摘要
【目的】研究2005~2018年黄河三角洲地区土壤盐分在年内和年际尺度上的时空变化特征。【方法】基于2005~2018年春季覆盖黄河三角洲地区的MODIS和Landsat系列数据,采用增强型自适应反射率时空融合模型(ESTARFM)获得30米分辨率高频地表反射率数据。基于2005年实测土壤盐分数据和Landsat地表反射率数据,采用随机森林方法建立土壤盐分反演模型,反演2005~2018年黄河三角洲地区春季土壤盐分数据,分析土壤盐分含量的时空演变特征。【结果】ESTARFM融合数据具有较为理想的精度,地表反射率总体误差在4%以内。年内尺度上,2~4月份黄河三角洲地区土壤盐分含量呈总体下降趋势,3~4月份存在盐分含量短期回升现象,进入4月份后,土壤盐分含量明显下降,非盐渍土和轻度盐渍土占比增加。年际尺度上,2005~2018年研究区土壤盐分含量呈先升后降趋势,最大值出现在2009年(4.262 g kg^(-1)),最小值出现在2005年(3.604 g kg^(-1))。2009年以来,研究区内非盐渍土和轻度盐渍土面积显著增加,盐土面积显著减少,盐渍化程度明显改善。【结论】增强型自适应反射率时空融合模型可用于高频次土壤盐分数据反演,反演结果可加深对土壤盐分年内和年际变化规律的认识。
[Objective]The spatio-temporal variations of soil salt content(SSC)at seasonal and inter-annual scales will be inversed in the Yellow River Delta from 2005 to 2018.[Method]This study derived 30-m resolution highfrequency surface reflectance data over the Yellow River Delta from 2005 to 2018 with the integration of the Moderateresolution Imaging Spectroradiometer(MODIS)and Landsat series sensors data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM).Based on soil sampling data in 2005 and the Landsat-5 Thematic Mapper(TM)surface reflectance data,a random forest model was established to model the relationship between SSC and spectral reflectance.The model was used to estimate multi-temporal SSC data from 2005 to 2018 based on which the spatio-temporal variations in SSC were analyzed.[Result]The ESTARFM performed well for deriving Landsat-like reflectance data with an overall uncertainty<4%.On seasonal scales,SSC showed a downward trend from February to April,with an occasional short-term rise in SSC from March to April.From April onwards SSC decreased significantly,shown as the increasing proportions of non-saline soils and slightly saline soils.On interannual scales,SSC first increased and then decreased from 2005–2018.The highest SSC value appeared in 2009(4.262 g kg^(-1)),and the lowest SSC value appeared in 2005(3.604 g kg^(-1)).Since 2009,the area of slightly saline soils has increased significantly,which means a substantial improvement in soil salinization.[Conclusion]The ESTARFM method can be used for high-frequency SSC mapping,which promotes our understanding towards intra-and interannual dynamics of soil salinity.
作者
余泽鸿
翁永玲
范兴旺
YU Ze-hong;WENG Yong-ling;FAN Xing-wang(School of Transportation,Southeast University,Nanjing 210096,China;Nanjing Instite of Geography and Limnology,Chinese Academy of Sciences,Nanjing 210008,China)
出处
《土壤通报》
CAS
CSCD
北大核心
2022年第4期757-767,共11页
Chinese Journal of Soil Science
基金
国家自然科学基金项目(41471352)资助。
关键词
黄河三角洲
土壤盐分
时空变化
数据融合
随机森林
Yellow River Delta
Soil salt content
Spatio-temporal variations
Data fusion
Random Forest