生态学报2017，Vol.37Issue(15)：5007-5022,16.DOI:10.5846/stxb201605090890
基于Landsat系列数据的盐分指数和植被指数对土壤盐度变异性的响应分析——以新疆天山南北典型绿洲为例
Sensitivity analysis of soil salinity and vegetation indices to detect soil salinity variation by using Landsat series images: applications in different oases in Xinjiang, China
摘要
Abstract
Several indices of vegetation and soil salinity have been developed to quantitatively evaluate soil salinization.This study was conducted to assess the soil salinity levels in the Fubei region (FG),Manas River Basin (MRB),and WeriganKuqa River Delta Oasis (WKRDO),which are distributed in the northern and southern Tianshan Mountains in Xinjiang,China.Ground measurements and remote sensing data were used to evaluate the sensitivity of vegetation and soil salinity indices to soil salinity variation in farmland and salt-affected land.A random sampling approach was used to collect soil samples from FG (n =37,only at 0-10-cm depth),MRB (n =58),and WKRDO (n =38).A total of 14,broadband indices encompassing vegetation and soil salinity indices were extracted from Landsat images.The correlation coefficient based on linear and non-linear models (10 models) between these indices,Landsat bands,and soil salinity was examined.The results showed that the extended enhanced vegetation index (EEVI) was the most effective for explaining the soil salinity variation at depths of 0-10 cm in two modes (all samples and partial samples with soil salinity (soil salt content) ＞0.3％) in FG.With the mode of all samples and partial samples (soil electric conductivity ＜2 dS/m) in MRB,band 2 yielded the best results for assessing the soil salinity of cultivated lands at the early stage of crop growth in April.The maximum depth of the significance test by using indices for detecting variation of soil salinity in this area was 30 cm.For all samples in WKRDO,the salinity index (SI-T) interpreted more variation of soil salinity than that by other indices at depths of 0-10 and 10-20 cm,and the three-band maximal gradient difference index (TGDVI) exhibited the highest significant correlation with salinity at 20-40 cm.In the mode of partial samples (soil salinity ＞2 dS/m),the most sensitive index for variation of soil salinity at 0-10,10-20,and 20-40 cm were band 5,TGDVI,and EEVI.In addition,the correlation of other indices (excluding those mentioned above) and soil salinity was highly dependent on land cover heterogeneity and sample period,and showed no significant relationships (p ＞ 0.05 or p ＞ 0.01).These results are preliminary conclusions,but in general,the soil salinity in Xinjiang dominated by different salt types was successfully assessed by broadband vegetation and soil salinity indices extracted from the Landsat images.However,relationships between remote sensing indices and soil salinity within fields are highly complex and require further investigation with additional samples and by using various soil salinity classifications.关键词
土壤盐渍化/盐分指数/植被指数/干旱区/LandsatKey words
soil salinization/salinity index/vegetation index/dryland/Landsat引用本文复制引用
王飞,丁建丽,魏阳,周倩倩,杨晓东,王前锋..基于Landsat系列数据的盐分指数和植被指数对土壤盐度变异性的响应分析——以新疆天山南北典型绿洲为例[J].生态学报,2017,37(15):5007-5022,16.基金项目
国家自然科学基金-新疆联合基金(U1603241) （U1603241）
新疆维吾尔自治区科技支疆项目(201591101) （201591101）
国家自然科学基金(41661046) （41661046）
中国博士后基金(2016M602909) （2016M602909）
新疆大学博士启动基金(BS150248) （BS150248）
新疆维吾尔自治区重点实验室专项基金(2014KL005) （2014KL005）
