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当前,基于机器学习的土壤水分反演与土壤水分产品数据的降尺度已成为获取土壤水分连续空间分布的2种常规手段,然而,如何有效综合2种手段的优势,获得更加准确、可靠的土壤水分分布亟需开展进一步的研究。鉴于此,以内蒙古自治区闪电河流域为研究区,以NDVI(normalized differential vegetation index)、LST(land surface temperature)和后向散射系数等为辅助数据,耦合随机森林(random forest
RF)和集合卡尔曼滤波(ensemble kalman filter
EnKF)算法,将反演和降尺度得到的土壤水分数据进行融合得到研究区1 km分辨率土壤水分数据,结合实地观测数据对模型效果进行评估和验证。结果表明:(1)基于EnKF算法的数据融合方法能够综合利用反演和降尺度的优势,进一步提升土壤水分空间分布预测的准确性。反演结果 R为0.52
RMSE为0.018 m
3
·m
-3
,降尺度结果 R为0.37
RMSE为0.022 m
3
·m
-3
,融合两者后的R提升至0.71
RMSE降低为0.010 m
3
·m
-3
;(2)流域内大部分区域土壤水分低于0.20 m
3
·m
-3
,南部边缘高海拔区域的土壤水分含量较高;结合随机森林特征重要性分析结果,NDVI、降水量以及DEM等对土壤水分空间分布的控制作用相对最为显著。该研究为准确获取土壤水分空间分布提供了一种新的思路,也为闪电河流域水资源管理等应用提供一定参考依据。
王雨诗.基于SVM-EnKF和多源遥感土壤水分的湘江流域骤旱预测研究[D].东南大学,2021(06).
曹煜,方秀琴,杨露露,蒋心远,廖美玉,任立良.基于随机森林的西辽河流域CCI土壤湿度降尺度研究[J].地球信息科学学报,2023(08).
张鹏,张巧凤,于红博,高依博,常帅,李想,乌日汗.FY-3B/3C和AMSR2土壤水分产品在内蒙古地区的适用性评价[J].干旱区资源与环境,2022(12).
王思楠,李瑞平,吴英杰,赵水霞,王秀青.基于环境变量和机器学习的土壤水分反演模型研究[J].农业机械学报,2022(05).
王雨诗,闵馨童,王成,夏晨庆,朱仟.基于EnKF的湘江流域多源遥感土壤水分数据分析[J].中国水土保持科学(中英文),2022(02).
焦月正,张安兵,王贺封,于坤,李武乾.基于Sentinel-1A数据的土壤水分反演[J].测绘与空间地理信息,2022(02).
程渊,李玉霞,李凡,何磊.基于极端随机树的闪电河流域土壤水分反演[J].遥感学报,2021(04).
曹炯玮,魏加华.集合卡尔曼滤波法在土壤湿度遥感数据融合的研究[J].青海师范大学学报(自然科学版),2019(01).
杨金明,刘志辉.Sentinel-1卫星数据产品应用探讨[J].地理空间信息,2016(12).
郑小坡,孙越君,秦其明,任华忠,高中灵,吴伶,孟庆野,王金梁,王建华.基于可见光-短波红外波谱反射率的裸土土壤含水量反演建模[J].光谱学与光谱分析,2015(08).
姚苏红,朱仲元,张圣微,张苏鲁,李杨.基于SWAT模型的内蒙古闪电河流域径流模拟研究[J].干旱区资源与环境,2013(01).
Imanpour Fatemeh,Dehghani Maryam,Yazdi Mehran.Improving SMAP soil moisture spatial resolution in different climatic conditions using remote sensing data.[J].Environmental monitoring and assessment,2023.
Mao Taoning,Shangguan Wei,Li Qingliang,Li Lu,Zhang Ye,Huang Feini,Li Jianduo,Liu Wei,Zhang Ruqing.A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation[J].Remote Sensing,2022.
Zheng Jingyao,Zhao Tianjie,Lü Haishen,Shi Jiancheng,Cosh Michael H.,Ji Dabin,Jiang Lingmei,Cui Qian,Lu Hui,Yang Kun,Wigneron Jean-Pierre,Li Xiaojun,Zhu Yonghua,Hu Lu,Peng Zhiqing,Zeng Yelong,Wang Xiaoyi,Kang Chuen Siang.Assessment of 24 soil moisture datasets using a new in situ network in the Shandian River Basin of China[J].Remote Sensing of Environment,2022.
