基于GF-1土壤含盐量的估测研究

发布时间：2018-09-09 11:26

【摘要】：土地盐碱化严重威胁着干旱、半干旱地区的稳定与可持续发展,因此利用遥感技术快速、准确估测土壤含盐量并及时掌握其空间分布具有重要的现实意义。以GF-1遥感影像为数据源,大庆市为研究对象,结合实地采样的土壤含盐量化验数据,探讨了土壤含盐量快速、准确的估测方法。研究表明:GF-1遥感影像的4个波段反射率与土壤含盐量存在显著的正相关性,且在第4波段达到峰值;反射率经过适当的数学变换可以有效提高与土壤含盐量的相关性,且反射率的指数变换与土壤含盐量的相关性最好,相关系数达到r=0.881;以第1波段反射率指数、第4波段反射率倒数的对数、第4波段反射率倒数建立的多元估测模型具有较高的估测精度与稳定性。研究结果充分说明利用GF-1遥感影像估测土壤含盐量是一种可行、精确、快速的方法,对于今后大区域土地盐碱化信息的快速提取及动态监测具有指导意义。
[Abstract]:Soil salinization is a serious threat to the stability and sustainable development of arid and semi-arid areas. Therefore, it is of great practical significance to use remote sensing technology to estimate soil salinity accurately and to grasp its spatial distribution in time. Taking GF-1 remote sensing image as the data source and Daqing city as the research object, the rapid and accurate estimation method of soil salt content was discussed. The results show that there is a significant positive correlation between the reflectivity of the four bands and the soil salinity in the fourth band, and the correlation between the reflectivity and the soil salt content can be improved by proper mathematical transformation. The correlation coefficient between reflectance and soil salt content is the best, and the correlation coefficient is 0.881.The first band reflectivity index, the logarithm of 4th band reflectance reciprocal, The multivariate estimation model based on the reciprocal reflectance of the fourth band has high estimation accuracy and stability. The results show that the GF-1 remote sensing image is a feasible, accurate and rapid method for estimating soil salinity, and it has a guiding significance for the rapid extraction and dynamic monitoring of soil salinization information in large areas in the future.
【作者单位】：辽宁省交通高等专科学校;
【基金】：国家自然科学基金项目(41371332) 中国地质调查局项目(1212010911084)资助
【分类号】：S156.41;S127

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