Spatial and temporal analysis of soil salinity in Yutian Oasis by combined optical and radar multi-source remote sensing
Received date: 2022-05-01
Revised date: 2022-07-22
Online published: 2023-02-24
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.
Sentian XIAO , NURMEMET Ilyas , MUHETAER Nuerbiye , Jing Zhao , ABULAITI Adilai . 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 . DOI: 10.13866/j.azr.2023.01.07
[1] | 孙媛, 贾萍萍, 尚天浩, 等. 基于地表高光谱与OLI影像的土壤含盐量和pH值估测[J]. 干旱地区农业研究, 2021, 39(1): 164-174. |
[1] | [Sun Yuan, Jia Pingping, Shang Tianhao, et al. Estimation of soil salinity and pH value based on surface hyperspectral and OLI images[J]. Agricultural Research in the Arid Areas, 2021, 39(1): 164-174.] |
[2] | 刘延锋, 靳孟贵, 金英春. 焉耆盆地土壤盐渍化状况的主成分分析[J]. 干旱地区农业研究, 2004, 22(1): 165-171. |
[2] | [Liu Yanfeng, Jin Menggui, Jin Yingchun. Principal component analysis of soil salinization in Yanqi Basin[J]. Agricultural Research in the Arid Areas, 2004, 22(1): 165-171.] |
[3] | 田长彦, 周宏飞, 刘国庆. 21世纪新疆土壤盐渍化调控与农业持续发展研究建议[J]. 干旱区地理, 2000, 23(2): 177-181. |
[3] | [Tian Changyan, Zhou Hongfei, Liu Guoqin. Research suggestions on soil salinization regulation and agricultural sustainable development in Xinjiang in the 21st century[J]. Arid Land Geography, 2000, 23(2): 177-181.] |
[4] | 魏云杰, 许模. 新疆土壤盐渍化成因及其防治对策研究[J]. 地球与环境, 2005, 33(S1): 593-597. |
[4] | [Wei Yunjie, Xu Mu. Study on the causes and countermeasures of soil salinization in Xinjiang[J]. Earth and Environment, 2005, 33(S1): 593-597.] |
[5] | 张士功, 邱建军, 张华. 我国盐渍土资源及其综合治理[J]. 中国农业资源与区划, 2000, 21(1): 54-58. |
[5] | [Zhang Shigong, Qiu Jianjun, Zhang Hua. Salinized soil resources and comprehensive management in China[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2000, 21(1): 54-58.] |
[6] | 尼加提·卡斯木, 师庆东, 郭玉川, 等. 基于EM38和WorldView-2影像的土壤盐渍化建模研究[J]. 土壤, 2019, 51(3): 594-601. |
[6] | [Nijat Kasim, Shi Qingdong, Guo Yuchuan, et al. Mapping and modelling of soil salinity using WorldView-2 data and EM38 in arid region of Keriya river, China[J]. Soils, 2019, 51(3): 594-601.] |
[7] | 陈香月, 丁建丽, 葛翔宇, 等. 基于机器学习的绿洲土壤盐渍化尺度效应研究[J]. 农业机械学报, 2021, 52(9): 312-320. |
[7] | [Chen Xiangyue, Ding Jianli, Ge Xiangyu, et al. Scale effect on soil salinization simulation in arid oasis based on machine learning methods[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(9): 312-320.] |
[8] | 黄权中, 徐旭, 吕玲娇, 等. 基于遥感反演河套灌区土壤盐分分布及对作物生长的影响[J]. 农业工程学报, 2018, 34(1): 102-109. |
[8] | [Huang Quanzhong, Lv Lingjiao, et al. Soil salinity distribution based on remote sensing and its effect on crop growth in Hetao irrigation district[J]. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(1): 102-109.] |
[9] | 翁永玲, 宫鹏. 土壤盐渍化遥感应用研究进展[J]. 地理科学, 2006, 26(3): 369-375. |
[9] | [Weng Yongling, Gong Peng. A review on remote sensing technique for salt-affected soils[J]. Scientia Geographica Sinica, 2006, 26(3): 369-375.] |
[10] | 马腾, 王耀强, 李瑞平, 等. 基于微波遥感极化目标分解的土地覆盖/土地利用分类[J]. 农业工程学报, 2015, 31(2): 259-265. |
