基于光学和雷达多源遥感的于田绿洲土壤盐渍化时空分析

doi:10.13866/j.azr.2023.01.07

摘要/Abstract

摘要：

目前土壤盐渍化是全球重要的环境问题，探明于田绿洲土壤盐渍化的时空变化规律，挖掘雷达遥感探测土壤盐分的优势，对干旱区绿洲的土壤盐渍化时空变化进行监测评估。以于田绿洲为研究区，基于PALSAR-2、Sentinel-1极化合成孔径雷达数据和Landsat 8 OLI等多源数据集，筛选雷达影像的最优后向散射特征与主成分分析后的光学影像组合，最后利用随机森林方法进行图像分类，定量提取于田绿洲土壤盐渍化信息，对土壤盐渍化时空变化进行分析。结果表明：（1）在同时使用随机森林分类方法下，各年的光学影像总体精度平均为80.36%，Kappa系数平均为0.77；光学影像结合雷达影像的分类精度比光学影像分类精度高，总体精度平均为85.62%，Kappa系数平均为0.82。（2） 2015—2021年于田绿洲产生土壤盐渍化的区域主要分布于研究区北部的绿洲边缘和荒漠交错带。（3） 2015—2021年盐渍地面积年均变化量为-1120.55 hm²·a^-1，变化率为-10.67%。于田绿洲盐渍化程度总体呈下降趋势，盐渍化以轻中度盐渍地为主。

关键词: 土壤盐渍化, 合成孔径雷达, Landsat 8 OLI, 随机森林分类, 时空变化

Abstract:

Soil salinization is currently a prominent global environmental problem. Spatiotemporal variation of soil salinization in Yutian Oasis was explored, and the advantages of radar remote sensing in excavated soil salinity were investigated to monitor and evaluate the temporal and spatial variabilities of soil salinization in arid oasis. Based on Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2), Sentinel-1 polarimetric synthetic aperture radar data, and Landsat 8 Operational Land Imager (Landsat 8 OLI) multi-source dataset, the optimal backscattering characteristics of radar images were selected, and optical images were combined based on principal component analysis. Finally, the random forest method was used to classify the images. Quantitative extraction of soil salinization information in Yutian Oasis and the spatial and temporal variation of soil salinization were analyzed. Results showed that (1) under the random forest classification approach, the total accuracy of optical images in each year was 80.36%, and the kappa coefficient was 0.77. The classification accuracy of optical images combined with radar images was higher than that of optical images, the total accuracy was 85.62%, and the kappa coefficient was 0.82. (2) From 2015 to 2021, the area of salinized soil in Yutian Oasis was mainly distributed in the north of the study area, interlaced edge of the oasis, and desert. (3) The average annual variation of saline land area from 2015 to 2021 was -1120.55 hm²·a^-1, and the change rate was -10.67%. The salinization of Yutian Oasis generally showed a downward trend and was mainly mild to moderate saline land.

Key words: soil salinization, synthetic aperture radar, Landsat 8 OLI, random forest classification, spatial and temporal variation

肖森天, 依力亚斯江·努尔麦麦提, 努尔比耶·穆合塔尔, 赵静, 阿迪莱·阿卜来提. 基于光学和雷达多源遥感的于田绿洲土壤盐渍化时空分析[J]. 干旱区研究, 2023, 40(1): 59-68.

XIAO Sentian, Ilyas NURMEMET, Nuerbiye MUHETAER, Zhao Jing, Adilai ABULAITI. Spatial and temporal analysis of soil salinity in Yutian Oasis by combined optical and radar multi-source remote sensing[J]. Arid Zone Research, 2023, 40(1): 59-68.

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卫星传感器	获取日期	分辨率/m	产品类型	极化方式/波段
PALSAR-2	2015-04-23	10×10	Level 1.1	VV、VH
Sentinel-1A	2018-04-23	10×10	GRD	VV、VH
Sentinel-1A	2021-04-18	10×10	GRD	VV、VH
Landsat8 OLI	2015-04-26	30×30	Level1T	1~7
Landsat8 OLI	2018-04-18	30×30	Level1T	1~7
Landsat8 OLI	2021-04-10	30×30	Level1T	1~7

序列	组合方式	简称	波段	备注
Ⅰ	PCA光谱特征	方式一	3	-
Ⅱ	后向散射特征	方式二	4	VV VV+VH VV²+VH (VV²+VH²)/VH
Ⅲ	PCA+后向散射特征	方式三	7	-

地物	数据集	样本J-M测度
地物	数据集	轻中度盐渍地	裸地	植被	水体
重度盐渍地	方式一	1.710	1.928	1.762	1.924
	方式二	1.274	1.249	1.456	1.684
	方式三	1.893	1.899	1.973	2.000

组合方式	2015年		2018年		2021年
组合方式	总体精度/%	Kappa系数	总体精度/%	Kappa系数	总体精度/%	Kappa系数
方式一	79.55	0.75	80.32	0.77	81.21	0.79
方式三	85.19	0.81	84.59	0.80	87.07	0.84

分类类别	2015年		2018年		2021年
分类类别	面积/hm²	比例/%	面积/hm²	比例/%	面积/hm²	比例/%
水体	4839.01	3.09	7652.32	4.88	5553.04	3.52
植被	61061.10	38.94	68645.04	43.78	71506.76	45.31
裸地	27970.34	17.84	25340.48	16.16	24533.92	15.54
轻中度盐渍地	41518.64	26.48	36462.24	23.25	32359.16	20.51
重度盐渍地	21411.11	13.65	18700.08	11.93	23847.28	15.12