Permafrost Soil Moisture Monitoring Using Multi-Temporal TerraSAR-X Data in Beiluhe of Northern Tibet, China

被引:11
|
作者
Wang, Chao [1 ,2 ]
Zhang, Zhengjia [1 ,2 ,3 ]
Paloscia, Simonetta [4 ]
Zhang, Hong [1 ]
Wu, Fan [1 ]
Wu, Qingbai [5 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] China Univ Geosci, Facaulty Informat Engn, Wuhan 430074, Hubei, Peoples R China
[4] CNR IFAC, Inst Appl Phys, Natl Res Council, I-50019 Florence, Italy
[5] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Gansu, Peoples R China
来源
REMOTE SENSING | 2018年 / 10卷 / 10期
基金
中国国家自然科学基金;
关键词
permafrost; soil moisture; SAR; multi-mode; Tibet; SYNTHETIC-APERTURE RADAR; SURFACE-ROUGHNESS; SAR DATA; L-BAND; EMPIRICAL-MODEL; PLATEAU; ASAR; RETRIEVAL; IMAGES; SERIES;
D O I
10.3390/rs10101577
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Global change has significant impact on permafrost region in the Tibet Plateau. Soil moisture (SM) of permafrost is one of the most important factors influencing the energy flux, ecosystem, and hydrologic process. The objectives of this paper are to retrieve the permafrost SM using time-series SAR images, without the need of auxiliary survey data, and reveal its variation patterns. After analyzing the characteristics of time-series radar backscattering coefficients of different landcover types, a two-component SM retrieval model is proposed. For the alpine meadow area, a linear retrieving model is proposed using the TerraSAR-X time-series images based on the assumption that the lowest backscattering coefficient is measured when the soil moisture is at its wilting point and the highest backscattering coefficient represents the water-saturated soil state. For the alpine desert area, the surface roughness contribution is eliminated using the dual SAR images acquired in the winter season with different incidence angles when retrieving soil moisture from the radar signal. Before the model implementation, landcover types are classified based on their backscattering features. 22 TerraSAR-X images are used to derive the soil moisture in Beiluhe, Northern Tibet with different incidence angles. The results obtained from the proposed method have been validated using in-situ soil moisture measurements, thus obtaining RMSE and Bias of 0.062 cm(3)/cm(3) and 4.7%, respectively. The retrieved time-series SM maps of the study area point out the spatial and temporal SM variation patterns of various landcover types.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Application of Multi-temporal TerraSAR-X Data to Map Winter Wheat Planted Areas in Hokkaido, Japan
    Sonobe, Rei
    Tani, Hiroshi
    Wang, Xiufeng
    Kobayashi, Nobuyuki
    Kimura, Atsushi
    Shimamura, Hideki
    JARQ-JAPAN AGRICULTURAL RESEARCH QUARTERLY, 2014, 48 (04): : 465 - 470
  • [22] Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images
    Gorrab, Azza
    Zribi, Mehrez
    Baghdadi, Nicolas
    Mougenot, Bernard
    Fanise, Pascal
    Chabaane, Zohra Lili
    REMOTE SENSING, 2015, 7 (08) : 10098 - 10116
  • [23] Change Detection in Multi-Temporal TerraSAR-X SAR Images Using a Hierarchical Markov Model on Regions
    Liu, Jie
    Yang, Wen
    Xia, Gui-Song
    Liao, Mingsheng
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 129 - 132
  • [24] TerraSAR-X Data in Cut Slope Soil Stability Monitoring in Malaysia
    Rauste, Yrjo
    Lateh, Habibah Bt
    Jefriza
    Mohd, Muhiyuddin Wan Ibrahim Wan
    Lonnqvist, Anne
    Hame, Tuomas
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (09): : 3354 - 3363
  • [25] Monitoring Rice Growth in Southern China Using TerraSAR-X Dual Polarization Data
    Chen Jinsong
    Han Yu
    Deng Xinping
    2017 6TH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS, 2017, : 421 - 423
  • [26] MONITORING THREE DIMENSIONAL DISPLACEMENTS OF THE SHUPING LANDSLIDE, THREE GORGES AREA WITH MULTI-TEMPORAL TERRASAR-X SAR IMAGES
    Shi, Xuguo
    Zhang, Lu
    Liao, Mingsheng
    Shi, Shuo
    IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 478 - 481
  • [27] Active Layer Thickness Retrieval of Qinghai-Tibet Permafrost Using the TerraSAR-X InSAR Technique
    Wang, Chao
    Zhang, Zhengjia
    Zhang, Hong
    Zhang, Bo
    Tang, Yixian
    Wu, Qingbai
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (11) : 4403 - 4413
  • [28] Use of TerraSAR-X Data to Retrieve Soil Moisture Over Bare Soil Agricultural Fields
    Baghdadi, Nicolas
    Aubert, Maelle
    Zribi, Mehrez
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2012, 9 (03) : 512 - 516
  • [29] Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust
    Aubert, M.
    Baghdadi, N.
    Zribi, M.
    Douaoui, A.
    Loumagne, C.
    Baup, F.
    El Hajj, M.
    Garrigues, S.
    REMOTE SENSING OF ENVIRONMENT, 2011, 115 (08) : 1801 - 1810
  • [30] ICE VELOCITY MEASUREMENTS OF NARSSAP SERMIA IN GREENLAND USING MULTI-TEMPORAL TERRASAR-X/TANDEM-X SAR OBSERVATIONS
    Jung, Seong-Woo
    Park, Seo-Woo
    Hong, Sang-Hoon
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 2342 - 2345