Zoning the soil salinization levels in the northern China’s coastal areas based on high-resolution soil mapping

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-03-01 Epub Date: 2025-03-03 DOI:10.1016/j.ecolind.2025.113303
Yuan Chi , Minglei Fan , Zhiwei Zhang , Yubing Qu
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Abstract

Zoning the soil salinization levels in large-scale coastal areas is vital for understanding the spatiotemporal mechanism of soil salinization and guiding the coastal integrated management. However, it is difficult due to the complicated influencing factors and the high demands for a fine mapping resolution and precise simulation results. In the present study, the northern China’s coastal areas (> 6 4000 km2) were selected as the study area, and extensive field investigation, multispectral remote sensing images, and open-source land cover data served as the data source. A simulation unit of 100 m × 100 m was employed to precisely map the soil salinity (SS) based on a predictor system that covered different aspects of influencing factors, and high-resolution soil salinization maps were generated for the entire study area and different cities. Results indicated that the mapping obtained a relative-root mean squared error of 0.31, which was in a low level and denoted a high accuracy compared with previous studies. The soil salinization levels presented the following spatial heterogeneities: (1) The levels showed distinct polarization, that is, extremely low and high levels covered the most of the study area. (2) The SS exhibited a distinct decrease from the coastline to the inner land, and wetlands and water areas exhibited much higher SS than the remaining land cover types. (3) Muddy coasts suffered more severe soil salinization than rocky and sandy coasts in the alongshore areas. (4) The inner land was generally free from the salinization but some small patches of bare lands and water areas were still at risk. (5) Dongying, Binzhou, Weifang, and Yancheng Cities suffered much more distinct soil salinization than the remaining cities. The coastline and ecological quality were the major factors that determine the spatial pattern of soil salinization in the alongshore and inland areas, respectively.
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基于高分辨率土壤制图的中国北方沿海地区土壤盐碱化水平区划
大尺度沿海地区土壤盐渍化水平分区对于认识土壤盐渍化时空机制,指导沿海综合治理具有重要意义。然而,由于影响因素复杂,对精细的映射分辨率和精确的仿真结果要求很高,因此很难实现。在本研究中,中国北方沿海地区(>;选取64000 km2)作为研究区域,以广泛的野外调查、多光谱遥感影像和开源土地覆盖数据为数据源。采用100 m × 100 m模拟单元,基于覆盖不同方面影响因素的预测系统,对土壤盐渍化进行精确制图,生成了整个研究区和不同城市的高分辨率土壤盐渍化图。结果表明,该图谱的相对均方根误差为0.31,与以往研究相比处于较低水平,具有较高的精度。土壤盐渍化水平的空间异质性表现为:(1)土壤盐渍化水平呈现明显的两极分化,即极低水平和高水平覆盖了大部分研究区域。(2)从海岸线到内陆,土地覆被类型的SS明显减少,湿地和水域的SS明显高于其他土地覆被类型。(3)泥质海岸土壤盐渍化程度较岩石海岸和沙质海岸严重。④内陆地区盐渍化程度基本稳定,但仍有少量裸地和水域存在盐渍化风险。(5)东营、滨州、潍坊、盐城等城市土壤盐渍化程度明显高于其他城市。海岸线和生态质量分别是决定沿海和内陆地区土壤盐渍化空间格局的主要因素。
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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