[10] | [Ma Teng, Wang Yaoqiang, Li Ruiping, et al. Land Cover/Land Use classification based on polarimetric target decomposition of microwave remote sensing[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(2): 259-265.] |
[11] | 赵孟银. 遥感影像去云方法研究[D]. 天津: 天津科技大学, 2016. |
[11] | [Zhao Mengyin. Study of Cloud Removal Method on Remote Sensing Image[D]. Tianjin:Tianjin University of Science and Technology, 2016.] |
[12] | 雷博恩, 王世航. 微波遥感应用现状综述[J]. 科技广场, 2016, 29(6): 171-174. |
[12] | [Lei Bo’en, Wang Shihang. Review on status quo of microwave remote sensing application[J]. Science Mosaic, 2016, 29(6): 171-174.] |
[13] | 刘全明, 成秋明, 王学, 等. 河套灌区土壤盐渍化微波雷达反演[J]. 农业工程学报, 2016, 32(16): 109-114. |
[13] | [Liu Quanming, Cheng Qiuming, Wang Xue, et al. Soil salinity inversion in Hetao Irrigation district using microwave radar[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(16): 109-114.] |
[14] | Shao Y, Hu Q R, Guo H D, et al. Effect of dielectric properties of moist salinized soils on backscattering coefficients extracted from RADARSAT image[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(8): 1879-1888. |
[15] | 李彪, 王耀强. 土壤盐渍化雷达反演模拟研究[J]. 干旱区资源与环境, 2015, 29(8): 180-184. |
[15] | [Li Biao, Wang Yaoqiang. Radar inversion and simulation of salty soil salinization[J]. Journal of Arid Land Resources and Environment, 2015, 29(8): 180-184.] |
[16] | Wu W, Claudio Z, Muhaimeed A S, et al. Soil salinity prediction and mapping by machine learning regression in Central Mesopotamia, Iraq[J]. Land Degradation and Development, 2018, 29(11): 4005-4014. |
[17] | Wang N, Xue J, Peng J, et al. Integrating remote sensing and landscape characteristics to estimate soil salinity using machine learning methods: A case study from southern Xinjiang, China[J]. Remote Sensing, 2020, 12(24): 4118. |
[18] | Ma G L, Ding J L, Han L J, et al. Digital mapping of soil salinization based on Sentinel-1 and Sentinel-2 data combined with machine learning algorithms[J]. Regional Sustainability, 2021, 2(2): 177-188. |
[19] | 依力亚斯江·努尔麦麦提, 师庆东, 阿不都拉·阿不力孜, 等. 灰色评估模型定量评价于田绿洲土壤盐渍化风险[J]. 农业工程学报, 2019, 35(8): 176-184. |
[19] | [Ilyas Nurmemet, Shi Qingdong, Abdulla Abliz, et al. Quantitative evaluation of soil salinization risk in Keriya Oasis based on grey evaluation model[J]. Transactions of the Chinese Society of Agricultural Engineering, 2019, 35(8): 176-184.] |
[20] | 韩丽. 克里雅河流域于田绿洲土壤质量研究[D]. 乌鲁木齐: 新疆大学, 2014. |
[20] | [Han Li. Research on Soil Quality in Yutian Oasis of the Keriya Valley[D]. Urumqi: Xinjiang University, 2014.] |
[21] | 顾思博, 周金龙, 曾妍妍, 等. 绿洲农田土壤微量营养元素的空间变异性研究——以新疆于田县为例[J]. 干旱区资源与环境, 2020, 34(3): 118-123. |
[21] | [Gu Sibo, Zhou Jinlong, Zeng Yanyan, et al. Spatial variability of trace elements in oasis farmland soil: A case study in Yutian County, Xinjiang[J]. Journal of Arid Land Resources and Environment, 2020, 34(3): 118-123.] |
[22] | 再屯古丽·亚库普, 买买提·沙吾提, 阿卜杜萨拉木·阿布都加帕尔, 等. 基于PALSAR雷达数据的于田绿洲土壤盐渍化反演[J]. 资源科学, 2018, 40(10): 2110-2117. |
