A METHOD FOR MONITORING HYDROLOGICAL CONDITIONS BENEATH HERBACEOUS WETLANDS USING MULTI-TEMPORAL ALOS PALSAR COHERENCE DATA

被引:2
|
作者
Zhang, Meimei [1 ,2 ]
Li, Zhen [1 ]
Tian, Bangsen [1 ]
Zhou, Jianmin [1 ]
Zeng, Jiangyuan [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
IWIDF 2015 | 2015年 / 47卷 / W4期
关键词
Hydrological conditions; Herbaceous wetlands; Interferometric synthetic aperture radar (InSAR); Coherence; Probability density function (PDF); Wet reeds extraction; SYNTHETIC-APERTURE RADAR; WATER-LEVEL CHANGES; FLORIDA EVERGLADES; AMAZON FLOODPLAIN; SAR IMAGERY; VEGETATION; INSAR; INUNDATION; DYNAMICS; PATTERNS;
D O I
10.5194/isprsarchives-XL-7-W4-221-2015
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Reed marshes, the world's most widespread type of wetland vegetation, are undergoing major changes as a result of climate changes and human activities. The presence or absence of water in reed marshes has a significant impact on the whole ecosystem and remains a key indicator to identify the effective area of a wetland and help estimate the degree of degeneration. Past studies have demonstrated the use of interferometric synthetic aperture radar (InSAR) to map water-level changes for flooded reeds. However, the identification of the different hydrological states of reed marshes is often poorly understood. The analysis given in this paper shows that L-band interferometric coherence is very sensitive to the water surface conditions beneath reed marshes and so can be used as classifier. A method based on a statistical analysis of the coherence distributions for wet and dry reeds using InSAR pairs was, therefore, investigated in this study. The experimental results were validated by in-situ data and showed very good agreement. This is the first time that information about the water cover under herbaceous wetlands has been derived using interferometric coherence values. This method can also effectively and easily be applied to monitor the hydrological conditions beneath other herbaceous wetlands.
引用
收藏
页码:221 / 226
页数:6
相关论文
共 50 条
  • [41] DAMAGE MAPPING BASED ON COHERENCE MODEL USING MULTI-TEMPORAL POLARIMETRIC- INTERFEROMETRIC UAVSAR DATA
    Jung, Jungkyo
    Kim, Duk-jin
    Yun, Sang-ho
    Lavalle, Marco
    [J]. 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 189 - 192
  • [42] A new soil sampling design method using multi-temporal and spatial data fusion
    Yang, Zedong
    Bai, Zhongke
    Qin, Zhiheng
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (14) : 21023 - 21033
  • [43] Environmental Monitoring of Bombetoka Bay and the Betsiboka Estuary, Madagascar, Using Multi-temporal Satellite Data
    Raharimahefa, Tsilavo
    Kusky, Timothy M.
    [J]. JOURNAL OF EARTH SCIENCE, 2010, 21 (02) : 210 - 226
  • [44] Paddy Monitoring in Seberang Perak, Malaysia Using Multi-Temporal Sentinel-1 Data
    Hameed, Azhar Abed
    Shariff, Abdul Rashid Bin Mohamed
    [J]. 10TH IGRSM INTERNATIONAL CONFERENCE AND EXHIBITION ON GEOSPATIAL & REMOTE SENSING, 2020, 540
  • [45] Global scale monitoring of soil and vegetation by using AMSR-E multi-temporal data
    Paloscia, S.
    Macelloni, G.
    Pampaloni, P.
    Santi, E.
    [J]. 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 1609 - 1612
  • [46] Subsidence monitoring in urban area using multi-temporal InSAR data: a case study in Ching
    Wang, Y
    Liao, MS
    Li, DR
    Lin, H
    [J]. REMOTE SENSING FOR ENVIRONMENTAL MONITORING, GIS APPLICATIONS, AND GEOLOGY IV, 2004, 5574 : 323 - 330
  • [47] A new soil sampling design method using multi-temporal and spatial data fusion
    Zedong Yang
    Zhongke Bai
    Zhiheng Qin
    [J]. Environmental Science and Pollution Research, 2022, 29 : 21023 - 21033
  • [48] Dust storm detection and monitoring using multi-temporal INSAT-3A-CCD data
    Sanwlani, Nivedita
    Chauhan, Prakash
    Navalgund, R. R.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2011, 32 (19) : 5527 - 5539
  • [49] Monitoring multi-temporal and spatial variations of water transparency in the Jiaozhou Bay using GOCI data
    Zhou, Yan
    Yu, Dingfeng
    Cheng, Wentao
    Gai, Yingying
    Yao, Huiping
    Yang, Lei
    Pan, Shunqi
    [J]. MARINE POLLUTION BULLETIN, 2022, 180
  • [50] Monitoring Archaeological Site Landscapes in Cyprus using Multi-temporal Atmospheric Corrected Image Data
    Hadjimitsis, D. G.
    Themistocleous, K.
    Agapiou, A.
    Clayton, C. R. I.
    [J]. INTERNATIONAL JOURNAL OF ARCHITECTURAL COMPUTING, 2009, 7 (01) : 121 - 138