干旱区生态环境知识资源中心(Arid): 基于国产高分一号卫星数据的区域土壤盐渍化信息提取与建模

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	基于国产高分一号卫星数据的区域土壤盐渍化信息提取与建模
其他题名	Extraction and Modeling of Regional Soil Salinization Based on Data from GF-1 Satellite
	曹雷; 丁建丽; 玉米提·哈力克; 苏雯; 宁娟; 缪琛; 李焕
来源期刊	土壤学报
ISSN	0564-3929
出版年	2016
卷号	53 期号:6 页码:1399-1409
中文摘要	土壤盐渍化是干旱半干旱地区土地退化的主要原因之一,给当地生态系统和社会经济的可持续发展带来了严重的威胁,而对盐渍化空间分布信息的提取是治理盐渍化的基础。因此,选取生态脆弱区渭一库绿洲为研究区,利用2014年7月19日GF-1多光谱影像数据,提取光谱指数及波段信息,结合实际采样点的土壤表层电导率数据(0~10 cm),采用偏最小二乘回归模型(partial least squares regression, PLSR)对土壤盐渍化进行模拟,并对研究区盐渍化分布进行模拟和评估。结果表明:实测土壤表层电导率与光谱指数相关性较好;利用PLSR对渭一库绿洲土壤表层盐渍信息建模,对土壤盐渍化信息提取效果较好,精度较高;充分利用了GF-1影像包含的信息,提高了高分辨率遥感影像盐渍化信息提取的精度;非盐渍化和轻度盐渍化面积分别占总面积的42.88%和17.16%,绿洲中部偏东及东南区域,盐渍化现象稍弱,可成为今后绿洲扩张的重点方向;而中度盐渍化、重度盐渍化和盐土面积分别占总面积的29.51%、8.57%和1.88%,绿洲北部/西部及西南方向的重度盐渍化区域紧挨绿洲区域,已严重威胁了绿洲经济的健康发展,亟待治理。
英文摘要	【Objective】 Soil salinization, being one of the main causes of land degradation in arid and semi-arid regions, poses a great threat to sustainable development of the local social economy and ecological system. 【Method】 How to extract the information of spatial distribution of soil salinization is the foundation for management of soil salinization. Therefore, the Weigan-Kuqa Oasis, an area rather fragile in ecology, was selected as an object in this study, using the GF-1 satellite multispectral images of the date of July 19,2014 as the main data source. A total of 16 spectral indices i.e. Normalized difference vegetation index (NDVI),soil adjusted vegetation index (SAVI), normalized differential salinity index (NDSI),salinity index (SI-T),brightness index (BI),salinity index (SI), salinity index 1 (SI1),salinity index 2 (SI2),salinity index 3 (SI3),salinity index (S1),salinity index (S2), salinity index (S3),salinity index (S5), salinity index (S6), intensity index 1 (Int1),intensity index 2 (Int2),and four bands, i.e. band 1 (B1),band 2 (B2),band 3 (B3) and band 4 (B4), were chosen for analysis. The images in pretreatment were computed by band in line with the spectral index formulas with the aid of software ENVI4.8. Hence, gray scale maps of different spectral indices were derived and pixel values of the 36 sampling points corresponding to the gray scale maps were extracted. The data of electrical conductivities in the surface soil layers (0 ~ 10 cm) of those sampling sites during 22 ~ 28 July 2014 were also collected for analysis of Pearson correlation with the pixel values using software SPSS 19.0. Thus sensitivities of different spectral indices to the data of soil salinization were figured out. PLSR models were built and validated for relationships of the mathematical formulas for five different electrical conductivities (i.e. measured conductivity, reciprocal of measured conductivity, logarithm of measured conductivity, MSR of measured conductivity and reciprocal of the logarithm of measured conductivity) with spectral indices. Measured conductivities of 24 samples were used for modeling and the remaining 12 samples for validation with the aid of the Unscrambler X10.3 software. 【Result】 Results show: 1) the measured surface soil conductivities are closely related to spectral indices, and moderately to SAVI, NDVI, NDSI, SI, SI1, S5, B3 and B4,with all correlations being significant at the 0.01 level; 2) based on the GF-1 satellite images PLSR was used for modeling of surface soil salinization in the Weigan-Kuqa Oasis. The model based on reciprocal of electrical conductivity is better than all the others with R~2 =0.69 and RMSE=0.58 dS m~(-1). For the validation model R~2 is 0.78 and RMSE 0.53 dS m~(-1). In the images of satellite vertical projection salinized and non salinized patches in the land cover can be clearly distiquished from each other, with little confusing or mistaking information. Characteristic texture of salinization relative to degree is distinct, showing a clear layered structure, easy to distinquish and making the visual interpretation of the images more consistent with the actual degree of soil salinization. Consequently the effect of information extraction of soil salinization is quite good and high in precision; 3) this study made full use of the information contained in GF-1 images, thus improving precision of the extraction of soil salinization information from GF-1 images. Non-salinized soil and slightly salinized soil in the oasis accounts for 42.88% and 17.16%, respectively, of total in area.
中文关键词	土壤盐渍化 ; 高分一号 ; 光谱指数 ; 偏最小二乘回归法(PLSR) ; 渭一库绿洲
英文关键词	Soil salinization GF-1 Spectral indices PLSR Weigan-Kuqa oasis
类型	Article
语种	中文
国家	中国
收录类别	CSCD
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:5846810
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/235097
作者单位	曹雷, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 丁建丽, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 玉米提·哈力克, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 苏雯, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 宁娟, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 缪琛, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.; 李焕, 新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国.
推荐引用方式 GB/T 7714	曹雷,丁建丽,玉米提·哈力克,等. 基于国产高分一号卫星数据的区域土壤盐渍化信息提取与建模[J]. 新疆大学,2016,53(6):1399-1409.
APA	曹雷.,丁建丽.,玉米提·哈力克.,苏雯.,宁娟.,...&李焕.(2016).基于国产高分一号卫星数据的区域土壤盐渍化信息提取与建模.土壤学报,53(6),1399-1409.
MLA	曹雷,et al."基于国产高分一号卫星数据的区域土壤盐渍化信息提取与建模".土壤学报 53.6(2016):1399-1409.