[22] | [Zaytungul Yakup, Mamat Sawut, Abdusalam Abdujappar, et al. Soil salinity inversion in Yutian Oasis based on PALSAR radar data[J]. Resources Science, 2018, 40(10): 2110-2117.] |
[23] | 周林虎, 王昊宇, 张秉来, 等. 硫酸盐渍土表观电导率与水分、盐分及粒径关系研究[J]. 干旱区研究, 2021, 38(4): 1020-1030. |
[23] | [Zhou Linhu, Wang Haoyu, Zhang Binglai, et al. The relationship between EC_a of sulfate saline soil and moisture content, salt content, and particle size[J]. Arid Zone Research, 2021, 38(4): 1020-1030.] |
[24] | 郭连坤. 基于多核Boosting多特征组合高光谱分类技术研究[D]. 西安: 西安科技大学, 2015. |
[24] | [Guo Liankun. Classification of Hyperspectral Data based on Multi-feature Combination by Multiple Kernel Boosting[D]. Xi’an: Xi’an University of Science and Technology, 2015.] |
[25] | 刘子维. 基于多特征的高分辨率遥感影像分类研究[D]. 长春: 吉林大学, 2021. |
[25] | [Liu Ziwei. Research on High-resolution Remote Sensing Image Classification based on Multi-feature[D]. Changchun: Jilin University, 2021.] |
[26] | 刘焕军, 杨昊轩, 徐梦园, 等. 基于裸土期多时相遥感影像特征及最大似然法的土壤分类[J]. 农业工程学报, 2018, 34(14): 132-139, 304. |
[26] | [Liu Huanjun, Yang Haoxuan, Xu Mengyuan, et al. Soil classification based on maximum likelihood method and features of multi-temporal remote sensing images in bare soil period[J]. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(14): 132-139, 304.] |
[27] | 邢立亭, 李净, 焦文慧. 基于MODIS和随机森林的兰州市日最高气温和最低气温估算[J]. 干旱区研究, 2020, 37(3): 689-695. |
[27] | [Xing Liting, Li Jing, Jiao Wenhui. Estimation of daily maximum and minimum temperature of Lanzhou City based on MODIS and random forest[J]. Arid Zone Research, 2020, 37(3): 689-695.] |
[28] | 陈媛媛, 郑加柱, 魏浩翰, 等. 基于不同特征的随机森林极化SAR图像分类[J]. 计算机系统应用, 2019, 28(8): 183-189. |
[28] | [Chen Yuanyuan, Zheng Jiazhu, Wei Haohan, et al. Tidal flat classification based on random forest model using different features of polarimetric SAR[J]. Computer Systems & Applications, 2019, 28(8): 183-189.] |
[29] | 徐乔, 张霄, 余绍淮, 等. 综合多特征的极化SAR图像随机森林分类算法[J]. 遥感学报, 2019, 23(4): 685-694. |
[29] | [Xu Qiao, Zhang Xiao, Yu Shaohuai, et al. Multi-feature-based classification method using random forest and superpixels for polarimetric SAR images[J]. Journal of Remote Sensing, 2019, 23(4): 685-694.] |
[30] | Belgiu M, Dragut L. Random forest in remote sensing: A review of applications and future directions[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 114: 24-31. |
[31] | 乔木, 周生斌, 卢磊, 等. 新疆渭干河流域土壤盐渍化时空变化及成因分析[J]. 地理科学进展, 2012, 31(7): 904-910. |
[31] | [Qiao Mu, Zhou Shengbin, Lu Lei, et al. Causes and spatial-temporal changes of soil salinization in Weigan River Basin, Xinjiang[J]. Progress in Geography, 2012, 31(7): 904-910.] |
[32] | 尼格拉·吐尔逊, 依力亚斯江·努尔麦麦提, 王远弘, 等. 基于H/A/α分解全极化合成孔径雷达数据的干旱区土壤盐渍化分类[J]. 江苏农业科学, 2019, 47(22): 273-279. |
[32] | [Nigela Tuerxun, Ilyas Nurmemet, Wang Yuanhong, et al. Classification of soil salinization in arid areas based on H/A/α polarization decomposition method of POLSAR data[J]. Jiangsu Agricultural Sciences, 2019, 47(22): 273-279.] |
[33] | 胡庆荣. 含水含盐土壤介电特性实验研究及对雷达图像的响应分析[D]. 北京: 中国科学院研究生院, 2003. |