Karami Ayoob,Moradi Hamid Reza,Mousivand Alijafar,van Dijk Albert I. J. M.,Renzullo Luigi.Using ensemble learning to take advantage of high-resolution radar backscatter in conjunction with surface features to disaggregate SMAP soil moisture product[J].International Journal of Remote Sensing,2022.
grid.412057.5, 0000 0004 0612 7328, Department of Rangeland and Watershed Management, University of Kashan, Kashan, Iran,grid.412475.1, 0000 0001 0506 807X, Faculty of Desert Studies, University of Semnan, Semnan, Iran,grid.46072.37, 0000 0004 0612 7950, Laboratory of Remote Sensing and GIS, Department of Soil Science, University of Tehran, P.O. Box: 4111, 31587-77871, Karaj, Iran,grid.472261.4, 0000 0004 5376 7555, Department of Botany, DAV University, 144012, Jalandhar, Punjab,, India.Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images[J].Arabian Journal of Geosciences,2020.
Fengmin Hu,Zushuai Wei,Wen Zhang,Donyu Dorjee,Lingkui Meng.A spatial downscaling method for SMAP soil moisture through visible and shortwave-infrared remote sensing data[J].Journal of Hydrology,2020.
Shouzhang Peng,Yongxia Ding,Wenzhao Liu,Zhi Li.1km monthly temperature and precipitation dataset for China from 1901 to 2017[J].Earth System Science Data,2019.
Jueying Bai,Qian Cui,Wen Zhang,Lingkui Meng.An Approach for Downscaling SMAP Soil Moisture by Combining Sentinel-1 SAR and MODIS Data[J].Remote Sensing,2019.
Di Long,Liangliang Bai,La Yan,Caijin Zhang,Wenting Yang,Huimin Lei,Jinling Quan,Xianyong Meng,Chunxiang Shi.Generation of spatially complete and daily continuous surface soil moisture of high spatial resolution[J].Remote Sensing of Environment,2019.
Shaodan Chen,Dunxian She,Liping Zhang,Mengyao Guo,Xin Liu.Spatial Downscaling Methods of Soil Moisture Based on Multisource Remote Sensing Data and Its Application[J].Water,2019.
Zushuai Wei,Yizhuo Meng,Wen Zhang,Jian Peng,Lingkui Meng.Downscaling SMAP soil moisture estimation with gradient boosting decision tree regression over the Tibetan Plateau[J].Remote Sensing of Environment,2019.
Yunqian Wang,Jing Yang,Yaning Chen,Gonghuan Fang,Weili Duan,Yupeng Li,Philippe De Maeyer.Quantifying the Effects of Climate and Vegetation on Soil Moisture in an Arid Area China[J].Water,2019.
Zijing Liu,Min Min,Jun Li,Fenglin Sun,Di Di,Yufei Ai,Zhenglong Li,Danyu Qin,Guicai Li,Yinjing Lin,Xiaolin Zhang.Local Severe Storm Tracking and Warning in Pre-Convection Stage from the New Generation Geostationary Weather Satellite Measurements[J].Remote Sensing,2019.
Peyman Abbaszadeh,Hamid Moradkhani,Xiwu Zhan.Downscaling SMAP Radiometer Soil Moisture Over the CONUS Using an Ensemble Learning Method[J].Water Resources Research,2019.
Chen Quan,Zeng Jiangyuan,Cui Chenyang,Li Zhen,Chen Kun Shan,Bai Xiaojing,Xu Jia.Soil Moisture Retrieval From SMAP: A Validation and Error Analysis Study Using Ground-Based Observations Over the Little Washita Watershed[J].IEEE Transactions on Geoscience and Remote Sensing,2018.
J. Kolassa,R.H. Reichle,Q. Liu,S.H. Alemohammad,P. Gentine,K. Aida,J. Asanuma,S. Bircher,T. Caldwell,A. Colliander,M. Cosh,C. Holifield Collins,T.J. Jackson,J. Martínez-Fernández,H. McNairn,A. Pacheco,M. Thibeault,J.P. Walker.Estimating surface soil moisture from SMAP observations using a Neural Network technique[J].Remote Sensing of Environment,2018.
Javier Loizu,Christian Massari,Jesús Álvarez-Mozos,Angelica Tarpanelli,Luca Brocca,Javier Casalí.On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation[J].Advances in Water Resources,2018.
