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基于Landsat影像的崇明岛东滩土壤盐分遥感反演技术
引用本文:王多多,贾文晓,王志保,张瑞峰,陈美田,蔡永立.基于Landsat影像的崇明岛东滩土壤盐分遥感反演技术[J].中国农业科技导报,2018,20(3):55-63.
作者姓名:王多多  贾文晓  王志保  张瑞峰  陈美田  蔡永立
作者单位:1.华东师范大学生态与环境科学学院, 上海市城市生态过程与生态修复重点实验室, 上海 200241; 2.北京大学城市与环境学院, 北京 100871
基金项目:国家自然科学基金项目(31670474)资助。
摘    要:目前我国土地资源面临着严重的盐碱退化问题。以上海市崇明岛东滩盐碱土为研究对象,基于野外实地调查土壤盐分数据以及Landsat遥感影像数据计算获取的各波段反射率、盐分指数(salinity index,SI)、盐分指数1(salinity index 1,SI1)、归一化差分植被指数(normalized difference vegetation index,NDVI)、冠层盐分响应指数(canopy response salinity index,CRSI)和陆地表面水分指数(land surface water index,LSWI),采用多元样条自回归模型(multivariate adaptive regression splines,MARS)与偏最小二乘回归方法(partial least squares regression,PLSR)分别建立土壤盐分的回归模型,并对区域盐碱土的空间格局进行探究。结果表明:(1)滨海土壤盐分在近红外波段有明显的吸收作用,与近红外波段、短波红外波段和NDVI相关系数较高;(2)MARS模型较PLSR模型对于样点土壤盐分反演有更好的效果(R2分别为0.74和0.70);(3)崇明东滩滨海土壤盐分在空间上具有较高的异质性,水体附近和滩涂土壤盐分较高,林地和农田土壤盐分较低。该结果为滨海地区区域尺度上的土壤盐碱化监测提供范例,为滨海土壤盐渍化的治理及岛屿的生态建设提供参考依据。

关 键 词:遥感  土壤盐分  多元样条自回归模型  电导率  崇明岛东滩  

Retrieving Coastal Soil Saline Based on Landsat Image in Chongming Dongtan
WANG Duoduo,JIA Wenxiao,WANG Zhibao,ZHANG Ruifeng,CHEN Meitian,CAI Yongli.Retrieving Coastal Soil Saline Based on Landsat Image in Chongming Dongtan[J].Journal of Agricultural Science and Technology,2018,20(3):55-63.
Authors:WANG Duoduo  JIA Wenxiao  WANG Zhibao  ZHANG Ruifeng  CHEN Meitian  CAI Yongli
Institution:1.Shanghai Key Lab for Urban Ecological Processes and Eco-restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241; 2.College of Urban and Environmental Sciences,Peking University, Beijing 100871, China
Abstract:Currently, the national land resources are facing a serious problem of salt alkali degradation. Taking Chongming Dongtan saline alkali soil in Shanghai as object, this study applied multivariate adaptive regression splines model (MARS) and partial least squares regression (PLSR) to establish regression models of soil salinity and explore spatial pattern of regional saline alkali soil, based on the filed sampling soil saline data, and band reflectance, salinity index(SI), salinity index 1(SI1), normalized difference vegetation index(NDVI), canopy response salinity index (CRSI) and land surface water index(LSWI) calculated from Landsat remote sensing data. The results showed that: ① The coastal soil salinity performed obvious absorption in infrared band, and showed high correlations with infrared band, shortwave infrared band(SWIR1) and NDVI. ② MARS model had better performance in retrieving of soil salinity than PLSR (R2=0.74 and 0.70, respectively). ③ There was high spatial heterogeneity of soil salinity in Chongming Dongtan coastal area, with higher value near water body and intertidal zone, and lower value in forest and farmland. This paper present a fashion for the regional monitoring of soil salinization in coastal area, and provided valuable information for controlling coastal saline alkali soil deterioration and ecological construction of the island.
Keywords:remote sensing  saline alkali soil  multivariate adaptive regression splines model  conductivity  Chongming Dongtan  
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