[33] | [Hu Qingrong. Studies on Microwave Dielectric Behavior of Moist Salt Soil and Its Effect on Backscattering Cofficients Extracted from Radar Image[D]. Beijing: Graduate University of Chinese Academy of Sciences, 2003.] |
[34] | 贾海峰, 刘雪华. 环境遥感原理与应用[M]. 北京: 清华大学出版社, 2006. |
[34] | [Jia Haifeng, Liu Xuehua. The Principle of Environmental Remote Sensing and Its Applications[M]. Beijing: Tsinghua University Press, 2006.] |
[35] | Metternicht G I. Analysing the relationship between ground-based reflectance and environmental indicators of salinity processes in the Cochabamba valleys (Bolivia)[J]. International Journal of Ecology & Environmental Sciences, 1998, 24(4): 359-370. |
[36] | 雷志斌, 孟庆岩, 田淑芳, 等. 基于GF-3和Landsat8遥感数据的土壤水分反演研究[J]. 地球信息科学学报, 2019, 21(12): 1965-1976. |
[36] | [Lei Zhibin, Meng Qingyan, Tian Shufang, et al. Soil moisture retrieval study based on GF-3 and Landsat8 remote sensing data[J]. Journal of Geo-information Science, 2019, 21(12): 1965-1976.] |
[37] | 董显聪. 植被覆盖下盐渍土含盐量的遥感反演研究[D]. 北京: 中国科学院大学, 2021. |
[37] | [Dong Xiancong. Retrieval of Saline Soil Salinity under Vegetation Cover based on Remote Sensing[D]. Beijing: University of Chinese Academy of Sciences, 2021.] |
[38] | 刘国华. 于田绿洲土壤盐分特征及其成盐驱动因子分析[D]. 乌鲁木齐: 新疆大学, 2009. |
[38] | [Liu Guohua. Study on Soil Salinity Characteristics and Its Salt-driven Actuation Factors in Yutian Oasis[D]. Urumqi: Xinjiang University, 2009.] |
[39] | 周利颖, 李瑞平, 苗庆丰, 等. 内蒙古河套灌区紧邻排干沟土壤盐渍化与肥力特征分析[J]. 干旱区研究, 2021, 38(1): 114-122. |
[39] | [Zhou Liying, Li Ruiping, Miao Qingfeng, et al. Characteristics of salinization and fertility of saline-alkali soil adjacent to drainage ditch in Hetao irrigation area of Inner Mongolia[J]. Arid Zone Research, 2021, 38(1): 114-122.] |
[40] | 李艳菊. 渭-库绿洲土壤盐分时空动态演变及驱动因子研究[D]. 乌鲁木齐: 新疆大学, 2019. |
[40] | [Li Yanju. Temporal and Spatial Dynamic Dvolution and Driving Factors of Soil Salinity in the Ogan Kucha River Oasis[D]. Urumqi: Xinjiang University, 2019.] |
[41] | 杨劲松, 姚荣江. 黄河三角洲地区土壤水盐空间变异特征研究[J]. 地理科学, 2007, 27(3): 348-353. |
[41] | [Yang Jinsong, Yao Rongjiang. Spatial variability of soil water and salt characteristics in the Yellow River Delta[J]. Scientia Geographica Sinica, 2007, 27(3): 348-353.] |
[42] | 苏春利, 纪倩楠, 陶彦臻, 等. 河套灌区西部土壤盐渍化分异特征及其主控因素[J]. 干旱区研究, 2022, 39(3): 916-923. |
[42] | [Su Chunli, Ji Qiannan, Tao Yanzhen, et al. Differentiation characteristics and main influencing factors of soil salinization in the West of Hetao[J]. Arid Zone Research, 2022, 39(3): 916-923.] |
[43] | 王海江, 石建初, 张花玲, 等. 不同改良措施下新疆重度盐渍土壤盐分变化与脱盐效果[J]. 农业工程学报, 2014, 30(22): 102-111. |
[43] | [Wang Haijiang, Shi Jianchu, Zhang Hualing, et al. Soil salinity dynamic change and desalting effect under different improvement measures in severe salinity soil in Xinjiang[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(22): 102-111.] |
[44] | Seydehmet J, Lv G H, Nurmrmet I, et al. Model prediction of secondary soil salinization in the Keriya Oasis, Northwest China[J]. Sustainability, 2018, 10(3): 656. |
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