Methods to predict the distribution of organic matters in the study region using data from a limited series of sampling points is very important in studying the soil status of tea gardens, providing guidance to manage tea gardens, and improving tea quality and products. In this paper, we made a research on 4 famous tea planting areas in Jiangsu Province and Zhejiang Province, and we conducted a comparative analysis on the spatial heterogeneity of the organic matters in tea garden soil using descriptive statistics and geostatistics, which included the semi-variogram model and the spatial interpolation diagram analysis. Furthermore, we explored the spatial distribution characteristics of the organic matters in tea garden soil and its influencing factors. The results showed that: (1) the average level of the soil organic matters in all of the four study areas was favorable for tea growth. In addition, the average level of soil organic matters in Zhejiang Province was higher than that in Jiangsu Province. (2) The semi-variance function models proposed that a medium spatial correlation existed in the organic content of Xilong growing area, while a strong spatial correlation was discovered in the other three areas. The interpolation map showed that regions with high organic content in the two study areas of Zhejiang was had broader ranges than the other two study areas in Jiangsu. (3) We also conducted a qualitative analysis on factors influencing the spatial distribution of organic matters, based on relevant literatures, investigations and data. As a result, we found that the spatial distribution of organic matters in each area was determined by the structural factors, such as the soil physicochemical properties and the characteristics of landforms. Moreover, the random factors, such as human activities, business operation modes, tea garden management, and proper protection strategies, also had local impacts on the distribution of organic matters.

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