Hengl Tomislav,Mendes de Jesus Jorge,Heuvelink Gerard B M,Ruiperez Gonzalez Maria,Kilibarda Milan,Blagotić Aleksandar,Shangguan Wei,Wright Marvin N,Geng Xiaoyuan,Bauer-Marschallinger Bernhard,Guevara Mario Antonio,Vargas Rodrigo,MacMillan Robert A,Batjes Niels H,Leenaars Johan G B,Ribeiro Eloi,Wheeler Ichsani,Mantel Stephan,Kempen Bas.SoilGrids250m: Global gridded soil information based on machine learning.[J].PloS one,2017.
Santi E.,Paloscia S.,Pettinato S.,Brocca L.,Ciabatta L.,Entekhabi D..On the synergy of SMAP, AMSR2 AND SENTINEL-1 for retrieving soil moisture[J].International Journal of Applied Earth Observations and Geoinformation,2017.
A. Colliander,T.J. Jackson,R. Bindlish,S. Chan,N. Das,S.B. Kim,M.H. Cosh,R.S. Dunbar,L. Dang,L. Pashaian,J. Asanuma,K. Aida,A. Berg,T. Rowlandson,D. Bosch,T. Caldwell,K. Caylor,D. Goodrich,H. al Jassar,E. Lopez-Baeza,J. Martínez-Fernández,A. González-Zamora,S. Livingston,H. McNairn,A. Pacheco,M. Moghaddam,C. Montzka,C. Notarnicola,G. Niedrist,T. Pellarin,J. Prueger,J. Pulliainen,K. Rautiainen,J. Ramos,M. Seyfried,P. Starks,Z. Su,Y. Zeng,R. van der Velde,M. Thibeault,W.Validation of SMAP surface soil moisture products with core validation sites[J].Remote Sensing of Environment,2017.
H. Lievens,B. Martens,N.E.C. Verhoest,S. Hahn,R.H. Reichle,D.G. Miralles.Assimilation of global radar backscatter and radiometer brightness temperature observations to improve soil moisture and land evaporation estimates[J].Remote Sensing of Environment,2017.
Jungho Im,Seonyoung Park,Jinyoung Rhee,Jongjin Baik,Minha Choi.Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches[J].Environmental Earth Sciences,2016.
Charlotte Pelletier,Silvia Valero,Jordi Inglada,Nicolas Champion,Gérard Dedieu.Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas[J].Remote Sensing of Environment,2016.
Nemesio Rodriguez-Fernandez,Filipe Aires,Philippe Richaume,Yann H. Kerr,Catherine Prigent,Jana Kolassa,François Cabot,Carlos Jimenez,Ali Mahmoodi,Matthias Drusch.Soil Moisture Retrieval Using Neural Networks: Application to SMOS.[J].IEEE Trans. Geoscience and Remote Sensing,2015.
Wolfgang Wagner,Sebastian Hahn,Richard Kidd,Thomas Melzer,Zoltan Bartalis,Stefan Hasenauer,Julia Figa-Saldaña,Patricia de Rosnay,Alexander Jann,Stefan Schneider,Jürgen Komma,Gerhard Kubu,Katharina Brugger,Christoph Aubrecht,Johann Züger,Ute Gangkofner,Stefan Kienberger,Luca Brocca,Yong Wang,Günter Blöschl,Josef Eitzinger,Kla Steinnocher.The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications[J].Meteorologische Zeitschrift,2013.
Wade T. Crow,Aaron A. Berg,Michael H. Cosh,Alexander Loew,Binayak P. Mohanty,Rocco Panciera,Patricia Rosnay,Dongryeol Ryu,Jeffrey P. Walker.Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products[J].Reviews of Geophysics,2012.
Draper, C. S.,Reichle, R. H.,M. De Lannoy, G. J.,Liu, Q..Assimilation of passive and active microwave soil moisture retrievals[J].Geophysical Research Letters,2012.
Sonia I. Seneviratne,Thierry Corti,Edouard L. Davin,Martin Hirschi,Eric B. Jaeger,Irene Lehner,Boris Orlowsky,Adriaan J. Teuling.Investigating soil moisture–climate interactions in a changing climate: A review[J].Earth Science Reviews,2010.
Leo Breiman.Random Forests.[J].Machine Learning,2001.
Geir Evensen.Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics[J].Journal of Geophysical Research: Oceans,1994.
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